such as enabling scale and agility , continuous development and integration to improved models , greater automation and — just as importantly — access to data science resources . The biggest struggle we witness for credit unions is attracting data scientists . SAS ’ philosophy is to become your data science resource through AI services on the cloud .
AT : Innovative technology offers undeniable benefits but also introduces risk . What risks should antifinancial crime ( AFC ) professionals be aware of as they add AI , machine learning and other technologies to their programs and processes ?
JT : There will always be a constant push and pull between the need for compliance to minimize the effect of money laundering and financial fraud and the desire of an FI to become more mature digitally . One of the biggest risks with new technology is that improper controls are put in place before the technology is fully understood and adequately mature . In addition to strong risk frameworks , ensuring that all stakeholders are engaged in the process ensures the best outcome . With AI and machine learning , you must solve issues of auditability , explainability , governance and risk management of complex AI / machine learning models as they move from development and into production . Further , you are dealing with more and more data ( vast amounts ), and you can only do this successfully with cloud computing power and AI models .
AT : In his interview , Hood also discussed how incorporating cryptocurrencies into anti-money laundering ( AML ) programs was an emerging area for credit unions . What is your take on FIs adapting their AML programs to include crypto and what risks do incorporating crypto into AML programs pose for FIs ?
JT : Crypto is moving through your institution whether you know it or not , and soon , regulators will not tolerate institutions that do not know their level of crypto exposure . Although most institutions are going to follow the lead of regulators , it would be much more prudent to get ahead of regulators by knowing your exposure . Once the exposure is known , risk measures can be established by the bank and automated controls can be instituted using technology .
To do this , most institutions will have to partner closely with third-party data vendors that focus on blockchain analysis and can help you undertake such complex crypto use cases . Moreover , as the regulations evolve , stronger ID verification and know your customer practices will reduce the potential for crypto fraud . There is a lot happening here and a lot of unknowns , but I believe the better prepared you are , the easier it will be to manage the complexity of crypto fraud once obligations are published .
AT : Hood also spoke about the value of partnerships — between banks and credit unions — in combating financial crime . How important are partnerships — either public-private partnerships ( PPPs ) or between FIs — in the fight against financial crime ?
JT : PPPs have always been an emphasis within the industry ; however , a formalized feedback loop on and the sharing of risk typologies has been a challenge in the compliance space . The industry needs more robust industry utilities that allow for cooperation and broader data-sharing to be underpinned by strong analytical functions .
The Anti-Money Laundering Act of 2020 calls for greater innovation and sharing utility for AML , but it has not been codified into tangible actions . Perhaps both the Financial Crimes Enforcement Network ( corporate registry ) and the regulators need to kickstart sharing and collaboration , including resource-sharing for smaller institutions . This will also help to solve the scarcity of data scientists in an institution ’ s fraud and AML groups .
AT : The growth in fraud in recent years , particularly since the COVID-19 pandemic , is top of mind for AFC professionals . What types of fraud do you see as prevalent lately and what steps should FIs take to better detect and combat fraud in general ?
JT : Institutions are being hammered by scams , automated bots , synthetic identities , instant payments fraud , a resurgence of check fraud , wire fraud , application fraud and mule activity while being pressured by new regulatory demands to take increased action to better protect customers . This calls for a holistic view of bad actors rather than a myopic view from fraud , AML and cybersecurity silos . There is a desire to integrate fraud , AML and cybersecurity to be able to unlock more benefits from investments made across all parts of the organization . But the obstacles , particularly for larger institutions , are great . These domains are typically siloed functions with discrete and often very different performance goals and inertia / apathy associated with legacy technology implementations . But the benefits are real . You will find common risks across the three divisions which are not addressed adequately in the individual silos . You will also realize substantial benefits from shared infrastructure , technology , costs and resources . And , of course , shared data provides a much more holistic view of how bad actors operate .
Interviewed by : ACAMS Today editorial , ACAMS , editor @ acams . org
ACAMS Today September – November 2023 101