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Welcome to Compliance 911, a no-nonsense, cut to the point, style show for today’s busy bank and credit union compliance professionals. With this series of bi-weekly shows our goal is to boil down some of today’s hottest regulatory compliance topics in quick and easy to digest 5-10 minute episodes so you can get the information you want and get on with your day. We’ll be discussing topics like CRA, HMDA, Fair Lending, Anti Money Laundering, and so much more. Don’t forget to subscribe and tell a friend about us! Follow M&M Consulting and GeoDataVision us on LinkedIn to get the latest updates.
Welcome to Compliance 911, a no-nonsense, cut to the point, style show for today’s busy bank and credit union compliance professionals. With this series of bi-weekly shows our goal is to boil down some of today’s hottest regulatory compliance topics in quick and easy to digest 5-10 minute episodes so you can get the information you want and get on with your day. We’ll be discussing topics like CRA, HMDA, Fair Lending, Anti Money Laundering, and so much more. Don’t forget to subscribe and tell a friend about us! Follow M&M Consulting and GeoDataVision us on LinkedIn to get the latest updates.
Episodes

Aug 30, 2023
Artificial Intelligence (AI) and Banking
Aug 30, 2023
Aug 30, 2023
8 min
In this podcast episode, Len Suzio and Dean Stockford discuss the unregulated use of Artificial Intelligence (AI) in the banking industry. Dean brings up how, amidst the focus on fair lending and Unfair, Deceptive, or Abusive Acts or Practices (UDAAP), there have been increasing concerns about potential bias in AI systems. Specifically, red flags have been raised about scoring systems built into the lending process and the potential for inadvertent redlining in marketing systems. Both Len and Dean concur on the importance of understanding and regulating the use of AI in banking systems.
Dean suggests several proactive measures for financial institutions (FIs) in anticipation of regulatory exams. He recommends conducting an enterprise-wide inventory of all AI-utilizing systems and understanding their specific applications, starting with BSA/AML and Fraud departments, followed by Lending/Underwriting, Marketing, and Human Resources. In addition, he urges FIs to conduct fair lending data analyses and risk assessments with specific emphasis on AI in lending/underwriting systems. To conclude, Dean emphasizes the need for management to understand underwriting systems through thorough testing and analysis, and document vendors' explanations and testing results, to gain a comprehensive view of the risk these systems pose to their institutions.
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