{
  "version": 3,
  "sources": ["ssg:https://framerusercontent.com/modules/NEd4VmDdsxM3StIUbddO/9rhBPUZttCbLCWqJEL42/YouTube.js", "ssg:https://framerusercontent.com/modules/DUaBI8Z0zQBEAftOFMh3/dGyNFE5np9YLEu9UoUFM/LW0fAVOt9-8.js"],
  "sourcesContent": ["import{jsx as _jsx,jsxs as _jsxs}from\"react/jsx-runtime\";import{useReducer,useState,useSyncExternalStore}from\"react\";import{ControlType,addPropertyControls}from\"framer\";import{useIsOnCanvas,emptyStateStyle,containerStyles,defaultEvents,useRadius,borderRadiusControl}from\"https://framer.com/m/framer/default-utils.js@^0.45.0\";var PlayOptions;(function(PlayOptions){PlayOptions[\"Normal\"]=\"Off\";PlayOptions[\"Auto\"]=\"On\";PlayOptions[\"Loop\"]=\"Loop\";})(PlayOptions||(PlayOptions={}));var ThumbnailOptions;(function(ThumbnailOptions){ThumbnailOptions[\"High\"]=\"High Quality\";ThumbnailOptions[\"Medium\"]=\"Medium Quality\";ThumbnailOptions[\"Low\"]=\"Low Quality\";ThumbnailOptions[\"Off\"]=\"Off\";})(ThumbnailOptions||(ThumbnailOptions={}));var ThumbnailFormat;(function(ThumbnailFormat){ThumbnailFormat[\"WebP\"]=\"webp\";ThumbnailFormat[\"JPG\"]=\"jpg\";})(ThumbnailFormat||(ThumbnailFormat={}));let _isBot=null;function isBot(){if(_isBot===null)_isBot=/bot|-Google|Google-|yandex|ia_archiver/iu.test(navigator.userAgent);return _isBot;}const emptySubscribe=()=>()=>{};/**\n * @framerIntrinsicWidth 560\n * @framerIntrinsicHeight 315\n *\n * @framerSupportedLayoutWidth fixed\n * @framerSupportedLayoutHeight fixed\n *\n * @framerComponentPresetProps isRed, borderRadius\n */export function Youtube({url,play,shouldMute,thumbnail,isRed,onClick,onMouseEnter,onMouseLeave,onMouseDown,onMouseUp,title,...props}){const onCanvas=useIsOnCanvas();const isAutoplay=play!==\"Off\";const showThumbnail=onCanvas||thumbnail!==\"Off\"&&!isAutoplay;const[isPreloading,preloadVideo]=useReducer(()=>true,false);const[showVideo,startVideo]=useReducer(()=>true,!showThumbnail);const[isHovered,setHovered]=useState(false);// https://tkdodo.eu/blog/avoiding-hydration-mismatches-with-use-sync-external-store#usesyncexternalstore\nconst iframeIsDefaultVisible=useSyncExternalStore(emptySubscribe,// bots should not have display:none on the iframe\n()=>isBot(),()=>false);const borderRadius=useRadius(props);const hasBorderRadius=borderRadius!==\"0px 0px 0px 0px\"&&borderRadius!==\"0px\";if(url===\"\"){return /*#__PURE__*/_jsx(Instructions,{});}const parsedURL=parseVideoURL(url);if(parsedURL===undefined){return /*#__PURE__*/_jsx(ErrorMessage,{message:\"Invalid Youtube URL.\"});}const[videoId,embedURL]=parsedURL;// https://stackoverflow.com/questions/2068344/how-do-i-get-a-youtube-video-thumbnail-from-the-youtube-api\nconst thumbnailURL=getThumbnailURL(videoId,thumbnail,getWebPSupported()?\"webp\":\"jpg\");// https://developers.google.com/youtube/player_parameters\nconst searchParams=embedURL.searchParams;searchParams.set(\"iv_load_policy\",\"3\");searchParams.set(\"rel\",\"0\");searchParams.set(\"modestbranding\",\"1\");searchParams.set(\"playsinline\",\"1\");if(// bots shouldn't autoplay the video but see the iframe in the DOM\n!iframeIsDefaultVisible&&(isAutoplay||// when there is no thumbnail, we don't want to autoplay, unless video is started\nshowThumbnail&&showVideo)){searchParams.set(\"autoplay\",\"1\");}if(isAutoplay&&shouldMute){searchParams.set(\"mute\",\"1\");}if(play===\"Loop\"){searchParams.set(\"loop\",\"1\");searchParams.set(\"playlist\",videoId);}if(!isRed){searchParams.set(\"color\",\"white\");}return /*#__PURE__*/_jsxs(\"article\",{onPointerEnter:()=>setHovered(true),onPointerLeave:()=>setHovered(false),onPointerOver:preloadVideo,onKeyDown:startVideo,onClick:startVideo,style:{...wrapperStyle,borderRadius,transform:// Safari sometimes struggles to render border-radius:\n// - on the canvas when changing from 0 to any other value\n// - or when rendering an iframe\nhasBorderRadius&&(showVideo||onCanvas)?\"translateZ(0.000001px)\":\"unset\",cursor:\"pointer\",overflow:\"hidden\"},role:\"presentation\",children:[isPreloading&&/*#__PURE__*/_jsx(\"link\",{rel:\"preconnect\",href:\"https://www.youtube.com\"}),isPreloading&&/*#__PURE__*/_jsx(\"link\",{rel:\"preconnect\",href:\"https://www.google.com\"}),/*#__PURE__*/_jsx(\"div\",{style:{...videoStyle,background:showThumbnail?`center / cover url(${thumbnailURL}) no-repeat`:undefined}}),!onCanvas?/*#__PURE__*/_jsx(\"iframe\",{title:title||\"Youtube Video\",style:{...videoStyle,display:showVideo||iframeIsDefaultVisible?undefined:\"none\"},src:embedURL.href,frameBorder:\"0\",allow:\"presentation; fullscreen; accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture\",onClick:onClick,onMouseEnter:onMouseEnter,onMouseLeave:onMouseLeave,onMouseDown:onMouseDown,onMouseUp:onMouseUp,loading:\"lazy\"}):null,showVideo||iframeIsDefaultVisible?null:/*#__PURE__*/_jsx(PlayButton,{onClick:startVideo,isHovered:isHovered,isRed:isRed})]});}Youtube.displayName=\"YouTube\";addPropertyControls(Youtube,{url:{type:ControlType.String,title:\"Video\"},play:{type:ControlType.Enum,title:\"Autoplay\",options:Object.values(PlayOptions)},shouldMute:{title:\"Mute\",type:ControlType.Boolean,enabledTitle:\"Yes\",disabledTitle:\"No\",hidden(props){return props.play===\"Off\";}},thumbnail:{title:\"Thumbnail\",description:\"Showing a thumbnail improves performance.\",type:ControlType.Enum,options:Object.values(ThumbnailOptions),hidden(props){return props.play!==\"Off\";}},isRed:{title:\"Color\",type:ControlType.Boolean,enabledTitle:\"Red\",disabledTitle:\"White\"},...borderRadiusControl,...defaultEvents});const defaultProps={url:\"https://youtu.be/smPos0mJvh8\",play:\"Off\",shouldMute:true,thumbnail:\"Medium Quality\",isRed:true};Youtube.defaultProps=defaultProps;function parseVideoURL(urlString){let url;try{url=new URL(urlString);}catch{const embedURL=getEmbedURL(urlString);return[urlString,embedURL];}if(url.hostname===\"youtube.com\"||url.hostname===\"www.youtube.com\"||url.hostname===\"youtube-nocookie.com\"||url.hostname===\"www.youtube-nocookie.com\"){const pathSegments=url.pathname.slice(1).split(\"/\");// https://www.youtube.com/watch?v=Fop2oskTug8\nif(pathSegments[0]===\"watch\"){const videoId=url.searchParams.get(\"v\");const embedURL=getEmbedURL(videoId);return[videoId,embedURL];}// https://www.youtube.com/embed/Fop2oskTug8\nif(pathSegments[0]===\"embed\"){const videoId=pathSegments[1];return[videoId,url];}}// https://youtu.be/Fop2oskTug8\nif(url.hostname===\"youtu.be\"){const videoId=url.pathname.slice(1);const embedURL=getEmbedURL(videoId);return[videoId,embedURL];}}function getEmbedURL(videoId){return new URL(`https://www.youtube.com/embed/${videoId}`);}function getThumbnailURL(videoId,res,format=\"jpg\"){// https://gist.github.com/a1ip/be4514c1fd392a8c13b05e082c4da363\nconst useWebP=format===\"webp\";const pre=useWebP?\"https://i.ytimg.com/vi_webp/\":\"https://i.ytimg.com/vi/\";const ext=useWebP?\"webp\":\"jpg\";switch(res){case\"Low Quality\":return`${pre}${videoId}/hqdefault.${ext}`;case\"Medium Quality\":return`${pre}${videoId}/sddefault.${ext}`;case\"High Quality\":return`${pre}${videoId}/maxresdefault.${ext}`;default:return`${pre}${videoId}/0.${ext}`;}}let _getWebPSupported;// https://stackoverflow.com/a/27232658\nfunction getWebPSupported(){// We're going to default to webp because it's pretty widely supported by now\nif(!window){return true;}if(_getWebPSupported!==undefined){return _getWebPSupported;}const element=document.createElement(\"canvas\");if(element.getContext&&element.getContext(\"2d\")){// was able or not to get WebP representation\nreturn element.toDataURL(\"image/webp\").indexOf(\"data:image/webp\")===0;}else{// very old browser like IE 8, canvas not supported\nreturn false;}}// Helper components\nfunction Instructions(){return /*#__PURE__*/_jsx(\"div\",{style:{...emptyStateStyle,overflow:\"hidden\"},children:/*#__PURE__*/_jsx(\"div\",{style:centerTextStyle,children:\"To embed a Youtube video, add the URL to the properties\\xa0panel.\"})});}function ErrorMessage({message}){return /*#__PURE__*/_jsx(\"div\",{className:\"framerInternalUI-errorPlaceholder\",style:{...containerStyles,overflow:\"hidden\"},children:/*#__PURE__*/_jsxs(\"div\",{style:centerTextStyle,children:[\"Error: \",message]})});}function PlayButton({onClick,isHovered,isRed}){return /*#__PURE__*/_jsx(\"button\",{onClick:onClick,\"aria-label\":\"Play\",style:buttonStyle,children:/*#__PURE__*/_jsxs(\"svg\",{height:\"100%\",version:\"1.1\",viewBox:\"0 0 68 48\",width:\"100%\",children:[/*#__PURE__*/_jsx(\"path\",{d:\"M66.52,7.74c-0.78-2.93-2.49-5.41-5.42-6.19C55.79,.13,34,0,34,0S12.21,.13,6.9,1.55 C3.97,2.33,2.27,4.81,1.48,7.74C0.06,13.05,0,24,0,24s0.06,10.95,1.48,16.26c0.78,2.93,2.49,5.41,5.42,6.19 C12.21,47.87,34,48,34,48s21.79-0.13,27.1-1.55c2.93-0.78,4.64-3.26,5.42-6.19C67.94,34.95,68,24,68,24S67.94,13.05,66.52,7.74z\",fill:isHovered?isRed?\"#f00\":\"#000\":\"#212121\",fillOpacity:isHovered?isRed?1:.8:.8,style:{transition:\"fill .1s cubic-bezier(0.4, 0, 1, 1), fill-opacity .1s cubic-bezier(0.4, 0, 1, 1)\"}}),/*#__PURE__*/_jsx(\"path\",{d:\"M 45,24 27,14 27,34\",fill:\"#fff\"})]})});}const buttonStyle={position:\"absolute\",top:\"50%\",left:\"50%\",transform:\"translate(-50%, -50%)\",width:68,height:48,padding:0,border:\"none\",background:\"transparent\",cursor:\"pointer\"};const wrapperStyle={position:\"relative\",width:\"100%\",height:\"100%\"};const centerTextStyle={textAlign:\"center\",minWidth:140};const videoStyle={position:\"absolute\",top:0,left:0,height:\"100%\",width:\"100%\"};\nexport const __FramerMetadata__ = {\"exports\":{\"Youtube\":{\"type\":\"reactComponent\",\"name\":\"Youtube\",\"slots\":[],\"annotations\":{\"framerContractVersion\":\"1\",\"framerSupportedLayoutWidth\":\"fixed\",\"framerComponentPresetProps\":\"isRed, borderRadius\",\"framerIntrinsicWidth\":\"560\",\"framerIntrinsicHeight\":\"315\",\"framerSupportedLayoutHeight\":\"fixed\"}},\"__FramerMetadata__\":{\"type\":\"variable\"}}}\n//# sourceMappingURL=./YouTube.map", "import{jsx as e,jsxs as i}from\"react/jsx-runtime\";import{ComponentPresetsConsumer as t,Link as n}from\"framer\";import{motion as a}from\"framer-motion\";import*as o from\"react\";import{Youtube as r}from\"https://framerusercontent.com/modules/NEd4VmDdsxM3StIUbddO/9rhBPUZttCbLCWqJEL42/YouTube.js\";export const richText=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring alerts can benefit many industries, particularly those in the banking and financial services sectors. These include traditional banks, credit unions, money transfer companies, insurance providers, and more. However, other industries such as eCommerce businesses and online payment providers can also put this tool to use to protect their customers' accounts from fraud or illegal activities. In fact, any organization that handles online transactions of value or sensitive customer data should consider using transaction monitoring alerts to help keep its customers secure.\"}),/*#__PURE__*/e(\"p\",{children:\"Let\u2019s take a look at the utility of transaction monitoring alerts across a variety of industries.\"}),/*#__PURE__*/e(\"h2\",{children:\"Transaction monitoring alerts in fintech\"}),/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring alerts can be used in a variety of ways in the fintech sector. For example, they may be used to alert financial institutions when suspicious transactions occur, such as large sums of money being transferred or sent internationally. Financial institutions can then take the necessary steps to investigate and prevent any potential fraudulent activities. In addition, transaction monitoring alerts can be used to detect and monitor unusual patterns of customer behavior, such as sudden changes in spending habits that could indicate identity theft or other forms of fraud. By identifying and adequately reacting to suspicious activity early on, businesses can reduce costs associated with fraud investigations and chargebacks.\"}),/*#__PURE__*/e(\"p\",{children:\"Some examples of transaction monitoring alerts in fintech include:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Irregular changes in customer balance or account activity\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unusual transfers between accounts owned by the same person\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Suspicious trades based on correlations between previously unrelated assets\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unusually large sums being moved out of an account without prior notice\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unexpected bank transfers from foreign countries.\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"Taking advantage of transaction monitoring alerts in eCommerce\"}),/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring alerts are especially useful in the e-commerce space due to the rise of online payment fraud. These alerts can be used to detect suspicious transactions that may indicate fraudulent activity, such as high-ticket orders placed or products requested to be shipped internationally. Additionally, transaction monitoring alerts can also detect unusual customer behavior and help verify customer information at key customer journey points (e.g. prior to completing an order or before initiating a refund).\"}),/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring can also improve e-commerce customer experience by providing accurate, real-time alerts about suspicious activities. These alerts allow businesses to take proactive steps to prevent fraud and identity theft before it occurs. Finally, transaction monitoring has been known to reduce false positives in many instances. This helps ensure that only actual suspicious activities are flagged and that customers are not inconvenienced by unnecessary interventions.\"}),/*#__PURE__*/e(\"p\",{children:\"Here are a few examples of transaction monitoring alerts in eCommerce:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Receiving multiple orders with the same card details within a short period of time\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"A significant increase in order volume from a single customer\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Purchases made using an unfamiliar IP address, email address etc\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Orders over a certain value being placed more frequently than usual\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Purchases being sent to new shipping addresses\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unusual payment methods being used.\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"How insurance organizations make use of transaction monitoring alerts\"}),/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring alerts can provide a number of benefits to the insurance industry. Firstly, they can help reduce fraudulent claims by quickly detecting fraud patterns and preventing them before the business incurs steep losses. This can result in cost savings for insurance companies, as well as improved customer satisfaction due to the timely resolution of fraud cases. Secondly, transaction monitoring alerts can be used to detect suspicious activities that may indicate identity theft or other forms of fraud, helping to protect customers' data and improve overall security. Finally, transaction monitoring can be used to detect suspicious changes in customer behavior which may cause potential losses if they go undetected. This helps to proactively identify risks and improve customer experience and trust in the insurance company.\"}),/*#__PURE__*/e(\"p\",{children:\"These are some of the common examples of alerts at insurance organizations:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Abnormal number of claim submissions from a single provider or customer\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unusually high-value claims submitted with suspicious supporting documentation\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Claims being made for services that are not covered by the specific policy\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Multiple claims for the same incident from different providers\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unexpected cancellations and changes to insurance policies.\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"Transaction monitoring alerts in healthcare\"}),/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring alerts can provide a number of benefits to healthcare organizations. By detecting and preventing fraudulent claims, they can help ensure that payments are being made correctly and that patient information is not being compromised. Additionally, these alerts can detect suspicious patterns of customer behavior which may indicate identity theft or other forms of fraud. This helps improve patient safety and protects the integrity of health data.\"}),/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring alerts can also make sure that customers' information is verified prior to granting access to services such as medical insurance plans. In addition, they can be used to detect and act on suspicious pharmaceutical orders, helping to protect patients from receiving counterfeit medication or inappropriate prescriptions. All in all, transaction monitoring alerts can provide an additional layer of security for healthcare organizations and help protect the safety of their patients.\"}),/*#__PURE__*/e(\"p\",{children:\"Below are a few examples of transaction monitoring alerts in healthcare:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"A large number of prescriptions with the same active drug ingredients, issued to different people at the same time\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unusual billing patterns for medical services, such as ordering too many tests or treatments for a single patient\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Claims submitted from unfamiliar states or countries where the patient has never been before\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Unfamiliar providers treating the same patient more than once\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Multiple prescriptions are being filled by a single pharmacy.\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"Make transaction monitoring alerts work for your business\"}),/*#__PURE__*/e(\"p\",{children:\"Did you know that you can identify suspicious activity with Oscilar's AI transaction monitoring solution? Oscilar\u2019s fraud detection platform gives you a comprehensive view of your customers\u2019 activity. With real-time decisioning on suspicious transactions, Oscilar helps you identify bad actors, fight fraud and stay compliant. Learn how Oscilar's AI Transaction Monitoring can help with your fraud prevention and compliance needs \u2013 let\u2019s talk!\"})]});export const richText1=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"The rapid rise in online business transactions has made Know Your Customer (KYC) a very vital aspect of accessing important services. From opening a bank account to simply placing an order online, a KYC form is a key part of the onboarding process for businesses to identify clients and expose fraud. There are many benefits to designing a frictionless and secure KYC process, chief among them being the prevention of fraud. By ensuring that all customers are properly vetted from the outset, companies can not only prevent criminal activities like bribery, fraud, money laundering, and identity theft but also attract more customers and increase revenue.\"}),/*#__PURE__*/e(\"h2\",{children:\"What are KYC and KYB?\"}),/*#__PURE__*/e(\"p\",{children:\"KYC verification is the process of verifying the identity of a customer. This usually includes checks like verifying government-issued ID documents and making sure that the customer\u2019s name, date of birth, and address match up.\"}),/*#__PURE__*/e(\"p\",{children:\"In some cases, additional information may be required to verify a customer\u2019s identity. This could include things like utility bills or bank statements. The level of due diligence will vary depending on the industry and the risk profile of the customer.\"}),/*#__PURE__*/e(\"p\",{children:\"The goal of KYC verification is to ensure that a customer is who they say they are, and that they are not engaged in any illegal activities. At the same time, KYC vetting cannot come at the cost of customer churn due to friction during the onboarding process.\"}),/*#__PURE__*/e(\"p\",{children:\"KYC is a fine balance between growth and fraud; an ideal KYC process introduces the minimum amount of friction required to accurately flag fraudulent customers.\"}),/*#__PURE__*/i(\"p\",{children:[\"The following are the \",/*#__PURE__*/e(n,{href:\"https://www.fincen.gov/news/news-releases/fincen-reminds-financial-institutions-cdd-rule-becomes-effective-today\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"three pillars of KYC\"})}),\":\"]}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Customer Identification Program (CIP)\"}),\": Verify that the customer is who they say they are\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Customer Due Diligence (CDD)\"}),\": Assess the customer\u2019s level of risk, including reviewing the beneficial owners of a company\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Continuous monitoring\"}),\": Monitor client transaction patterns and report suspicious activity on an ongoing basis\"]})})]}),/*#__PURE__*/e(\"h3\",{children:\"KYB: KYC for Business\"}),/*#__PURE__*/e(\"p\",{children:\"Know Your Business (KYB) is an extension of KYC for business suppliers or partners. Just as companies need to vet individuals before allowing them to open a bank account or invest through their platform, companies also need to vet other businesses they work with.\"}),/*#__PURE__*/e(\"p\",{children:\"KYB processes involve:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Identifying high-risk businesses.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Determining the nature of the business including what it sells, what service it provides, and who it partners with.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Collecting documents like articles of incorporation, business licenses, partnership agreements, and financial statements.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Identifying and verifying ultimate beneficial owners (UBO) before establishing a business relationship. A beneficial owner may not be the owner or company leader but is a person who ultimately benefits from the business transactions.\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"What is KYC fraud detection?\"}),/*#__PURE__*/e(\"p\",{children:\"KYC (Know Your Customer) fraud detection is the process of identifying, monitoring, and preventing fraudulent activities in the financial system. It involves verifying the identity of customers to ensure they are who they claim to be and that their transactions do not involve any suspicious activity. KYC fraud detection aims to protect organizations from potential losses due to fraud, money laundering, and terrorist financing. KYC fraud detection systems provide organizations with the tools to detect and investigate fraud promptly. By verifying customer identity and analyzing potential fraudulent transactions, organizations can mitigate their risk exposure and minimize financial losses. This helps organizations protect themselves from costly violations of laws, regulations, and internal guidelines. KYC fraud detection is an essential component of any organization's financial compliance program as it provides a proactive approach to identifying and preventing fraud. By employing effective KYC fraud detection systems and procedures, organizations can ensure that their customers are legitimate and their transactions are secure.\"}),/*#__PURE__*/e(\"h2\",{children:\"Types of fraud detected by the KYC process\"}),/*#__PURE__*/e(\"p\",{children:\"KYC fraud detection systems can detect a variety of types of fraud, including money laundering, identity theft, and financial crimes. Money laundering is the process of disguising illegal proceeds from criminal activities to make them appear as legitimate income. Identity theft occurs when someone obtains and uses another person's personal information without their authorization. Financial crimes are any type of offense involving the misappropriation or misuse of funds. KYC fraud detection systems use various techniques such as customer profiling, identity verification, and transaction monitoring to identify suspicious activity associated with customers or transactions.\"}),/*#__PURE__*/e(\"h2\",{children:\"The many benefits of KYC fraud detection\"}),/*#__PURE__*/e(\"p\",{children:\"There are many benefits to designing a frictionless and secure KYC process, chief among them being the prevention of fraud.\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Fewer financial losses\"}),\": By ensuring that all customers are properly vetted from the outset, companies can prevent fraud resulting from false identities or online schemes. KYC processes also prevent\\xa0\",/*#__PURE__*/e(n,{href:\"https://ec.europa.eu/info/business-economy-euro/banking-and-finance/financial-supervision-and-risk-management/anti-money-laundering-and-countering-financing-terrorism_en\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"money laundering\"})}),\". It helps organizations carry out an adequate risk assessment on customers by identifying their financial history and owned assets.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Legal compliance\"}),\": In addition to fraud prevention, a frictionless and secure KYC process can also help to ensure compliance with anti-money laundering (AML) regulations. In many jurisdictions, it is a legal requirement for companies to carry out KYC checks on their customers. By properly verifying the identities of their customers, companies can avoid hefty fines and penalties.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Efficient business growth\"}),\": Manual KYC procedures slow down how quickly banks can onboard customers \u2014 a process that\\xa0\",/*#__PURE__*/e(n,{href:\"https://www.infosys.com/industries/financial-services/insights/documents/transforming-customer-onboarding-ai.pdf\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"can take anywhere from 2-34 weeks according to Forrester research\"})}),\".\\xa0By designing a frictionless KYC process, a business can attract and onboard more customers.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Increased customer trust\"}),\": KYC protects customer accounts from unauthorized third-party access, thereby building trust between customers and organizations, and attracting more customers to a business.\"]})})]}),/*#__PURE__*/e(\"h2\",{children:\"Data sources for identity verification\"}),/*#__PURE__*/e(\"p\",{children:\"Data sources used for identity verification in the KYC process typically include official government documents, such as passports or driver's licenses, as well as public records and other third-party sources. Government documents are often used to confirm an individual\u2019s name and date of birth. Public records such as utility bills and bank statements can be used to establish residency while third-party sources provide additional information that can help verify customers' identities. Organizations may also use biometric data such as fingerprints or facial recognition to ensure that the customer is who they say they are. By collecting this data from various sources, organizations can create a comprehensive profile for each customer, which helps them detect and investigate fraudulent activity more effectively.\"}),/*#__PURE__*/e(\"h2\",{children:\"Standardized checklist for KYC fraud detection\"}),/*#__PURE__*/e(\"p\",{children:\"Organizations can use a standardized checklist to ensure they are verifying customer identity correctly and thoroughly. This checklist should include steps such as collecting proof of identity such as government-issued documents, public records and third-party sources; confirming the customer's name, address and other personal information; verifying biometric data such as fingerprints or facial recognition; assessing any potential risk associated with the customer; and monitoring transactions for suspicious activity. By following a standardized checklist for identity verification, organizations can ensure that their customers are legitimate and their transactions are secure. Furthermore, it helps organizations meet applicable laws and internal guidelines by taking a proactive approach to identifying fraud and preventing money laundering. As such, it is essential for organizations to have a robust KYC process in place to ensure that their customers are legitimate and their transactions are secure.\"}),/*#__PURE__*/e(\"h2\",{children:\"How to pick the right KYC fraud detection technology\"}),/*#__PURE__*/i(\"p\",{children:[\"Adopting the right KYC tool is the cornerstone of designing a secure, fast, and frictionless KYC experience. The features of the tool you choose will have a direct bearing on the user experience. Pick a KYC solution that offers \",/*#__PURE__*/e(\"strong\",{children:\"flexibility\"}),\" to express \",/*#__PURE__*/e(\"strong\",{children:\"customizable risk scores\"}),\" based on each business's unique risk requirements, multiple data sources for verifying identity information, as well as, continuous transaction monitoring to rerun KYC checks for users that engage in suspicious activities post onboarding.\"]}),/*#__PURE__*/i(\"p\",{children:[\"The right KYC fraud detection technology also employs \",/*#__PURE__*/e(\"strong\",{children:\"dynamic KYC checks\"}),\". Subjecting every customer to the same heavyweight KYC checks not only increases friction due to false positives but also increases costs associated with KYC processes. KYC fraud checks are rarely 100% accurate. At times, a user's risk profile can fall into a grey area. An ideal KYC fraud detection technology must employ dynamic KYC checks that have a layered approach; starting with a light KYC check and progressively adding more friction by asking for more information for users that cross a certain risk threshold. This is where having the\\xa0ability to calculate dynamic risk scores\\xa0comes in handy.\\xa0Dynamically computed risk scores with corresponding thresholds can be used for triaging applications instantly to automatically \",/*#__PURE__*/e(\"em\",{children:\"accept\"}),\", \",/*#__PURE__*/e(\"em\",{children:\"decline\"}),\", or \",/*#__PURE__*/e(\"em\",{children:\"review\"}),\" an application.\"]}),/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"AI-powered KYC fraud detection\"}),\" technology goes further ahead in allowing organizations to spot suspicious KYC patterns without the need for human intervention.\\xa0This is particularly useful in presence of huge amounts of data, where even the most eagle-eyed KYC analysts would fail to spot discrepancies.\\xa0Of course, AI isn\u2019t sophisticated enough to perform full compliance analysis, but it\u2019s certainly a step in the right direction for organizations looking to save time and resources uncovering potential risks.\"]}),/*#__PURE__*/e(\"h2\",{children:\"Compliance with regulatory requirements for KYC\"}),/*#__PURE__*/e(\"p\",{children:\"Organizations must comply with a variety of regulatory requirements when it comes to KYC fraud detection. This includes laws such as the Bank Secrecy Act (BSA), which requires organizations to maintain customer identity and transaction records; Anti-Money Laundering (AML) regulations, which call for enhanced due diligence measures when evaluating potential risks associated with customers; and Know Your Customer (KYC) guidelines, which require organizations to verify customer identity before allowing access to services or products. Organizations must also adhere to privacy laws that protect the customer's personal information from unauthorized use or disclosure. By meeting these regulatory requirements, organizations can ensure that their customers are legitimate and their transactions are secure. Furthermore, it helps organizations meet applicable laws and internal guidelines by taking proactive steps to prevent money laundering and identify fraud. As such, organizations need to develop a robust KYC process to protect their customers and meet regulatory requirements.\"}),/*#__PURE__*/e(\"h2\",{children:\"A proactive and continuous KYC strategy is the cornerstone of successful KYC fraud detection\"}),/*#__PURE__*/e(\"p\",{children:\"KYC (Know Your Customer) and KYB (Know Your Business) are processes used by organizations to verify a customer\u2019s identity and assess the risk associated with the customer to protect themselves from fraud. KYC fraud detection is an important part of this process, as it involves verifying the customer\u2019s identity and monitoring transactions for any suspicious activities. It has many benefits, such as reducing the risk of losses due to fraud and money laundering, helping organizations meet regulatory requirements, and providing customers with a secure experience. When selecting a KYC fraud detection technology, organizations should consider factors like customer profiling, identity verification, dynamic KYC checks, risk scoring, and AI-powered analytics. Additionally, organizations must comply with the applicable laws and regulations to ensure their customers are legitimate and their transactions are secure. By doing so, they can prevent fraudulent activities in the financial system while providing a safe experience for their customers.\"})]});export const richText2=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Credit decisioning software\"}),\" is leading a paradigm shift in the world of credit. Borrowers nowadays, regardless of their reasons for seeking out credit, want an effortless and rapid experience that caters to their individual needs.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"On the other hand, lenders are desperate for cutting-edge customer experiences that reduce abandonment during the loan application process while also optimizing customer satisfaction levels and profits.\"}),/*#__PURE__*/e(\"p\",{children:\"Unfortunately, legacy systems and infrastructure can make it difficult for lenders to provide a seamless digital borrowing experience. With the rise of artificial intelligence (AI) and real-time data analytics, online lending is becoming more automated than ever before!\\xa0\"}),/*#__PURE__*/i(\"p\",{children:[\"In fact, the online lending platform market was valued at $ 7.04 Billion in 2022, and it\u2019s estimated to grow annually by 26.5% until 2030 - according to \",/*#__PURE__*/e(n,{href:\"https://www.grandviewresearch.com/industry-analysis/digital-lending-platform-market\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"Grandview Research\"})}),\".\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"This means that disruption by innovation is well underway, with banks and fintechs making strategic decisions that will determine the winners of tomorrow.\"}),/*#__PURE__*/e(\"p\",{children:\"By choosing the right provider, lenders can improve customer satisfaction and boost revenue.\"}),/*#__PURE__*/e(\"p\",{children:\"But making the right choice is not so simple: that\u2019s why we\u2019ve written this guide to help you make the right decision by understanding how credit decisioning software works, what kind of use cases it can help you with, and how to choose \u201Cthe right one\u201D for your needs.\"}),/*#__PURE__*/i(\"p\",{children:[\"(We also happen to be a no-code credit decisioning platform that you can deploy quickly and easily for \",/*#__PURE__*/e(n,{href:\"https://oscilar.com/solutions/instant-credit-decisioning\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"instant credit decisioning\"})}),\", but more on that later.)\"]}),/*#__PURE__*/e(\"p\",{children:\"This blog post will cover the following topics and explore how you can make smarter, faster decisions with credit decisioning engine:\"}),/*#__PURE__*/i(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"What is credit decisioning software?\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"The benefits of using credit decisioning software\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"How credit decisioning software works: automated risk assessment and more\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Fuel efficient business growth with credit decisioning software\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Protect your business from fraud with credit decisioning software\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Find the right credit decisioning solution for your financial institution\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Conclusion: Credit decisioning software is the foundation of modern lending\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"What is credit decisioning software?\"}),/*#__PURE__*/e(\"p\",{children:\"Credit decisioning software, also known as a credit decision engine, is a powerful tool used by financial institutions to determine the creditworthiness of potential customers. Lenders rely on this technology to make better decisions faster and with greater accuracy than manual processes, while also reducing operational costs.\"}),/*#__PURE__*/e(\"h2\",{children:\"Automated workflows, smarter decisions\"}),/*#__PURE__*/e(\"img\",{alt:\"credit decisioning flow\",className:\"framer-image\",height:\"627\",src:\"https://framerusercontent.com/images/W6uHiU2OiVc0tlPDjRX5WVnO1s8.jpg\",srcSet:\"https://framerusercontent.com/images/W6uHiU2OiVc0tlPDjRX5WVnO1s8.jpg?scale-down-to=512 512w,https://framerusercontent.com/images/W6uHiU2OiVc0tlPDjRX5WVnO1s8.jpg?scale-down-to=1024 1024w,https://framerusercontent.com/images/W6uHiU2OiVc0tlPDjRX5WVnO1s8.jpg?scale-down-to=2048 2048w,https://framerusercontent.com/images/W6uHiU2OiVc0tlPDjRX5WVnO1s8.jpg 2400w\",style:{aspectRatio:\"2400 / 1254\"},width:\"1200\"}),/*#__PURE__*/e(\"p\",{children:\"Credit decisioning software uses sophisticated algorithms to analyze applicants' financial health, credit, and payment history, as well as other alternative data to accurately assess credit risk.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"It also features automated credit scoring, data verification, and fraud detection capabilities to ensure reliable results. With the help of this technology, lenders can offer more competitive payment terms, and make better loan approvals for their customers - while controlling risk and fraud.\"}),/*#__PURE__*/e(\"p\",{children:\"Additionally, It also enables lenders to optimize lending parameters to fit their credit policies as the risk profile and goals of the business evolve. Some other key features of modern credit decisioning platforms include:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Automates the collection of data that underpins loan approvals, such as that of credit bureaus and third-party sources.\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Automates the collection and analysis of alternative data such as bank and accounting information\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Offers out-of-the-box capabilities to define credit models\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Case management tools to speed up manual reviews\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Enables the use of advanced real-time data analytics and Machine Learning (ML) to discover new parameters for credit models.\"})})]}),/*#__PURE__*/e(\"p\",{children:\"By investing in the right solution for your bank or financial institution, you can realize a host of advantages that will increase approvals while reducing risk. So let\u2019s take a closer look at how credit decisioning software works and what it can provide.\"}),/*#__PURE__*/e(\"h2\",{children:\"The benefits of using credit decisioning software\"}),/*#__PURE__*/e(\"img\",{alt:\"credit decisioning software benefits\",className:\"framer-image\",height:\"627\",src:\"https://framerusercontent.com/images/ikThJgFgHPZ50bkz8M9uRWwh0bY.jpg\",srcSet:\"https://framerusercontent.com/images/ikThJgFgHPZ50bkz8M9uRWwh0bY.jpg?scale-down-to=512 512w,https://framerusercontent.com/images/ikThJgFgHPZ50bkz8M9uRWwh0bY.jpg?scale-down-to=1024 1024w,https://framerusercontent.com/images/ikThJgFgHPZ50bkz8M9uRWwh0bY.jpg?scale-down-to=2048 2048w,https://framerusercontent.com/images/ikThJgFgHPZ50bkz8M9uRWwh0bY.jpg 2400w\",style:{aspectRatio:\"2400 / 1254\"},width:\"1200\"}),/*#__PURE__*/e(\"p\",{children:\"There are numerous advantages to using credit decisioning software for modern-day lending. Here are the main benefits they offer:\"}),/*#__PURE__*/e(\"h3\",{children:\"1. Seamless borrowing experience\"}),/*#__PURE__*/e(\"p\",{children:\"By automating much of the lending process, you can offer a seamless experience for your borrowers. Instead of manually verifying applicants and their financial statements, for example, you can automate the process by connecting different providers in a decisioning flow to automatically make decisions in a matter of minutes.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"At Oscilar, we provide not just credit-bureau data, but over 100 alternative data sources as well to instantly give you a 360-degree view of your customers.\"}),/*#__PURE__*/e(\"h3\",{children:\"2. Increasing the accuracy of credit decisions\"}),/*#__PURE__*/e(\"p\",{children:\"With the use of the right software, credit scoring can become more accurate. By aggregating data from multiple sources, analyzing it, and using ML models, a platform can identify patterns that humans would not be able to detect. This allows for a more comprehensive assessment & control of credit risk and leads to more accurate decisions.\"}),/*#__PURE__*/e(\"h3\",{children:\"3. Personalized credit decisions\"}),/*#__PURE__*/e(\"p\",{children:\"In addition to being more accurate, credit decisions made with credit decisioning software can also be more personalized.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"By taking into account factors such as:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Income\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Employment history\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Spending habits\"})})]}),/*#__PURE__*/e(\"p\",{children:\"you can provide more tailored decisions that are specific to the borrower, leading to a better customer experience and increasing satisfaction with the credit product.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"4. Faster lending decisions\"}),/*#__PURE__*/e(\"p\",{children:\"By automating the gathering and analysis of data, you can make a credit decision in a matter of seconds or minutes, rather than days or weeks: this is instant decisioning.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Instead of working with third-party data sources and spending engineering resources to bring them all under one hood, decisioning platforms like Oscilar combine everything into one view, allowing analysts themselves to create & deploy rules themselves.\"}),/*#__PURE__*/e(\"p\",{children:\"The value is of course that you can capture value that otherwise would have been lost due to customer churn.\"}),/*#__PURE__*/e(\"h3\",{children:\"5. Reduced cost of loan originations\"}),/*#__PURE__*/i(\"p\",{children:[\"AI-powered credit scoring can reduce the cost of loan origination by up to \",/*#__PURE__*/e(n,{href:\"https://www.mckinsey.com/business-functions/risk/how-we-help-clients/impact-stories/digitizing-credit-risk-trims-costs-and-delights-customers\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"40%\"})}),\" and reduce the cost of decisions on low-complexity cases.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"Also, lenders can scale their operations to new geographies and higher volumes with a marginal increase in human workforce capacity.\"}),/*#__PURE__*/e(\"h2\",{children:\"How credit decisioning software works: automated risk assessment and more\"}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"337\",src:\"https://framerusercontent.com/images/VUF7qXBSmFvPyZvMk7IzkoSRIM.gif\",srcSet:\"https://framerusercontent.com/images/VUF7qXBSmFvPyZvMk7IzkoSRIM.gif?scale-down-to=512 512w,https://framerusercontent.com/images/VUF7qXBSmFvPyZvMk7IzkoSRIM.gif?scale-down-to=1024 1024w,https://framerusercontent.com/images/VUF7qXBSmFvPyZvMk7IzkoSRIM.gif 1360w\",style:{aspectRatio:\"1360 / 674\"},width:\"680\"}),/*#__PURE__*/e(\"p\",{children:\"Credit decisioning software automates the risk assessment process by analyzing applicants' financial data, payment and credit history to determine their creditworthiness. The tool ingests and processes credit risk data from credit bureaus and external data sources, as well as, income and cash flow data and runs credit models on a combination of these signals.\"}),/*#__PURE__*/e(\"p\",{children:\"Advanced credit decisioning software uses predictive analytics to identify potential risks, such as defaulting on repayment or committing fraud.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Additionally, you can detect discrepancies in submitted applications and carry out automated credit scoring to make sure the results are reliable and accurate.\"}),/*#__PURE__*/i(\"p\",{children:[\"Credit decisioning software also monitors creditworthiness throughout the customer lifecycle, allowing lenders to update their risk assessment as needed. This ensures that they can make informed decisions based on up-to-date information about borrowers and minimize their exposure to potential losses, streamlining the \",/*#__PURE__*/e(n,{href:\"https://oscilar.com/solutions/instant-credit-decisioning\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"credit underwriting process\"})}),\".\"]}),/*#__PURE__*/e(\"h2\",{children:\"Fuel efficient growth with a credit decisioning engine\"}),/*#__PURE__*/e(\"p\",{children:\"One of the biggest advantages of a credit decisioning engine is its ability to optimize: save time, resources, and costs - improving lenders' bottom line.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"By automating the risk assessment process, this technology eliminates manual labor associated with reviewing applications, reducing operational costs and boosting efficiency.\"}),/*#__PURE__*/e(\"p\",{children:\"Additionally, decisioning software helps to protect lenders from potential losses due to fraud or non-repayment of debt.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Finally, using credit decisioning software that can analyze alternative data sources can boost revenue by using additional risk and enabling inclusive lending practices.\"}),/*#__PURE__*/e(\"p\",{children:\"Overall, decisioning processes and software can significantly improve the lending process for both lenders and consumers by providing faster decisions with greater accuracy and lower costs.\"}),/*#__PURE__*/e(\"h2\",{children:\"Protect your business from fraud with credit decisioning software\"}),/*#__PURE__*/e(\"p\",{children:\"Credit decisioning software helps financial institutions protect themselves from potential losses due to fraud or non-repayment of debt. A good solution can detect potential signs of fraudulent activity in applications such as identity theft, false information, duplicate profiles, and other suspicious behaviors.\"}),/*#__PURE__*/e(\"p\",{children:\"You can also conduct automated credit checks to verify the accuracy of information provided by customers before they are approved for a loan or line of credit.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"By using an integrated fraud and credit risk management platform to both underwrite and detect and prevent fraudulent activity, lenders can minimize their exposure and protect their businesses from potential losses.\"}),/*#__PURE__*/e(\"h2\",{children:\"Find the right credit decisioning software for your financial institution\"}),/*#__PURE__*/i(\"p\",{children:[\"When lenders are looking for credit decisioning software, certain features and capabilities are essential. Here are a few things to look for in a credit \",/*#__PURE__*/e(n,{href:\"https://oscilar.com/blog/decisioning-engine\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"decisioning engine\"})}),\".\"]}),/*#__PURE__*/e(\"h3\",{children:\"Real-time decisions\"}),/*#__PURE__*/i(\"p\",{children:[\"The ability to make a \",/*#__PURE__*/e(\"strong\",{children:\"real-time\"}),\" credit decision is critical. By aggregating the right data sources and automating the application of the right credit models, lenders can now make credit decisions in real-time.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Custom decisioning process\"}),/*#__PURE__*/i(\"p\",{children:[\"The ability to \",/*#__PURE__*/e(\"strong\",{children:\"customize\"}),\" the decisioning process. Good engines should allow lenders to customize the workflows to fit their specific needs.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Ease of use\"}),/*#__PURE__*/i(\"p\",{children:[\"The platform should be \",/*#__PURE__*/e(\"strong\",{children:\"easy to use\"}),\" and navigate so that lenders can get up and running quickly, as well as, reduce dependence on engineering resources.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Data aggregation & Machine Learning support\"}),/*#__PURE__*/i(\"p\",{children:[\"The platform should allow \",/*#__PURE__*/e(\"strong\",{children:\"aggregating data\"}),\" from multiple sources, analyzing it, and using ML models that can identify patterns that humans would not be able to detect.\"]}),/*#__PURE__*/e(\"h3\",{children:\"No-code, API-first\"}),/*#__PURE__*/i(\"p\",{children:[\"The platform should be able to integrate with a lender\u2019s existing systems and infrastructure so that they can continue to use their existing tools and processes. An \",/*#__PURE__*/e(\"strong\",{children:\"API-first and no-code platform\"}),\" is best positioned to allow that flexibility of integration.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Credit model variety\"}),/*#__PURE__*/i(\"p\",{children:[\"The platform should offer a \",/*#__PURE__*/e(\"strong\",{children:\"variety of credit models\"}),\" so that lenders can choose the one that best fits their needs.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Scalability\"}),/*#__PURE__*/i(\"p\",{children:[\"The platform should be able to handle a \",/*#__PURE__*/e(\"strong\",{children:\"high volume of transactions\"}),\" so that lenders can scale their business as needed.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Reliability\"}),/*#__PURE__*/i(\"p\",{children:[\"A 24x7 borrower experience requires credit decisioning software that offers high reliability, uptime, and \",/*#__PURE__*/e(\"strong\",{children:\"24x7 customer support\"}),\".\"]}),/*#__PURE__*/e(\"h3\",{children:\"Affordability\"}),/*#__PURE__*/i(\"p\",{children:[\"The platform should allow lenders to start small and \",/*#__PURE__*/e(\"strong\",{children:\"scale pricing\"}),\" as the lender experiences value from the credit decisioning engine.\"]}),/*#__PURE__*/e(\"h2\",{children:\"Credit decisioning software is the foundation of modern lending\"}),/*#__PURE__*/e(\"p\",{children:\"Credit decisioning software is an invaluable tool for financial institutions that want to increase approvals and make faster, more informed credit decisions while also minimizing their risk exposure. Features such as automated credit scoring, data verification, fraud detection, and customizable workflows to fit the lender\u2019s needs are staples of a good provider.\"}),/*#__PURE__*/e(\"p\",{children:\"Finding the right provider for your bank or financial institution requires careful consideration of several factors. By looking for features such as:\\xa0\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Real-time instant decision-making ability\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Customization capabilities\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Easy UI\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"The ability to aggregate data and apply ML models\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Integration flexibility, out-of-the-box credit models\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",style:{\"--framer-font-size\":\"11px\",\"--framer-text-color\":\"rgb(0, 0, 0)\",\"--framer-text-decoration\":\"none\"},children:/*#__PURE__*/e(\"p\",{children:\"Scalability and 24x7 customer support\\xa0\"})})]}),/*#__PURE__*/e(\"p\",{children:\"You can ensure that you are selecting the best credit decisioning software for your organization.\"}),/*#__PURE__*/e(\"p\",{children:\"If you are curious about how such an engine looks and feels in action, consider scheduling a demo with us: we are more than happy to show you what\u2019s under the hood.\"})]});export const richText3=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"In today's ever-evolving business landscape, decisioning engines are becoming increasingly important for organizations to stay competitive. By leveraging decisioning engines, businesses can make faster and better decisions based on their data, enabling them to take advantage of opportunities while avoiding costly mistakes. With the power of decisioning engine technology, businesses can quickly analyze large datasets, process complex algorithms, and make informed decisions in real time.\"}),/*#__PURE__*/e(\"p\",{children:\"In this blog post, we will cover the following topics\"}),/*#__PURE__*/i(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"What is a decisioning engine?\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The benefits of decisioning engines for businesses\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The drawbacks of conventional decisioning engines\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The 5 pillars of modern decisioning engines\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"How decisioning engines are transforming industries\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"What is a decisioning engine?\"}),/*#__PURE__*/e(\"p\",{children:\"A decisioning engine is a system that can make decisions based on data inputs. It helps organizations to efficiently and quickly analyze large datasets, process complex algorithms, and make informed decisions in real-time. This technology is useful for many applications such as financial services, healthcare, fraud detection, customer segmentation, marketing automation, and more.\"}),/*#__PURE__*/e(\"p\",{children:\"Decisioning engines give organizations the tools they need to effectively analyze data from multiple sources and draw insights from it. By utilizing decisional algorithms and artificial intelligence (AI) technologies, decisioning engines are able to rapidly make decisions based on the data they receive. This decision-making process provides organizations with insights that can be used to make informed decisions, leading to increased efficiency, better decision making and improved customer experience.\"}),/*#__PURE__*/e(\"p\",{children:\"At the core of decisioning engine technology is a decision-making algorithm. This algorithm is used to analyze data from numerous sources, which can include customer data, historical data or real-time market trends. Through a process of analysis and inference, decisioning engines use this data to make decisions based on predefined parameters.\"}),/*#__PURE__*/e(\"h2\",{children:\"Benefits of decisioning engines for businesses\"}),/*#__PURE__*/e(\"p\",{children:\"Decisioning engine technology can provide numerous advantages to businesses that leverage it. One major benefit is the ability to make decisions quickly and accurately, eliminating the need for manual decision-making processes which can be time-consuming and often inaccurate. Furthermore, decisioning engines can be quickly customized to provide decision-making capabilities for specific tasks or scenarios.\"}),/*#__PURE__*/e(\"p\",{children:\"This customization allows decisioning engines to better reflect the changing needs of businesses as well as their unique decision-making requirements. Additionally, decisioning engines can analyze massive amounts of data in a short period, allowing organizations to quickly uncover valuable insights from their data.\"}),/*#__PURE__*/e(\"h2\",{children:\"Drawbacks of conventional decisioning engines\"}),/*#__PURE__*/e(\"p\",{children:\"Conventional decisioning engines were designed around lower-level abstractions leading to several drawbacks involving engineering overhead, performance, and slow iteration time.\"}),/*#__PURE__*/e(\"h3\",{children:\"High engineering overhead\"}),/*#__PURE__*/e(\"p\",{children:\"Building a lower-level abstraction such as a simple rules engine often means that a decisioning engine's end users\u2014business analysts and data scientists\u2014require expensive engineering resources to design and deploy end-to-end decisioning workflows. This includes integrating appropriate data sources and writing new rules, A/B testing new decisioning models to pushing them live, and monitoring their performance. This reliance on engineering is not ideal for business teams and is an expensive proposition for the company.\"}),/*#__PURE__*/e(\"h3\",{children:\"Performance\"}),/*#__PURE__*/e(\"p\",{children:\"Conventional decisioning engines were designed solely for expressing decisioning workflows, but not for processing large amounts of data that feed into each decisioning workflow. This leads to processing data in a batch fashion, impacting response time and efficiency negatively.\"}),/*#__PURE__*/e(\"h3\",{children:\"Slow iteration speed\"}),/*#__PURE__*/e(\"p\",{children:\"Conventional decisioning engines lack out-of-the-box integrations with the right data sources, from CRM tools to marketing tools and internal databases. The absence of automated out-of-the-box integrations with the right data sources often means significant time spent on data plumbing to discover new decisioning vectors. Coupled with the lack of no-code automation, this means a delay of weeks to months to respond to rapidly evolving business needs. This slow response time results in high opportunity costs for the business.\"}),/*#__PURE__*/e(\"h3\",{children:\"Lack of advanced testing capabilities\"}),/*#__PURE__*/e(\"p\",{children:\"Conventional decisioning engines lack advanced testing capabilities. Deploying new decisioning models rapidly and accurately requires the ability to test those models thoroughly. A variety of testing methodologies need to be applied, from unit testing to backtesting and A/B testing. The absence of such modern testing capabilities significantly hampers the user's ability to deploy new decisioning models rapidly and accurately.\"}),/*#__PURE__*/e(\"h2\",{children:\"The 5 pillars of modern decisioning engines\"}),/*#__PURE__*/e(\"h3\",{children:\"In-built data integration capabilities\"}),/*#__PURE__*/e(\"p\",{children:\"Data is the foundation of decisioning. The core need of modern decisioning is a platform that integrates data coming from a variety of sources, offers an easy way to process and aggregate data, and does that continuously as new data is generated.\"}),/*#__PURE__*/e(\"h3\",{children:\"Application of rules and Machine Learning\"}),/*#__PURE__*/e(\"p\",{children:\"The journey of modern decisioning often starts with rules centered around heuristics and advances to an extensive application of Machine Learning. Tuning rules might work well for incorporating certain high-confidence signals, but might fall short of discerning new multi-dimensional patterns. As business needs evolve, the rules and corresponding thresholds must adapt quickly as well. This is where Machine Learning (ML) for decisioning comes in. ML models are effective at discerning fraud patterns using a large number of complex and related signals. Therefore, a combination of rules and ML is an effective strategy for increasing the accuracy of decisioning.\"}),/*#__PURE__*/e(\"h3\",{children:\"Integrated real-time data analytics and decisioning\"}),/*#__PURE__*/e(\"p\",{children:\"There is a clear gap in the decisioning engines market; conventional decisioning engines do not support the ability to analyze and visualize data to find new decisioning vectors and immediately decision on them. However, to increase the speed and accuracy of decisioning, you need both data analytics and decisioning capabilities. The data that was used to find a new decisioning vector should also be used to then decision on it.\"}),/*#__PURE__*/e(\"p\",{children:\"The best fraud detection software integrates real-time data analytics and visualization with decisioning workflows, allowing you to:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"search through activity logs\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"slice and dice data + visualize patterns\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"use the decisioning signals discovered from the above processes to train ML models and run rules\"})})]}),/*#__PURE__*/e(\"h3\",{children:\"No-code automation\"}),/*#__PURE__*/e(\"p\",{children:\"No-code automation is the foundation of modern decisioning engines and frees up business personnel like analysts and data scientists from writing code and relying on engineering for core day-to-day decisioning needs.\"}),/*#__PURE__*/e(\"h3\",{children:\"Advanced testing\"}),/*#__PURE__*/e(\"p\",{children:\"In the same way that you never deploy software applications without testing them, you rarely want to deploy a new change to your decisioning ML models or rules without knowing how they will perform in practice. This ability to accurately unit test, backtest, and A/B test new decisions is surprisingly difficult to build and hence capability rarely available in conventional fraud detection software.\"}),/*#__PURE__*/e(\"p\",{children:\"The best decisioning engines integrate historical data with real-time data, allow you to run unit tests, do backtesting by running rules and ML models on past data, as well as, allow you to run A/B test simulations to validate the change and iterate on it.\"}),/*#__PURE__*/e(\"h2\",{children:\"How decisioning engines are transforming industries\"}),/*#__PURE__*/e(\"p\",{children:\"Decisioning engines have a variety of applications in different industries across financial services, insurance, healthcare, retail, and more.\"}),/*#__PURE__*/e(\"h3\",{children:\"Decisioning engines for fraud detection\"}),/*#__PURE__*/e(\"p\",{children:\"Decisioning engines also have a variety of applications in fraud detection. By analyzing data collected from user activity, decisioning engines can quickly identify suspicious behavior and alert organizations to potential fraudulent activity. This helps organizations protect themselves against financial losses caused by fraudsters and reduce the time spent on manual investigation.\"}),/*#__PURE__*/e(\"h3\",{children:\"Decisioning engines for credit underwriting\"}),/*#__PURE__*/e(\"p\",{children:\"Decisioning engine technology is also playing a significant role in credit underwriting. By leveraging decisioning engines, lenders can quickly and accurately assess the risk of lending to a prospective borrower. Decisioning engines provide lenders with deep insights into a borrower's credit history, allowing them to make informed decisions about issuing credit and setting loan terms. This technology is not only improving decision-making but also helping lenders make better use of their resources, ultimately leading to higher profits.\"}),/*#__PURE__*/e(\"h3\",{children:\"Decisioning engines for insurance\"}),/*#__PURE__*/e(\"p\",{children:\"Decisioning engines are also revolutionizing the insurance industry. By utilizing decisioning engines, insurers can quickly make decisions about claims processing and customer service. This technology also enables insurers to analyze large datasets to draw insights from customer behavior and preferences to create more tailored offerings. In addition, decisioning engine technology can be used for risk management, allowing insurers to identify and manage risks more effectively.\"}),/*#__PURE__*/e(\"h3\",{children:\"Decisioning engines for retail\"}),/*#__PURE__*/e(\"p\",{children:\"In retail, decisioning engines can be used to quickly analyze customer data and segment customers into different categories. This allows businesses to better understand their customers\u2019 needs and tailor relevant offers accordingly. By leveraging decisioning engine technology, retailers can create personalized shopping experiences for their customers, leading to higher conversion rates and increased customer satisfaction. Decisioning engines can also be used to automate marketing campaigns, allowing businesses to quickly and effectively reach the right customers with the right message.\"}),/*#__PURE__*/e(\"h3\",{children:\"Decisioning engines for healthcare\"}),/*#__PURE__*/e(\"p\",{children:\"In healthcare, decisioning engines can be used to help make informed decisions about patient care and improve their operations. By leveraging decisional algorithms and artificial intelligence (AI) technologies, decisioning engines can rapidly analyze data from multiple sources and draw insights from it. This decision-making process provides organizations with insights that can be used for better decision-making, leading to improved patient outcomes and cost savings.\"}),/*#__PURE__*/e(\"p\",{children:\"Decisioning engine technology can be used for many healthcare applications such as predictive analytics, decision support systems, clinical decision support systems (CDSS), disease management programs and medical decision-making.\"}),/*#__PURE__*/e(\"h3\",{children:\"Decisioning engines for marketing\"}),/*#__PURE__*/e(\"p\",{children:\"In marketing, decisioning engines are becoming an invaluable tool for businesses to automate their campaigns and deliver personalized messages to their customers. Decisioning engines can help marketers segment their customer base according to preferences and interests to better target them with relevant offers and promotions. Additionally, decisioning engines can be used to optimize the timing of communications, allowing businesses to send out messages at the most effective times for their customers. With decisioning engines, businesses can also use predictive analytics to anticipate customer needs and behaviors, allowing them to tailor their campaigns for maximum impact.\"}),/*#__PURE__*/e(\"h2\",{children:\"Decisioning engines have become a core part of digital businesses\"}),/*#__PURE__*/e(\"p\",{children:\"The decisioning engine technology has revolutionized decision-making for organizations across a variety of industries. By leveraging decisioning engine technology, businesses can analyze large datasets and make informed decisions in real-time. Decisioning engines can be used for a variety of applications such as fraud detection, customer segmentation, marketing automation, and more. While decisioning engines enable businesses to make better decisions faster, there are still certain drawbacks in conventional decisioning engines. The limitations of conventional decisioning engines include: limited scalability; lack of accuracy due to manual processes; and difficulty in keeping up with changing customer needs and preferences. To overcome these issues, organizations need to adopt the five pillars of modern decisioning engines: advanced real-time integration and analytics, no-code automation, advanced testing and artificial intelligence (AI). By leveraging the power of these five pillars, decisioning engines can provide organizations with greater insight into their data and help them make more informed decisions quickly and accurately.\"})]});export const richText4=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/i(\"p\",{children:[\"According to the\\xa0\",/*#__PURE__*/e(n,{href:\"https://www.unodc.org/unodc/en/money-laundering/overview.html\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"United Nations\"})}),\", $2 trillion is laundered every year. Financial institutions have been fined a staggering \",/*#__PURE__*/e(n,{href:\"https://www.nasdaq.com/articles/5-lessons-from-aml-bank-fines-of-2021-2021-10-11\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"$2 billion\"})}),\" in 2021, according to Nasdaq's 'AML Fines H1 2021 Report'. The numbers are staggering and a big reason why real-time transaction monitoring has become the cornerstone of compliance programs in the finance industry. \"]}),/*#__PURE__*/e(\"p\",{children:\"Real-time transaction monitoring is the process of identifying suspicious events such as payments or business agreements by using rules and data. These transactions are then flagged for manual examination. Real-time transaction monitoring is fundamentally critical for organizations that move money on behalf of clients or companies and is a critical part of any organization's anti-money laundering (AML) compliance program.\"}),/*#__PURE__*/e(\"p\",{children:\"By flagging potentially suspicious transactions, real-time transaction monitoring helps organizations identify and report suspicious activities \u2013 such as terrorist financing, money laundering, and other illicit financial activities \u2013 to the appropriate authorities. As such, real-time transaction monitoring plays an important role in helping to prevent financial crime worldwide.\"}),/*#__PURE__*/e(\"p\",{children:\"In this comprehensive guide to real-time transaction monitoring, we cover the following topics:\"}),/*#__PURE__*/i(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"What is real-time transaction monitoring, what are the types of transaction monitoring, and what it detects\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The challenges in real-time transaction monitoring today\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The pillars of real-time transaction monitoring\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"How to pick the right real-time transaction monitoring solution\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Key takeaways\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"What is real-time transaction monitoring?\"}),/*#__PURE__*/e(\"p\",{children:\"Real-time transaction monitoring helps organizations recognize and understand patterns of potentially criminal behavior, stop suspicious payments, or analyze them post-payment. Different types of real-time transaction monitoring techniques are used to improve the accuracy and speed of the enhanced due diligence (EDD) process, detect and prevent fraud, and analyze transactional data to detect money laundering.\"}),/*#__PURE__*/e(\"h3\",{children:\"Types of transaction monitoring\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Real-time transaction monitoring\"}),\" not only allows you to detect crime as it happens but also blocks any suspicious payments in real-time. Consequently, this type of transaction monitoring is extremely valuable in detecting and preventing fraud.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Post-event transaction monitoring\"}),\" is used in less critical circumstances, where the payments do not create an immediate red flag. To reveal hidden patterns in completed payments, they are compared to money laundering typologies in post-event transaction monitoring.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Continuous\\xa0transaction monitoring\"}),\" is used to check historical customer data to better understand patterns and irregularities in customer behavior. Oscilar allows you to generate data aggregations for weekly, monthly or continuous transactional behavior samples.\"]})})]}),/*#__PURE__*/e(\"p\",{children:\"Transaction monitoring systems are usually built by extracting transaction information from an organization's internal databases and transaction records. This transaction data is then cleansed, normalized, and aggregated before being fed into the transaction monitoring system. The system uses pre-configured rules and models to identify potentially suspicious transaction patterns. A transaction when flagged as potentially suspicious is then forwarded to a financial crimes analyst for further review.\"}),/*#__PURE__*/e(\"h3\",{children:\"What can real-time transaction monitoring detect?\"}),/*#__PURE__*/e(\"p\",{children:\"A thorough transaction monitoring program can detect:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Money laundering\"}),\" is the process of concealing the source of illegally obtained money. It is typically done in three stages: placement, layering, and integration. In the placement stage, the money is deposited into a business. In the layering stage, accounting techniques are used to cover up the origins of the money. In the integration stage, the money is used for other payments. Money laundering can have serious implications for businesses, as it can lead to financial penalties and other regulatory compliance issues.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Terrorist financing\"}),\" is the act of providing financial support to individuals or groups involved in terrorism. Most regulated businesses have a transaction monitoring program in place that includes a list of organizations that they monitor on an ongoing basis for terrorist activity. The Financial Action Task Force (FATF) Blacklist is a list of countries that are designated as non-cooperative in the global fight against terrorist financing. Businesses are required to take extra due diligence measures when dealing with customers from these countries. In addition, the US Patriot Act requires businesses to have procedures in place to prevent the financing of terrorism. These procedures typically include enhanced customer due diligence and increased monitoring of transactions.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Fraud\"}),\" occurs when one or more parties deliberately deceive another party. When it comes to finances, fraud usually involves things like identity theft, false insurance claims, credit card defaults, and more. Continuous transaction monitoring that analyzes historical user activity in the context of the current transaction is most effective in stopping fraudulent activity from taking place.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Bribery and corruption:\"}),\" Transaction monitoring is an effective way to detect potential bribery situations, as it can flag up specific indicators such as abnormal cash payments and expense payments made in round sums. By implementing transaction monitoring, businesses can comply with anti-bribery regulations, such as the Bribery Act 2010.\"]})})]}),/*#__PURE__*/e(\"h2\",{children:\"The challenges in real-time transaction monitoring today\"}),/*#__PURE__*/e(\"p\",{children:\"Financial criminals always have the advantage: they use cutting-edge technology, have few restrictions, and plenty of resources. Unfortunately, this means that compliance teams are constantly playing catch-up. They often lack the manpower to investigate and prevent money laundering promptly. And that is not all.\"}),/*#__PURE__*/e(\"p\",{children:\"When it comes to real-time transaction monitoring, organizations face even greater challenges, in part due to:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Outdated legacy solutions\"}),\" that lack continuous transaction monitoring that integrates historical user activity data and the current transaction data to flag suspicious activity, leading to more false positives or more manual reviews.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"False positive alerts:\"}),\" Poor-quality data, together with inaccurate transaction monitoring rules, can produce a large number of false positive alerts. Organizations that find themselves in this situation have two options: hire large teams to keep up with the growing workload, or choose transaction monitoring tools to minimize operational risk and keep compliance costs in check. The latter option is often the more cost-effective choice, as it can automate many of the tasks associated with real-time transaction monitoring and alert response. In addition, it can help to improve the quality of data by providing tools for data cleansing and enrichment. As a result, false positive rates can be reduced, saving time and money.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Operational costs:\"}),\" As businesses increasingly rely on compliance with regulations to avoid penalties and maintain customers' trust, the costs of compliance have come into sharp focus. A recent study found that the average cost of compliance for a small business is $12,000 per year, while the cost for a large enterprise can be as high as $16 million. Not surprisingly, compliance costs are one of the top concerns for companies. When faced with a growing number of false positives, it's essential to have someone on hand to resolve the alerts and clear the alert backlog. However, increasing headcount to deal with compliance issues can quickly drive up operational costs, triggering a vicious circle that is difficult to escape.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Regulatory consequences:\"}),\" The regulatory environment is constantly evolving, and organizations must be prepared to adapt their compliance programs accordingly. Regulatory consequences can be severe, ranging from financial penalties to reputational damage. To avoid these consequences, it is essential to have a well-run compliance program in place. However, simply complying with the regulations is not enough. Organizations must also be proactive in fighting crime. This means having systems and controls in place to identify and report suspicious activity. By taking these measures, organizations can reduce the risk of regulatory consequences.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Customer friction:\"}),\" Customer friction is detrimental to business growth. The absence of a smooth, frictionless experience for your customers runs the risk of losing them to the competition. Oftentimes, real-time transaction monitoring tools lead to more false positives, thereby affecting customer friction negatively.\"]})})]}),/*#__PURE__*/e(\"p\",{children:\"Balancing the challenges of maintaining compliance and fighting financial crime, while providing the best experience for your customers is a tough balance that organizations strive to strike. To stop crime from happening and catch criminals when it does happen, compliance teams must have access to the latest real-time transaction monitoring tools and technology.\"}),/*#__PURE__*/e(\"h2\",{children:\"The pillars of real-time transaction monitoring\"}),/*#__PURE__*/e(\"p\",{children:\"A real-time transaction monitoring system is a vital piece of security infrastructure for any organization that deals with money. By using rules and data to flag suspicious transactions for manual review, a transaction monitoring system can help prevent terrorist financing, money laundering, and other malicious financial crimes.\"}),/*#__PURE__*/e(\"p\",{children:\"There are two main components of real-time transaction monitoring: rule-based detection and data-driven detection.\"}),/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Rule-based detection\"}),\" uses pre-defined rules to identify potentially suspicious transactions. These rules can be based on factors such as the amount of money involved, the destination country, or the type of business involved.\"]}),/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Data-driven detection\"}),\" uses historical transaction data to identify patterns or anomalies that may indicate criminal activity. This data can be used to create models that identify specific behaviors associated with criminal activity. For example, a model might look for patterns in payments made to certain countries or payments made by certain types of businesses.\"]}),/*#__PURE__*/e(\"p\",{children:\"Once a transaction has been flagged as potentially suspicious, it will be subjected to further manual review. This review may involve contacting the customer or business involved in the transaction, checking for red flags such as links to known criminals or terrorist organizations, or reviewing the transaction history of the involved parties.\"}),/*#__PURE__*/e(\"h2\",{children:\"How to pick the right real-time transaction monitoring solution\"}),/*#__PURE__*/e(\"p\",{children:\"Given the complexity of transaction monitoring, the right real-time transaction monitoring solution is the cornerstone of a company's ability to fight financial crime.\"}),/*#__PURE__*/e(\"p\",{children:\"Here are the most important capabilities to look for in a transaction monitoring solution:\"}),/*#__PURE__*/i(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Ability to handle high transaction volume and complexity:\"}),\" If you process a large number of transactions each day, you'll need a transaction monitoring system that can handle that volume of data. Similarly, if your transactions are complex (e.g., involving multiple currencies or jurisdictions), you'll need a system that can handle that complexity.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Apply firewall rules:\"}),\" By blocking high-risk countries, firewall rules act as a safeguard against fraudulent transactions and help companies to comply with sanctions. Nearly all business-grade firewalls can block cases of fraud originating from a particular domain, IP address, or geolocation. This process can be done manually as you identify suspicious activity or proactively. For example, add countries where you don't sell your products to the block list ahead of time.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Leverage Machine Learning:\"}),\" Machine learning has proven to be one of the most effective tools in combating financial fraud. These platforms are built to scale your business and constantly monitor the threat landscape to prohibit new and evolving attacks. While manual fraud investigation is certainly beneficial, AI-powered technology works 24x7, with minimal or no human involvement.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Prioritize frictionless experiences:\"}),\" It's possible to minimize false declines while monitoring transactions. Adopt real-time transaction monitoring tools that offer challenges that enable a frictionless customer experience. Accurately applied challenges prioritize the customer experience by reserving an extra layer of authentication for only the very small number of transactions that truly pose a high risk.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Reporting and analytics:\"}),\" A real-time transaction monitoring system is only as good as the data it provides. Make sure to choose a system that offers reporting and analytics features that will help you draw trends from your historical and real-time transaction data.\"]})})]}),/*#__PURE__*/e(\"h2\",{children:\"Real-time transaction monitoring: Key takeaways\"}),/*#__PURE__*/e(\"p\",{children:\"Real-time transaction monitoring is a critical tool for organizations that move money on behalf of customers or businesses. It helps prevent terrorist financing, money laundering, and other malicious financial crimes. Real-time transaction monitoring can also be used to detect and investigate suspicious activity, and to comply with anti-money laundering regulations. There are several challenges that transaction monitoring systems face today, including the increasing complexity of transactions, the need for real-time monitoring, and the challenge of false positives. \"}),/*#__PURE__*/e(\"p\",{children:\"A new approach to real-time transaction monitoring is needed that takes into account the changing landscape of financial transaction trends. This new approach should be able to handle the complexity of today's transactions, provide real-time monitoring, and reduce false positives. When choosing a real-time transaction monitoring system for your business, there are numerous factors to consider, including transaction volume and complexity, integration with other systems, leveraging firewall rules, applying machine learning and reporting, and historical + real-time analytics capabilities. \"}),/*#__PURE__*/e(\"p\",{children:\"By using the right real-time transaction monitoring solution, organizations can protect themselves from financial crimes, and penalties and improve security and safety for their customers or clients. If you are looking for a partner to help you reduce false positives, build a strong and efficient compliance program, and combat financial crime, book a demo to see Oscilar's Real-Time Transaction Monitoring solution.\"})]});export const richText5=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"The rapid rise in online business transactions has made Know Your Customer (KYC) a very vital aspect of accessing important services. From opening a bank account to simply placing an order online, a KYC form is a key part of the onboarding process for businesses to identify clients and expose fraud. There are many benefits to designing a frictionless and secure KYC process, chief among them being the prevention of fraud. By ensuring that all customers are properly vetted from the outset, companies can not only prevent criminal activities like bribery, fraud, money laundering, and identity theft but also attract more customers and increase revenue.\"}),/*#__PURE__*/i(\"p\",{children:[\"At the same time, the costs of KYC verification are on the rise and companies are looking for ways to streamline their KYC processes and cut costs associated with KYC processes. This is especially true in industries where compliance is of the utmost importance, such as banking and finance. According to a \",/*#__PURE__*/e(n,{href:\"https://www.miteksystems.com/files/docs/hyperion-whitepaper-final-for-release-june2017pdf.pdf\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"study\"})}),\" conducted by Consult Hyperion, banks spend an average of $60 million each year on KYC and related procedures.\"]}),/*#__PURE__*/e(\"p\",{children:\"To strike the right balance between growth and security, organizations should use sophisticated identity technology to significantly cut manual processing costs, be less prone to error, and reduce the risk of sanctions, KYC friction, and operational expenses.\"}),/*#__PURE__*/e(\"p\",{children:\"This blog post explores the key elements of designing an efficient, frictionless, and secure KYC process.\"}),/*#__PURE__*/i(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"What is KYC and KYB?\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The true costs associated with KYC fraud and how to cut those costs\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The benefits of a frictionless and secure KYC process\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The latest trends in KYC verification\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The 5 pillars of designing a secure and frictionless KYC experience\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"What is KYC and KYB?\"}),/*#__PURE__*/e(\"p\",{children:\"KYC verification is the process of verifying the identity of a customer. This usually includes checks like verifying government-issued ID documents and making sure that the customer\u2019s name, date of birth, and address match up.\"}),/*#__PURE__*/e(\"p\",{children:\"In some cases, additional information may be required to verify a customer\u2019s identity. This could include things like utility bills or bank statements. The level of due diligence will vary depending on the industry and the risk profile of the customer.\"}),/*#__PURE__*/e(\"p\",{children:\"The goal of KYC verification is to ensure that a customer is who they say they are, and that they are not engaged in any illegal activities. At the same time, KYC vetting cannot come at the cost of customer churn due to friction during the onboarding process.\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"em\",{children:\"KYC is a fine balance between growth and fraud; an ideal KYC process introduces the minimum amount of friction required to accurately flag fraudulent customers.\"})}),/*#__PURE__*/i(\"p\",{children:[\"Following are the \",/*#__PURE__*/e(n,{href:\"https://www.fincen.gov/news/news-releases/fincen-reminds-financial-institutions-cdd-rule-becomes-effective-today\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"three pillars of KYC\"})}),\":\"]}),/*#__PURE__*/i(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Customer Identification Program (CIP): \"}),\"Verify that the customer is who they say they are\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Customer Due Diligence (CDD): \"}),\"Assess the customer\u2019s level of risk, including reviewing the beneficial owners of a company\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Continuous monitoring: \"}),\"Monitor client transaction patterns and report suspicious activity on an ongoing basis\"]})})]}),/*#__PURE__*/e(\"h3\",{children:\"KYB: KYC for Business\"}),/*#__PURE__*/e(\"p\",{children:\"Know Your Business (KYB) is an extension of KYC for business suppliers or partners. Just as companies need to vet individuals before allowing them to open a bank account or invest through their platform, companies also need to vet other businesses they work with.\"}),/*#__PURE__*/e(\"p\",{children:\"KYB processes involve:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Identifying high-risk businesses.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Determining the nature of the business including what it sells, what service it provides, and who it partners with.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Collecting documents like articles of incorporation, business licenses, partnership agreements, and financial statements.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Identifying and verifying ultimate beneficial owners (UBO) before establishing a business relationship. A beneficial owner may not be the owner or company leader but is a person who ultimately benefits from the business transactions.\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"The true costs associated with KYC are significantly high\"}),/*#__PURE__*/e(\"p\",{children:\"There are many hidden costs associated with KYC fraud and those costs are often underestimated. It isn't just about the time spent on manual labor, financial losses due to fraud, and the cost of compliance solutions; heavy-handed KYC checks also come with high business opportunity costs as customers turn to competitive products that have a frictionless onboarding experience.\"}),/*#__PURE__*/i(\"p\",{children:[\"Financial institutions have reported spending an average of $60 million annually on KYC-related costs, according to a \",/*#__PURE__*/e(n,{href:\"https://www.fstech.co.uk/fst/mitek/Hyperion-Whitepaper-Final-for-Release-June2017.pdf\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"2017 study\"})}),\" by Consult Hyperion while some banks are estimated to be spending up to $500 million each year on KYC compliance, according to a \",/*#__PURE__*/e(n,{href:\"https://www.thomsonreuters.com/en/press-releases/2016/may/thomson-reuters-2016-know-your-customer-surveys.html\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"2016 Thomson Reuters survey\"})}),\".\"]}),/*#__PURE__*/e(\"p\",{children:\"Here are some findings from the Consult Hyperion research about KYC costs:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The cost of a single KYC check may range from $13 to over $130.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The typical bank spends roughly $60 million per year on KYC processes.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Roughly 25% of customer applications in the UK are abandoned due to KYC difficulties.\"})})]}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"231\",src:\"https://framerusercontent.com/images/IscApDrXSXBOKtIkoHlTGixeqo.webp\",srcSet:\"https://framerusercontent.com/images/IscApDrXSXBOKtIkoHlTGixeqo.webp?scale-down-to=512 512w,https://framerusercontent.com/images/IscApDrXSXBOKtIkoHlTGixeqo.webp?scale-down-to=1024 1024w,https://framerusercontent.com/images/IscApDrXSXBOKtIkoHlTGixeqo.webp 1801w\",style:{aspectRatio:\"1801 / 463\"},width:\"900\"}),/*#__PURE__*/i(\"p\",{children:[\"Beyond the immediate cost of implementing processes, KYC has other costs associated with time and customer churn. Onboarding can take as long as one to three months, and\\xa0\",/*#__PURE__*/e(n,{href:\"https://www.theglobaltreasurer.com/2017/12/19/a-new-era-in-digital-banking-virtual-account-management/\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"12% of businesses\"})}),\"\\xa0reported changing banks due to KYC issues. Such business opportunity costs are arguably the most critical component of the costs associated with KYC.\"]}),/*#__PURE__*/i(\"p\",{children:[\"Non-compliance with KYC regulations can lead to steep fines, and these fines are increasing. In 2013 and 2014,\\xa0\",/*#__PURE__*/e(n,{href:\"https://www2.deloitte.com/content/dam/Deloitte/tr/Documents/financial-services/meeting-new-expectations-012915.pdf\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"$4.3 billion in fines\"})}),\"\\xa0were levied against financial institutions, a sum that quadrupled the fines of the nine previous years combined. As an example,\\xa0\",/*#__PURE__*/e(n,{href:\"http://www.bankinfosecurity.com/chase-a-6356/op-1\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"JP Morgan\"})}),\"\\xa0was fined more than $2 billion for a failure to report suspicious activities.\"]}),/*#__PURE__*/e(\"p\",{children:\"A significant proportion of KYC costs can be attributed to time spent on manual tasks. Some financial institutions still do not employ a digital onboarding process. For applications performed in the branch,\\xa0there are substantial costs associated with document archival and significant inconvenience to the customer if the documentation provided is insufficient (and they have to make a subsequent visit to the branch with the correct documentation). These processes will often involve hidden costs such as the time spent by staff performing checks, the need for staff to receive specialist training, and the need to employ compliance officers to ensure processes are being implemented correctly.\"}),/*#__PURE__*/e(\"p\",{children:\"Even for organizations that employ a digital onboarding and KYC experience, typically, KYC checks have a high failure rate, as high as 20%, due to data quality issues. Any failure leads to a switch to a manual process, which is costly and frustrating for both the customer and the organization.\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"em\",{children:\"Organizations that employ a digital onboarding experience powered by sophisticated identity technology are best positioned to strike the right balance between security and friction while reducing KYC costs.\"})}),/*#__PURE__*/e(\"h2\",{children:\"The benefits of a frictionless and secure KYC process\"}),/*#__PURE__*/e(\"p\",{children:\"There are many benefits to designing a frictionless and secure KYC process, chief among them being the prevention of fraud.\"}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"219\",src:\"https://framerusercontent.com/images/EmNMQ7IpeA8vbl9n7t6U1xPyNo.webp\",srcSet:\"https://framerusercontent.com/images/EmNMQ7IpeA8vbl9n7t6U1xPyNo.webp?scale-down-to=512 512w,https://framerusercontent.com/images/EmNMQ7IpeA8vbl9n7t6U1xPyNo.webp?scale-down-to=1024 1024w,https://framerusercontent.com/images/EmNMQ7IpeA8vbl9n7t6U1xPyNo.webp 1801w\",style:{aspectRatio:\"1801 / 438\"},width:\"900\"}),/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Fewer financial losses\"}),\": by ensuring that all customers are properly vetted from the outset, companies can prevent fraud resulting from false identities or online schemes. KYC processes also prevent\\xa0\",/*#__PURE__*/e(n,{href:\"https://ec.europa.eu/info/business-economy-euro/banking-and-finance/financial-supervision-and-risk-management/anti-money-laundering-and-countering-financing-terrorism_en\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"money laundering\"})}),\". It helps organizations carry out an adequate risk assessment on customers by identifying their financial history and owned assets.\"]}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Legal compliance\"}),\": In addition to fraud prevention, a frictionless and secure KYC process can also help to ensure compliance with anti-money laundering (AML) regulations. In many jurisdictions, it is a legal requirement for companies to carry out KYC checks on their customers. By properly verifying the identities of their customers, companies can avoid hefty fines and penalties.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Efficient business growth\"}),\": Manual KYC procedures slow down how quickly banks can onboard customers \u2014 a process that\\xa0\",/*#__PURE__*/e(n,{href:\"https://www.infosys.com/industries/financial-services/insights/documents/transforming-customer-onboarding-ai.pdf\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"can take anywhere from 2-34 weeks according to Forrester research\"})}),\".\\xa0By designing a frictionless KYC process, a business can attract and onboard more customers.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Increased customer trust\"}),\": KYC protects customer accounts from unauthorized third-party access, thereby building trust between customers and organizations, and attracting more customers to a business.\"]})})]}),/*#__PURE__*/e(\"h2\",{children:\"The latest trends in KYC verification\"}),/*#__PURE__*/e(\"p\",{children:\"KYC is a fast-evolving field with numerous trends across the globe:\"}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"219\",src:\"https://framerusercontent.com/images/JjdMSDVA8rwaw9QwB6Nt23pOHw.webp\",srcSet:\"https://framerusercontent.com/images/JjdMSDVA8rwaw9QwB6Nt23pOHw.webp?scale-down-to=512 512w,https://framerusercontent.com/images/JjdMSDVA8rwaw9QwB6Nt23pOHw.webp?scale-down-to=1024 1024w,https://framerusercontent.com/images/JjdMSDVA8rwaw9QwB6Nt23pOHw.webp 1801w\",style:{aspectRatio:\"1801 / 438\"},width:\"900\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"A push towards frictionless KYC\"}),\": Digitally-savvy customers are pushing back against more intrusive forms of KYC verification. They prefer products that have a frictionless onboarding experience \u2013 especially for neobanks and challenger banks. Smaller organizations simply cannot survive with heavy-handed KYC checks.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Digitization of official identities\"}),\": New initiatives to digitize legal documentation and create online identifiers have been initiated around the globe. For instance, the EU is preparing to introduce the European Digital Identity. KYC processes must integrate with the federal identity source for accurate KYC verification.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"New legal mandates\"}),\": Legislators\u2019 attention has recently turned to cryptocurrencies and NFTs, with \",/*#__PURE__*/e(n,{href:\"https://www.fatf-gafi.org/publications/fatfrecommendations/documents/public-consultation-guidance-vasp.html\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"new regulations\"})}),\" in place for companies in the sector. Regulatory hurdles are expected to become steeper for other industries too, especially so after the prevalence of fraud related to pandemic grants around the globe.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"AI-generated synthetic IDs\"}),\": Researchers believe that some criminal organizations use neural networks to generate synthetic IDs. As a result, a variety of data sources must be used to identify users.\"]})})]}),/*#__PURE__*/e(\"h2\",{children:\"The 5 pillars of a frictionless and secure KYC process\"}),/*#__PURE__*/e(\"p\",{children:\"Studies conducted in the banking industry have revealed that a frictionless onboarding experience is a vital part of attracting customers, and thereby, generating more revenue. There are 5 pillars to designing a frictionless and secure KYC process.\"}),/*#__PURE__*/e(\"h3\",{children:\"A proactive and continuous KYC strategy\"}),/*#__PURE__*/e(\"p\",{children:\"Organizations must view KYC as a proactive strategy, not a reactive afterthought or burdensome obligation.\\xa0Establishing a CIP (customer identification program) is one important initiative. CIP fulfills the federal requirements for financial institutions to confirm the identity of all potential customers. Achieving an effective CIP program, in turn, allows an organization to meet KYC requirements.\"}),/*#__PURE__*/e(\"p\",{children:\"Aside from strategy, setting up a fraud-resistant culture is critical to protect an organization from potential fraud and other threats. Reviewing data from a client shouldn't end with onboarding. Organizations must use an automated, holistic approach to implementing KYC and AML to continuously review and monitor a customer's ongoing transactions. An identity and risk profile must be built for each customer based on the information gathered thus far. Every profile subsequently becomes an important tool for detecting any unusual behaviors or actions that might indicate possible fraud risks.\"}),/*#__PURE__*/e(\"h3\",{children:\"Dynamic KYC checks\"}),/*#__PURE__*/i(\"p\",{children:[\"Subjecting every customer to the same heavyweight KYC checks not only increases friction due to false positives but also increases costs associated with KYC processes. KYC fraud checks are rarely 100% accurate. At times, a user's risk profile can fall into a grey area. An ideal KYC process must employ dynamic KYC checks that have a layered approach; starting with a light KYC check and progressively adding more friction by asking for more information for users that cross a certain risk threshold. This is where having the\\xa0ability to calculate dynamic risk scores\\xa0comes in handy.\\xa0Dynamically computed risk scores with corresponding thresholds can be used for triaging applications instantly to automatically \",/*#__PURE__*/e(\"em\",{children:\"accept\"}),\", \",/*#__PURE__*/e(\"em\",{children:\"decline\"}),\", or \",/*#__PURE__*/e(\"em\",{children:\"review\"}),\" an application.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Partner with the right KYC fraud detection tool\"}),/*#__PURE__*/e(\"p\",{children:\"Adopting the right KYC tool is the cornerstone of designing a secure, fast, and frictionless KYC experience. The features of the tool you choose will have a direct bearing on the user experience. Pick a KYC solution that offers flexibility to express customizable risk scores based on each business's unique risk requirements, multiple data sources for verifying identity information, as well as, continuous transaction monitoring to rerun KYC checks for users that engage in suspicious activities post onboarding.\"}),/*#__PURE__*/e(\"h3\",{children:\"A tailored and customizable KYC approach\"}),/*#__PURE__*/e(\"p\",{children:\"A tailor-made solution is often necessary to meet business needs. This is especially true for identity verification. Financial services companies can use custom identity verification rulesets to strike the proper balance between meeting compliance requirements and keeping customers happy. Optimized verification rules ensure the best match rates, avoiding false negatives. Custom rulesets also enable businesses to adjust rules on a case-by-case basis to address the specific needs and requirements of a country, region, or industry, increasing match rates.\"}),/*#__PURE__*/e(\"h3\",{children:\"Applied AI for KYC\"}),/*#__PURE__*/e(\"p\",{children:\"AI-powered KYC will allow organizations to spot suspicious KYC patterns without the need for human intervention.\\xa0This is particularly useful in presence of huge amounts of data, where even the most eagle-eyed KYC analysts would fail to spot discrepancies.\\xa0Of course, AI isn\u2019t sophisticated enough to perform full compliance analysis, but it\u2019s certainly a step in the right direction for organizations looking to save time and resources uncovering potential risks.\"}),/*#__PURE__*/e(\"h2\",{children:\"A modern and frictionless KYC experience is the need of the day\"}),/*#__PURE__*/e(\"p\",{children:\"A frictionless onboarding experience is vital to attract new customers, thereby, increasing revenue. KYC verification is critical for many reasons. It helps prevent fraud, ensure compliance with KYC regulations, and streamline customer onboarding processes. While the true costs associated with KYC are significant, there are many ways to reduce these costs. By implementing the 5 pillars of KYC verification such as the use of AI to improve the accuracy and efficiency of KYC, designing a tailored KYC approach, incorporating dynamic KYC checks, and adopting the right KYC tool for your business, customers can design a frictionless and secure KYC process. Oscilar's customizable KYC platform fully embraces these 5 pillars by offering a customizable, comprehensive, and AI-powered KYC platform with continuous transaction monitoring capabilities. By embracing the five pillars of a frictionless and secure KYC process, companies can reap the benefits of improved customer satisfaction, reduced fraud, and compliance with KYC regulations.\"})]});export const richText6=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"Today's credit landscape is in the midst of a revolution. Today\u2019s borrowers \u2014 no matter what type of credit they\u2019re seeking \u2014 want a straightforward, fast, and personalized lending experience. Lenders desire the same state-of-the-art customer experience that reduces drop-offs during the credit application process, improves customer satisfaction, and boosts revenue. However, legacy systems and infrastructure often hinder a lender\u2019s ability to provide a seamless digital borrowing experience. With the advent of artificial intelligence (AI) and real-time data analytics, credit decisioning is becoming increasingly automated. By choosing the right credit decisioning platform, lenders can improve customer satisfaction and boost revenue.\"}),/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"br\",{}),\"This blog post will cover the following topics:\"]}),/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"1.\"}),\" What is a credit decisioning platform and why do you need it\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"strong\",{children:\"2.\"}),\" The needs of modern credit decisioning\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"strong\",{children:\"3.\"}),\" The benefits of using a credit decisioning platform\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"strong\",{children:\"4.\"}),\" How to choose the right credit decisioning platform for your business\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"strong\",{children:\"5.\"}),\" The right credit decisioning platform is the foundation of modern credit decisioning\"]}),/*#__PURE__*/e(\"h2\",{children:\"What is a credit decisioning platform and why do you need it\"}),/*#__PURE__*/e(\"p\",{children:\"A credit decisioning platform allows lenders to define lending parameters precisely and thus sharpen their ability to approve creditworthy customers while rejecting proposals from customers who either are not creditworthy, fraudulent or cannot afford further debt.\\xa0A credit decisioning platform also enables lenders to change and tweak lending parameters as the risk profile and goals of the business evolve. The platform automates the collection of data that underpins credit decisions, offers out-of-the-box capabilities to define credit models, tools to speed up manual reviews, and enables use of advanced analytics and Machine Learning (ML) to discover new parameters for credit models.\"}),/*#__PURE__*/e(\"h3\",{children:\"The needs of modern credit decisioning\"}),/*#__PURE__*/e(\"p\",{children:\"Modern credit decisioning requires several capabilities that are absent in conventional credit decisioning tools:\"}),/*#__PURE__*/i(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Combining traditional credit data with alternative data sources\u2014such as telecom, utilities, and specialty finance\u2014can help drive more informed credit risk decisions.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Moving beyond traditional modeling techniques, such as logistic regression, to calculate credit worthiness.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Applying advanced analytics and ML to reveal patterns of financial behavior that can help predict a consumer\u2019s financial trajectory\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The predictive nature of trended credit data can help strengthen analytics and credit model development.\"})})]}),/*#__PURE__*/e(\"p\",{children:\"Addressing the above needs of modern credit decisioning is not merely an incremental change for conventional credit decisioning systems; it requires building an entirely new foundation. This foundation has fundamental characteristics that lend themselves to addressing the core requirements of a modern credit decisioning system. And that new foundation is built on AI and data analytics.\"}),/*#__PURE__*/e(\"p\",{children:\"Addressing the above needs of modern credit decisioning is not merely an incremental change for conventional credit decisioning systems; it requires building an entirely new foundation. This foundation has fundamental characteristics that lend themselves to addressing the core requirements of a modern credit decisioning system. And that new foundation is built on AI and data analytics.\"}),/*#__PURE__*/e(\"h3\",{children:\"The benefits of using a credit decisioning platform\"}),/*#__PURE__*/e(\"p\",{children:\"There are numerous benefits to using a credit decisioning platform for modern-day lending.\"}),/*#__PURE__*/i(\"p\",{children:[\"1. \",/*#__PURE__*/e(\"strong\",{children:\"Seamless borrowing experience:\"}),\" By automating much of the lending process, a credit decisioning platform enables lenders to offer a seamless experience for borrowers.\"]}),/*#__PURE__*/i(\"p\",{children:[\"2. \",/*#__PURE__*/e(\"strong\",{children:\"Increasing the accuracy of credit decisions:\"}),\" With the use of the right platform, credit decisioning can become more accurate. By aggregating data from multiple sources, analyzing it, and using ML models, a credit decisioning platform can identify patterns that humans would not be able to detect. This allows for a more comprehensive assessment of credit risk and leads to better credit decisions.\"]}),/*#__PURE__*/i(\"p\",{children:[\"3. \",/*#__PURE__*/e(\"strong\",{children:\"Personalized credit decisions: \"}),\"In addition to being more accurate, credit decisions made with a credit decisioning platform can also be more personalized. By taking into account factors such as income, employment history, and spending habits, a credit decisioning platform using the right data, can provide a more tailored credit decisions that is specific to the borrower. This leads to a better borrowing experience for the borrower and increased satisfaction with the credit product.\"]}),/*#__PURE__*/i(\"p\",{children:[\"4. \",/*#__PURE__*/e(\"strong\",{children:\"Faster credit decisions\"}),\": A credit decisioning platform can also help speed up the credit decisioning process. By automating the gathering and analysis of data, a credit decisioning platform can provide a credit decision in a matter of seconds or minutes, rather than days or weeks. This not only leads to a better borrowing experience for the borrower, but also allows the lender to capture the business value that would otherwise be lost.\"]}),/*#__PURE__*/i(\"p\",{children:[\"5. \",/*#__PURE__*/e(\"strong\",{children:\"Reduced cost of originations:\"}),\" AI-powered credit scoring using the right credit decisioning platform can reduce the cost of origination of loans by up to\\xa0\",/*#__PURE__*/e(n,{href:\"https://www.mckinsey.com/business-functions/risk/how-we-help-clients/impact-stories/digitizing-credit-risk-trims-costs-and-delights-customers\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"40%\"})}),\"\\xa0and reduce the cost of decisioning on low-complexity cases. Also, lenders can scale their operations to new geographies and higher volumes with a marginal increase in human workforce capacity.\"]}),/*#__PURE__*/e(\"h2\",{children:\"How to choose the right credit decisioning platform for your business\"}),/*#__PURE__*/e(\"p\",{children:\"When lenders are looking for a credit decisioning platform, certain features and capabilities are essential. Here are 10 things to look for in a credit decisioning platform:\"}),/*#__PURE__*/i(\"p\",{children:[\"1. \",/*#__PURE__*/e(\"strong\",{children:\"Speed: \"}),\"The ability to make \",/*#__PURE__*/e(\"strong\",{children:\"real-time decisions\"}),\". By aggregating the right data sources and enabling the use of a variety of credit models, lenders can now make credit decisions in real-time. This means that borrowers can get an instant decision on their loan application, without having to wait for days or weeks.\"]}),/*#__PURE__*/i(\"p\",{children:[\"2. \",/*#__PURE__*/e(\"strong\",{children:\"Customizability:\"}),\" The ability to customize the credit decisioning process. Each lender has its unique lending process and criteria. A good credit decisioning platform should be able to accommodate these differences and allow lenders to customize the software to fit their specific needs.\"]}),/*#__PURE__*/i(\"p\",{children:[\"3. \",/*#__PURE__*/e(\"strong\",{children:\"A user-friendly interface\"}),\". The platform should be easy to use and navigate so that lenders can get up and running quickly, as well as, reduce dependence on engineering resources.\"]}),/*#__PURE__*/i(\"p\",{children:[\"4. \",/*#__PURE__*/e(\"strong\",{children:\"Comprehensive reporting and analytics tools\"}),\". The platform should provide lenders with detailed reports on their credit decisioning process so that they can identify areas for improvements.\"]}),/*#__PURE__*/i(\"p\",{children:[\"5. \",/*#__PURE__*/e(\"strong\",{children:\"Advanced analytics and ML capabilities: \"}),\"The platform should allow aggregating data from multiple sources, analyzing it, and using ML models, that can identify patterns that humans would not be able to detect.\"]}),/*#__PURE__*/i(\"p\",{children:[\"6. \",/*#__PURE__*/e(\"strong\",{children:\"Flexible integration options\"}),\". The platform should be able to integrate with a lender\u2019s existing systems and infrastructure so that they can continue to use their existing tools and processes. An API-first credit decisioning platform is best positioned to allow that flexibility of integration.\"]}),/*#__PURE__*/i(\"p\",{children:[\"7. \",/*#__PURE__*/e(\"strong\",{children:\"A wide range of credit decisioning models\"}),\". The platform should offer a variety of credit decisioning models so that lenders can choose the one that best fits their needs.\"]}),/*#__PURE__*/i(\"p\",{children:[\"8. \",/*#__PURE__*/e(\"strong\",{children:\"The ability to handle a large volume of transactions\"}),\". The platform should be able to handle a high volume of transactions so that lenders can scale their business as needed.\"]}),/*#__PURE__*/i(\"p\",{children:[\"9. \",/*#__PURE__*/e(\"strong\",{children:\"Reliability, uptime, and 24/7 customer support\"}),\". A 24x7 borrower experience requires a credit decisioning platform that offers high reliability, uptime and 24x7 customer support.\"]}),/*#__PURE__*/i(\"p\",{children:[\"10. \",/*#__PURE__*/e(\"strong\",{children:\"Consumption-based pricing\"}),\". The platform should allow lenders to start small and scale pricing as the lender experiences value from the credit decisioning platform.\"]}),/*#__PURE__*/e(\"h2\",{children:\"The right credit decisioning platform is the foundation of modern credit decisioning\"}),/*#__PURE__*/e(\"p\",{children:\"A credit decisioning platform helps lenders make credit decisions in real time. This type of platform is essential for modern lenders who want to provide a fast and personalized lending experience to their borrowers. Credit decisioning platforms offer many benefits, including the ability to make decisions in real time, customizing the credit decisioning process, and using advanced analytics and ML capabilities to increase the accuracy of lending decisions. When choosing a credit decisioning platform, lenders should keep in mind the 10 things listed above to ensure they find the best solution for their needs. By finding a credit decisioning platform that offers all of these features, lenders can dramatically improve customer satisfaction and boost revenue.\"})]});export const richText7=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/i(\"p\",{children:[\"The growing adoption of online services--from mobile banking, on-demand services, e-commerce, instant credit, on-demand healthcare--is providing the impetus for a corresponding increase in online fraud. The fraud management industry is a rapidly growing field; per \",/*#__PURE__*/e(n,{href:\"https://www.fortunebusinessinsights.com/industry-reports/fraud-detection-and-prevention-market-100231\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"Fortune Business Insights\"})}),\", the global fraud detection and prevention market is projected to grow from USD 30.65 billion in 2022 to USD 129.17 billion in 2029, exhibiting a CAGR of 22.8%.\"]}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"486\",src:\"https://framerusercontent.com/images/Caos9lS5oE6PBcKHYNf6Pj0Sb4.jpg\",srcSet:\"https://framerusercontent.com/images/Caos9lS5oE6PBcKHYNf6Pj0Sb4.jpg?scale-down-to=512 512w,https://framerusercontent.com/images/Caos9lS5oE6PBcKHYNf6Pj0Sb4.jpg?scale-down-to=1024 1024w,https://framerusercontent.com/images/Caos9lS5oE6PBcKHYNf6Pj0Sb4.jpg 1800w\",style:{aspectRatio:\"1800 / 972\"},width:\"900\"}),/*#__PURE__*/e(\"p\",{children:\"The impact of fraud on a business can be profound; besides the obvious financial losses, it also erodes customer trust, damages the company brand, and increases operational costs. Unfortunately, businesses that don\u2019t adapt are at an increased risk of experiencing even higher fraud losses. That\u2019s where fraud detection software come in. The best way to prevent fraud and curb fraud losses is to partner with a fraud detection company to manage risk and establish trust across the customer journey.\"}),/*#__PURE__*/e(\"p\",{children:\"But because fraud detection software can be difficult to understand and select, this article aims to demystify the process. In this article, I'll go over the top fraud detection software on the market, their strengths and weaknesses, and how to pick the right one for your business.\"}),/*#__PURE__*/e(\"h2\",{children:\"What is a fraud detection software\"}),/*#__PURE__*/e(\"p\",{children:\"Fraud detection software is a tool that is used to find fraud and financial abuse. It usually performs a variety of fraud-related tasks, such as identifying unusual activities, analyzing data patterns, addressing adversarial patterns, and generating reports.\"}),/*#__PURE__*/e(\"p\",{children:\"Overall, the best fraud detection software delivers the following key benefits:\"}),/*#__PURE__*/i(\"ul\",{style:{\"--framer-font-size\":\"16px\",\"--framer-line-height\":\"1.5em\",\"--framer-text-alignment\":\"start\",\"--framer-text-color\":\"rgb(55, 53, 47)\",\"--framer-text-transform\":\"none\"},children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Provide a frictionless and safe customer experience\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Accept good users and increase revenue by reducing false positives\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Reduce the financial losses from criminal and friendly fraud\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Build customer trust and reduce brand damage as the result of fraud\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Decrease the operational costs associated with fighting fraud\"})})]}),/*#__PURE__*/e(\"h2\",{children:\"5 things to look for in a fraud detection software\"}),/*#__PURE__*/e(\"h3\",{children:\"Integrated Machine Learning and rules approach\"}),/*#__PURE__*/e(\"p\",{children:\"As new adversarial patterns emerge, decisioning workflows must evolve instantly to address them. Rules lend themselves to changes easily, making them a good fit for mitigating new fast-evolving adversarial patterns. However, as fraud patterns adapt to human-defined thresholds, the complexity of features and their corresponding thresholds used by rules can increase rapidly necessitating the use of Machine Learning models.\"}),/*#__PURE__*/e(\"p\",{children:\"The best fraud detection software does not just offer black box ML models with a fraud score but employs an integrated Machine Learning and rules approach, allows you to use your custom ML models with customizable rules, and offers a platform for performing feature engineering to train your ML models. Furthermore, it also makes the same features that you trained your ML models on available to your rules.\"}),/*#__PURE__*/e(\"h3\",{children:\"Customizable rules engine\"}),/*#__PURE__*/e(\"p\",{children:\"As much as opinionated data formats make applying a fraud detection software for a specific use case easier, it fundamentally limits the user's ability to tailor the fraud detection software to their data, business needs, and unique fraud detection patterns. Fraud detection software that allows a company to send data in a flexible format via a REST API, offering the ability to transform the data, create aggregates, and historical lists using the data, and then make that data available to the rules engine is a core need for enterprise companies.\"}),/*#__PURE__*/e(\"h3\",{children:\"Comprehensive testing and trial deployment functionality\"}),/*#__PURE__*/e(\"p\",{children:\"What most fraud detection software often miss is the ability to backtest new changes and gradually deploy them. In the same way that you never deploy software applications without testing them, you rarely want to deploy a new change to your fraud ML model or rules without knowing how they will perform in practice. This ability to accurately backtest new decisions is surprisingly difficult to build and hence capability rarely available in conventional fraud detection software.\"}),/*#__PURE__*/i(\"p\",{children:[\"The best fraud detection software integrates historical data with real-time data, replays rules by running them on past data, and allows you to observe the match rate and matched data to validate the change and iterate on it. It should also offer trial mode deployment where the new fraud detection logic runs on live traffic but doesn't take effect; a necessary step to study how the change will affect the most recent user transactions. After assessing the impact of the new fraud detection logic in trial mode, the fraud detection software must also allow you to \",/*#__PURE__*/e(\"em\",{children:\"canary\"}),\" the changes into production by gradually turning the dial from 0% to 100% of user requests rather than impacting all users abruptly.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Data integration and fraud analytics\"}),/*#__PURE__*/e(\"p\",{children:\"There is a clear divide in the fraud detection software market; some support visualization of data to find new fraud signals while others allow you to decision on fraud signals that you have already found. However, to increase the speed and accuracy of fraud detection, you need both. The data that was used to find a new fraud signal should also be used to then decision on it.\"}),/*#__PURE__*/e(\"p\",{children:\"The best fraud detection software integrates real-time fraud analytics and visualization with decisioning workflows, allowing you to:\"}),/*#__PURE__*/i(\"ul\",{style:{\"--framer-font-size\":\"16px\",\"--framer-line-height\":\"1.5em\",\"--framer-text-alignment\":\"start\",\"--framer-text-color\":\"rgb(55, 53, 47)\",\"--framer-text-transform\":\"none\"},children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"search through user activity logs\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"slice and dice data + visualize patterns\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"use graph analytics to flag entities that have similar characteristics\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"use the fraud signals discovered from the above processes to train ML models and run rules\"})})]}),/*#__PURE__*/e(\"h3\",{children:\"Data-driven case management\"}),/*#__PURE__*/e(\"p\",{children:\"Lack of the right data at the time of decisioning has a profound impact on a key metric tracked by fraud and risk teams -- the time spent on manual reviews. A majority of the time spent by analysts is on collecting data related to the case. A plethora of case management tools exist in the market, but few have the real-time data analytics capabilities that truly make fraud and risk operations efficient. You need graph analytics capability to analyze group behavior of related entities, ability to pull in data from 3rd party tools, and real-time data analytics capability to assess past user behavior, in conjunction with case management capabilities.\"}),/*#__PURE__*/e(\"h2\",{children:\"How to Choose the Right Fraud Detection Software for Your Business\"}),/*#__PURE__*/e(\"p\",{children:\"Thus far, we discussed what is fraud detection software and the key capabilities of the best fraud detection software, but how do you choose the right one for your business?\"}),/*#__PURE__*/e(\"p\",{children:\"Here are a few factors to consider:\"}),/*#__PURE__*/e(\"h3\",{children:\"Complexity of independent fraud detection tools\"}),/*#__PURE__*/e(\"p\",{children:\"The conventional approach to addressing fraud has been to layer a slew of independent fraud-prevention tools and systems on top of one other, each with its own set of capabilities. The result is a fragmented fraud stack, often characterized by redundancies and cost inefficiencies.\"}),/*#__PURE__*/e(\"p\",{children:\"The core problem with this approach, other than the increased complexity, is the inability to use an evolving 360-degree view of the user data for mitigating risk throughout the customer journey. After all, if a user has a high account risk, that should factor in the risk assessment for the user's payment transaction.\"}),/*#__PURE__*/e(\"p\",{children:\"Platform approaches that have come into the market in recent years have sought to address this. Selecting a comprehensive fraud detection platform with a flexible API and customizable decisioning engine is paramount to your ability to accurately model user behavior and apply it for assessing risk throughout the customer journey.\"}),/*#__PURE__*/e(\"h3\",{children:\"The need to consult multiple 3rd party tools\"}),/*#__PURE__*/e(\"p\",{children:\"Often, fraud detection tools offer a single fraud score based on proprietary data and algorithms. But do you want to depend on one company's data or would you rather consult multiple data sources? Increasingly, companies are opting to consult multiple 3rd party tools for various fraud scores in conjunction with internal data for holistic fraud detection capability.\"}),/*#__PURE__*/e(\"p\",{children:\"The best fraud detection software employs a platform approach -- the ability to leverage multiple data sources and fraud scores versus a single one based on their own proprietary data.\"}),/*#__PURE__*/e(\"h3\",{children:\"Time spent on accessing the right data\"}),/*#__PURE__*/e(\"p\",{children:\"We surveyed dozens of fraud and risk professionals and the feedback was resounding -- a majority of the time in fraud detection operations is spent on assembling the right data that is typically fragmented across various databases, applications, and the data warehouse. Often fraud detection tools lack crucial data integration and analytics functionality that is instrumental in cutting down the meantime to mitigation for addressing adversarial fraud patterns.\"}),/*#__PURE__*/e(\"p\",{children:\"A comprehensive fraud detection solution must have no-code data integration functionality that allows non engineers to easily pull in all the right data from various internal data systems and 3rd party tools alike. And have the ability to integrate external and internal data and make it available to ML model training and running custom rules.\"}),/*#__PURE__*/e(\"h3\",{children:\"The need for fraud analytics\"}),/*#__PURE__*/e(\"p\",{children:\"Finding a new adversarial pattern is like finding a needle in a haystack; you need to sift through a lot of data in real-time, slice and dice it, and visualize the patterns to spot a new fraud trend. Moreover, spotting a new fraud trend is followed by decisioning on the same set of signals. At present, fraud analytics is done on the data warehouse using SQL in a batch fashion while scoring takes place on a decisioning engine. Data from the SQL data warehouse is different from the data used by the decisioning engine fundamentally impacting the accuracy and speed of the fraud mitigation process. The fraud detection tools market is fragmented between tools that do analytics or visualization and tools that do fraud scoring and decisioning. However, accurate and timely fraud detection requires both to work in tandem and in real-time.\"}),/*#__PURE__*/e(\"h3\",{children:\"Time spent on manual review\"}),/*#__PURE__*/e(\"p\",{children:\"A core issue for fraud and risk teams is efficiency concerns driven by the growing number of cases sent for manual review. Basic operational improvements and investment in enhancing review workflow tools may help reduce the time and money invested internally on manual review, but they merely address the symptoms rather than the problem itself, and therefore don't address the foundational issues -- a) the lack of comprehensive data available at the time of decisioning causing more cases to fall in the gray area, that then get routed for manual review b) the lack of real-time data available to the case reviewer to accurately and swiftly evaluate the case.\"}),/*#__PURE__*/e(\"h2\",{children:\"Fight fraud with a well-rounded fraud detection software\"}),/*#__PURE__*/e(\"p\",{children:\"To continue modernizing your business by moving critical customer interactions online while also dealing with the complexity of adversarial patterns, there is an urgent need to pick a well-rounded fraud detection software. One that is not only comprehensive in the functionality it provides but also sufficiently customizable to adapt to your company's evolving business needs. After all, balancing fraud losses with friction in the user experience isn't a one-time decision.\"}),/*#__PURE__*/i(\"p\",{children:[\"In this article, we've looked at five things to look for in a fraud detection solution, as well as, a guide on how to pick the best one for your business needs. If you would like to learn more, we'd \",/*#__PURE__*/e(n,{href:\"mailto:hi@oscilar.com\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"love to chat\"})}),\".\"]})]});export const richText8=/*#__PURE__*/i(o.Fragment,{children:[/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"br\",{}),\"As digital businesses continue to grow, so does online fraud. The \",/*#__PURE__*/e(n,{href:\"https://www.javelinstrategy.com/content/Javelin-2021-Identity-Fraud-Study\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"total fraud losses in 2020 amounted to 56 billion USD\"})}),\" and \",/*#__PURE__*/e(n,{href:\"https://businessfraudprevention.org/fraud-statistics/\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"U.S. businesses will lose an average of 5% of gross revenue to fraud\"})}),\", making fraud mitigation a core area of focus in businesses of all manner. At the same time, detecting fraud in real-time is a difficult proposition causing substantially high monetary losses due to late detection of fraudulent behavior. More than 50% of organizations \",/*#__PURE__*/e(n,{href:\"https://home.kpmg/xx/en/home/insights/2019/05/the-multi-faceted-threat-of-fraud-are-banks-up-to-the-challenge-fs.html\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"said in a survey\"})}),\" that they recover less than only 25% of fraud losses. In addition to monetary losses, late fraud detection causes irreparable damage to brand equity and user trust alike.\"]}),/*#__PURE__*/e(\"p\",{children:\"Fraudsters are getting more sophisticated in their methods, and it is becoming more difficult for businesses to detect and prevent fraudulent activity. This is where Artificial Intelligence (AI) comes in. AI is the foundation of effective online fraud detection, and businesses must implement AI-based fraud detection strategies to stay ahead of ever-evolving fraud patterns. In this blog post, we will discuss why AI is the future of online fraud detection, what it entails, and how it can help your business protect itself from sophisticated fraudulent activity.\"}),/*#__PURE__*/e(\"h2\",{children:\"AI for Online Fraud Detection: The missing part of the puzzle\"}),/*#__PURE__*/e(\"p\",{children:\"Up until recently, the primary approach to fraud prevention was centered around human-defined rules coupled with a manual review of potentially fraudulent transactions. While human review of fraudulent transactions might lead to fewer false positives, it, unfortunately, leaves a window of opportunity for advanced and fast-evolving adversarial techniques leading to substantial financial and reputation damage. Therefore, effective fraud mitigation requires accurate and instant decisioning ability with low false positives.\"}),/*#__PURE__*/e(\"p\",{children:\"Instant fraud decisioning involves ingesting hundreds of signals, some from the incoming transaction and some from historical analytics, to decide the appropriate course of action for the transaction as it is happening. This is where artificial intelligence comes in. Artificial intelligence is ideal for detecting online fraud because it can rapidly and accurately identify automated, increasingly complex fraud attempts.\"}),/*#__PURE__*/i(\"p\",{children:[/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"em\",{children:\"The best AI-based fraud detection strategies use a combination of supervised and unsupervised machine learning, as well as, an integrated machine learning and rules approach, which enables businesses to quickly identify patterns in fraudulent behavior.\"}),/*#__PURE__*/e(\"br\",{}),\"This is important because as fraudsters become more sophisticated, they develop new methods that are difficult to detect using traditional fraud detection methods.\"]}),/*#__PURE__*/e(\"p\",{children:\"There are several reasons why artificial intelligence is the future of online fraud detection:\"}),/*#__PURE__*/i(\"ol\",{style:{\"--framer-font-size\":\"16px\",\"--framer-line-height\":\"1.5em\",\"--framer-text-alignment\":\"start\",\"--framer-text-color\":\"rgb(55, 53, 47)\",\"--framer-text-transform\":\"none\"},children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"AI can help businesses keep up with the increasing sophistication of fraudsters.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"AI-based fraud detection strategies are more effective than traditional rules-only and manual methods in detecting and preventing complex multi-dimensional fraudulent activity.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"AI enables businesses to rapidly and accurately identify fraudulent behavior, which is essential for protecting businesses from loss.\"})})]}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"370\",src:\"https://framerusercontent.com/images/qdZOm4h1yiz4jvdNHNLTIfvYsfE.jpg\",srcSet:\"https://framerusercontent.com/images/qdZOm4h1yiz4jvdNHNLTIfvYsfE.jpg?scale-down-to=512 512w,https://framerusercontent.com/images/qdZOm4h1yiz4jvdNHNLTIfvYsfE.jpg?scale-down-to=1024 1024w,https://framerusercontent.com/images/qdZOm4h1yiz4jvdNHNLTIfvYsfE.jpg 1920w\",style:{aspectRatio:\"1920 / 740\"},width:\"960\"}),/*#__PURE__*/e(\"h2\",{children:\"Industry insights on why AI is the future of online fraud detection\"}),/*#__PURE__*/i(\"p\",{children:[\"Recent research is shedding light on why AI is the future of online fraud detection. According to the\\xa0\",/*#__PURE__*/e(n,{href:\"https://www.acfe.com/\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"Association of Certified Fraud Examiners (ACFE)\"})}),\"'s\\xa0\",/*#__PURE__*/e(n,{href:\"https://www.sas.com/content/dam/SAS/documents/briefs/third-party/en/acfe-anti-fraud-technology-112576.pdf\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:/*#__PURE__*/e(\"em\",{children:\"Anti-Fraud Technology Benchmarking Report\"})})}),/*#__PURE__*/e(\"em\",{children:\",\"}),\" over 60% of organizations will significantly increase the budgets allocated to the adoption of anti-fraud technology over the next two years. While currently, only 17% of businesses employed artificial intelligence to detect and prevent fraud, that number is expected to jump to 26% by 2023-2024, a growth of almost 53%. The ACFE study found that the use of AI techniques to fight fraud will double over the next two years.\"]}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"1073\",src:\"https://framerusercontent.com/images/LKe8LdylBiJrVxOJuRaxoZS9Rbk.jpg\",srcSet:\"https://framerusercontent.com/images/LKe8LdylBiJrVxOJuRaxoZS9Rbk.jpg?scale-down-to=1024 858w,https://framerusercontent.com/images/LKe8LdylBiJrVxOJuRaxoZS9Rbk.jpg?scale-down-to=2048 1717w,https://framerusercontent.com/images/LKe8LdylBiJrVxOJuRaxoZS9Rbk.jpg 1800w\",style:{aspectRatio:\"1800 / 2146\"},width:\"900\"}),/*#__PURE__*/i(\"p\",{children:[\"The 2022 \",/*#__PURE__*/e(n,{href:\"https://www.pwc.com/gx/en/services/forensics/economic-crime-survey.html\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"Global Economic Crime and Fraud Survey\"})}),\", conducted by PwC, is based on interviews with 1,296 executives across 53 countries and regions around the world to assess how well digital fraud prevention is progressing globally. The report discovered that 46% of surveyed organizations reported experiencing fraud, corruption or other economic crimes in the last 24 months. The report states three critical recommendations made by the survey respondents:\"]}),/*#__PURE__*/i(\"ol\",{style:{\"--framer-font-size\":\"16px\",\"--framer-line-height\":\"1.5em\",\"--framer-text-alignment\":\"start\",\"--framer-text-color\":\"rgb(55, 53, 47)\",\"--framer-text-transform\":\"none\"},children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Understand the end-to-end lifecycle of customer-facing products.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Strike the proper balance between user friction and fraud controls. The dual objectives of keeping false positives as low as possible and catching true fraud can be achieved by applying AI in fraud detection efforts.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Orchestrate data: It is crucial to consolidate fraud indicators in a central platform, like Oscilar, that can track the end-to-end lifecycle of users (fraudsters or not) and generate meaningful alerts.\"})})]}),/*#__PURE__*/i(\"p\",{children:[\"To overcome these challenges, businesses should \",/*#__PURE__*/e(n,{href:\"https://oscilar.com/solutions/fraud-detection\",motionChild:!0,nodeId:\"LW0fAVOt9\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(a.a,{children:\"use more machine learning and AI in tandem with prescriptive analytics\"})}),\", as the graph below from the 2018 report shows.\"]}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",height:\"486\",src:\"https://framerusercontent.com/images/ajwUEdHvXseij3Yd9aS6tLUnAfY.jpg\",srcSet:\"https://framerusercontent.com/images/ajwUEdHvXseij3Yd9aS6tLUnAfY.jpg?scale-down-to=512 512w,https://framerusercontent.com/images/ajwUEdHvXseij3Yd9aS6tLUnAfY.jpg?scale-down-to=1024 1024w,https://framerusercontent.com/images/ajwUEdHvXseij3Yd9aS6tLUnAfY.jpg 1800w\",style:{aspectRatio:\"1800 / 972\"},width:\"900\"}),/*#__PURE__*/e(\"h2\",{children:\"How is AI used for online fraud detection?\"}),/*#__PURE__*/e(\"p\",{children:\"Digital businesses with the best track record of defeating internet fraud do the following to apply AI for fraud detection:\"}),/*#__PURE__*/i(\"ul\",{style:{\"--framer-font-size\":\"16px\",\"--framer-line-height\":\"1.5em\",\"--framer-text-alignment\":\"start\",\"--framer-text-color\":\"rgb(55, 53, 47)\",\"--framer-text-transform\":\"none\"},children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"strong\",{children:\"Use performance insights from high-quality rules to train models using supervised machine learning for detecting fraud attempts quicker than manual approaches.\"})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Digital businesses we work with say that they start their fraud detection journeys with rules-based approaches that are easy to put in place. As fraud patterns become increasingly complex, scaling online fraud detection efforts becomes challenging with a rules-only approach. This scaling is best achieved by replacing a subset of rules with supervised machine learning models. Adopting supervised machine learning is easier for some businesses that have data scientists on staff who are trained on the foundational concepts and algorithms. Others might depend on consulting a variety of third-party fraud scores that assess the risk of a user's transaction based on a multitude of signals such as phone, email, online identity, ip address, and more.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"strong\",{children:\"Integrate supervised and unsupervised machine learning to effectively find anomalies in emerging user transactions.\"})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Integrating supervised and certain unsupervised machine learning techniques is one way AI can be effectively applied for online fraud prevention. While a subset of fraud signals are best modeled by supervised machine learning techniques, certain types of anomaly detection is best achieved with an unsupervised machine learning approach. In our experience, a more integrated approach to online fraud prevention that combines supervised and unsupervised machine learning can deliver fraud scores that are twice as predictive as previous approaches.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"strong\",{children:\"Capitalize on large-scale, universal data networks to complement custom machine learning algorithms to dramatically improve the predictive power of fraud prevention scores.\"})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Often consulting custom in-house machine learning models is insufficient to capture a large enough surface area of fraudulent patterns. The most advanced digital businesses are looking for ways to supplement their machine learning models using large-scale universal data sets. Many businesses have years of transaction data they rely on initially for building in-house machine learning models. However, no business or tool has the best data. Therefore, supplementing in-house machine learning models with 3rd party fraud scores that have large-scale universal data networks--often including billions of transactions captured over decades from thousands of customers globally--improves fraud prevention dramatically.\"})})]}),/*#__PURE__*/e(\"p\",{children:\"The combination of these three factors forms the foundation of online fraud detection.\\xa0Digital companies faced with a high risk of fraud leverage online fraud detection platforms, like Oscilar, that have the above functionality, to enable their fraud experts to have the insights they need to identify and combat fraud early.\"}),/*#__PURE__*/e(\"h2\",{children:\"AI is the future of online fraud detection\"}),/*#__PURE__*/e(\"div\",{className:\"framer-text-module\",style:{\"--aspect-ratio\":\"560 / 315\",aspectRatio:\"560 / 315\",height:\"auto\",width:\"100%\"},children:/*#__PURE__*/e(t,{componentIdentifier:\"module:NEd4VmDdsxM3StIUbddO/9rhBPUZttCbLCWqJEL42/YouTube.js:Youtube\",children:i=>/*#__PURE__*/e(r,{...i,play:\"Off\",shouldMute:!0,thumbnail:\"Medium Quality\",url:\"https://youtu.be/smPos0mJvh8\"})})}),/*#__PURE__*/e(\"p\",{children:\"Fraud detection is hard enough, but it's made much more difficult when the only data available to an organization is limited, fragmented and not appropriately analyzed. AI is a must-have foundation for online fraud detection, and platforms built on these technologies need to achieve three things exceptionally well to succeed. First, supervised machine learning algorithms need to be fine-tuned with the invaluable historical performance of high-quality rules data to minimize false positives and scale fraud detection efforts. Second, unsupervised machine learning is required to find emerging anomalies signaling more sophisticated forms of online fraud. 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}