What are the alternatives and challenges of AI within the fraud prevention and identification verification house? We caught up with Heidi Hunter, Chief Product Officer for IDology, a GBG firm, to search out out.
IDology delivers a complete suite of identification verification, AML/KYC, and fraud administration options to assist companies drive income, deter fraud, and preserve compliance. Based in 2003, IDology made its Finovate debut in 2012. GBG acquired the corporate in 2019.
Ms. Hunter joined GBG Americas in 2011 and has labored in each product innovation and buyer success roles throughout her profession with the corporate. She brings greater than 13 years’ expertise in supporting prospects and serving to them with their enterprise wants via product innovation, help, and implementation roles.
At present, Ms. Hunter is liable for driving the corporate’s product roadmap and bringing new improvements to the identification verification market via strategic product growth.
AI has introduced on challenges and alternatives in terms of fraud and monetary crime. What are the principal challenges monetary establishments are going through?
Heidi Hunter: There are 4 principal areas of concern: cybersecurity and fraud, biased fashions, human oversight, and regulatory compliance.
Deloitte has written on the rising concern of AI as a cybersecurity and fraud menace, noting that 51% of executives interviewed imagine that the cybersecurity vulnerabilities of AI are a serious concern. One challenge is the issue of extra and higher faux paperwork. AI will simplify creation of passports, driver’s licenses, and ID playing cards which are nearly indistinguishable from real ones. One other challenge right here is elevated artificial identification fraud. Generative AI is a productiveness device for fraudsters, creating extremely sensible artificial identities at scale.
Moreover, there may be simpler phishing and social engineering. A current examine of 1,000 determination makers discovered 37% had skilled deepfake voice fraud. And Generative AI is used to gasoline a surge in phishing ways.
You additionally talked about biased fashions, human oversight, and compliance.
Hunter: The usage of AI and machine studying (ML) algorithms have come underneath scrutiny with considerations over information bias, transparency, and accountability. With regard to human oversight, 88% of customers reported that they’d discontinue a useful personalization service in the event that they didn’t perceive how their information can be managed.
Lack of human oversight can be a regulatory concern. AI typically lacks transparency, leaving companies uncovered after they should clarify their decisioning, which has introduced expectations of future regulation. AI-generated deepfakes are shifting quick and policymakers can’t sustain.
Can the identical expertise that’s enabling fraudsters additionally allow FIs to thwart them?
Hunter: Sure, particularly when AI is paired with human intelligence. AI advantages from consultants charged with overseeing incoming and outgoing information. A educated fraud analyst accompanying AI-based options can catch new and established fraud developments. This contains novel threats that AI options on their very own might miss.
From a compliance perspective, this implies companies can supply a extra clear resolution and handle potential bias. Supervised AI can get rid of the necessity to manually confirm an ID, and assist present the reason wanted for compliance and regulatory necessities.
Automation performs a serious position in AI. So does human oversight. Are you able to discuss concerning the relationship between AI and automation?
Hunter: Automation is often rule-based and follows predetermined directions, whereas AI can be taught from information and make selections based mostly on that information. In different phrases, automation software program operates on a set of predefined guidelines, whereas AI could make predictions and selections based mostly on the info it’s introduced with. The ‘predictions’ side of AI- and ML-based tech is the place human supervision performs such an vital position.
What’s the correct steadiness between human oversight and AI? What position do people have in an more and more AI-powered world?
Hunter: Like with any device, human-supervised AI is nice when it’s one half of a bigger identification verification (IDV) technique.
People have a job at each ‘stage’ of AI use or implementation: in growth, by way of what information is getting used to coach a mannequin; throughout deployment, the place an AI-based device is used and to what diploma; and in terms of holding AI-based instruments accountable. This implies analyzing a given output and what selections a FI makes based mostly on that output.
For identification verification particularly, how has human-supervised AI helped resolve issues?
Hunter: Shoppers additionally set the bar excessive for seamless interactions. For instance, 37% of customers deserted a digital onboarding course of as a result of it was too time-consuming. Overcoming this problem requires a complete technique. Human-supervised AI can play a essential position within the course of, as it could shortly scrutinize huge volumes of digital information to uncover patterns of suspicious exercise whereas additionally offering perception and transparency into how selections are made.
Are companies embracing human-supervised AI? What hurdles stay to broader adoption?
Hunter: Sure, as a result of whereas there may be a variety of pleasure round what AI can do, a number of companies and folks within the tutorial neighborhood imagine AI isn’t able to make unsupervised selections. As talked about earlier, companies present concern over AI working by itself. Issues vary from moral questions, to cybersecurity and fraud dangers, to creating a nasty enterprise determination based mostly on AI. On a optimistic notice, companies have gotten extra conscious of advantages of supervised studying fashions.
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