{"id":5538,"date":"2023-09-29T16:21:10","date_gmt":"2023-09-29T16:21:10","guid":{"rendered":"https:\/\/www.horsesforsources.com\/?p=5538"},"modified":"2024-09-11T11:48:42","modified_gmt":"2024-09-11T11:48:42","slug":"genpact-financialcrime-genai_092923","status":"publish","type":"post","link":"https:\/\/www.horsesforsources.com\/genpact-financialcrime-genai_092923\/","title":{"rendered":"Fighting financial crime with GenAI… less Gen-wash and more Genpact please!"},"content":{"rendered":"
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You know what we\u2019re sick and tired of at HFS? Ridiculous empty-promise press releases touting GenAI capabilities with no in-production use cases or substantiated benefits.<\/p>\n
You know, the ones boasting \u201cwidget ABC now with generative AI\u201d. A close second on the naughty list is press releases purporting to showcase generative AI capabilities but are really promoting the same non-generative AI capabilities they already had.\u00a0 Then there are all the promises of billions of dollars of “investment in GenAI” without any sort of accountability they’ll ever be held to it.<\/p>\n
Let’s be honest, the entire marketplace is exhausted<\/em> by genAI-washing, where everyone can pretty much claim whatever they want and never be held to account. This is such a shame because the potential is massive as we explore the seemingly limitless possibilities of GPT4 technologies.<\/a><\/p>\n So when we do manage to find actual GenAI use cases that are in production with real live customers and delivering benefits, we move like the BS-busting analyst cheetahs that we are, and we cover them! This was the case when Genpact briefed us on its newly developed anti-financial crime (fincrime) regulatory risk and compliance GenAI capabilities (see news release here<\/a>). We approached with an appropriate level of \u201cshow me the outcomes\u201d cynicism and were pleasantly surprised to find that despite its shiny newness, its capabilities were developed with not one but two<\/em> actual clients (gasp), and they were showcasing in-production use cases.<\/p>\n Despite financial services firms being the early adopters and now long-time poster children of applied automation and AI, these capabilities have not been adopted consistently across all business functions. Areas like shared services, risk modelling, and customer service have benefited substantially from intelligent automation beating down the manual processes caused by compounded legacy tech debt. But many processes within anti-fincrime functions like fraud, know your customer (KYC), and anti-money laundering (AML) have proven to buck the trend by being non-standard, requiring humans to make final decisions, and\/or not being sufficiently explainable to satisfy regulators. The current state reality of many fincrime groups within financial institutions is loads of humans generating content to enable or justify decisions. This is intense, detail-oriented work in a specialized domain with a high burn-out rate.<\/p>\n Genpact acquired riskCanvas, a software suite of AML solutions and a related consulting practice, from Booz Allen in 2019 to help enhance its fledging risk and compliance practice. A couple of Genpact\u2019s riskCanvas clients, including Apex Fintech Solutions, were excited about the potential of GenAI and agreed to a discovery session turned hack-a-thon with Genpact and its partner AWS to road test AWS\u2019 Bedrock foundational AI model capabilities. Genpact and its clients leveraged their respective private and secure data from riskCanvas, chronicling years of AML events, to feed various foundational GenAI models. The initial results were so encouraging they transitioned to a full-on hack-a-thon at the Amazon2 headquarters. From the event, two use cases rose to the top as offering the greatest immediate impact:<\/p>\n It is critical to note that the generative capabilities of GenAI are also used to produce explainability statements. The hack-a-thons took place in July 2023. These production use cases were hardened and put into production quickly because the necessary data was available and already hosted securely on riskCanvas in the AWS cloud. Also critical to note \u2013 these are publicly available models used privately in a static format to ensure privacy.<\/p>\n Other use cases have also been identified \u2013 all loosely in the ilk of fincrime functions with loads of content documentation that needs to be produced and is currently heavily manual \u2013 like customer due diligence review and summation, case review and summation, fraud alert decisioning with detailed explanation, transaction monitoring alert decisioning with detailed explanation. You get the picture.<\/p>\n Nothing happens if you don\u2019t try. Failing fast is a great mantra, but it requires effort<\/a>. Kudos to Genpact, its intrepid clients, and AWS for experimenting and succeeding in building in-production GenAI models that can legitimately help better fight financial crime and improve the harried lives of fincrime analysts. The regulatory burden of documented proof of decisioning is a heavy lift for firms of all sizes. But it is a problem screaming for GenAI solutions \u2013 literally, the power of generative content trained on private data from past reports \u2013 is an ideal fit.<\/p>\n The rub for fincrime compliance typically is unhappy regulators. The critical nuance here is GenAI enables the humans, with humans taking all final decisions with full explainability documented.\u00a0 Here are our critical focal points for successful GenAI<\/a>:<\/p>\nAnti-fincrime regulatory compliance \u2013 super important, super manual<\/strong><\/h3>\n
Genpact, some edgy riskCanvas clients, and AWS came together to make fincrime compliance less soul-crushing<\/strong><\/h3>\n
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The bottom line. Genpact makes a bold step forward to make GenAI real and impactful in fighting financial crime. Banks tired of analyst burn-out take notice!<\/strong><\/span><\/h3>\n