Common suggestions include fraud detection, generating compliance reports, business intelligence reporting (e.g., tracking loan trends) and customer service. But what specific issues does your bank face? Are there other ways to solve these problems? DEVELOP POLICIES FOR THE USE OF AI AT YOUR BANK Are you concerned that your employees already use AI tools to help them with their work? Have you asked them? Have you or your legal team reviewed the terms and conditions of these commercially available tools like ChatGPT? What about the fear of using “poisoned data” or data that has been corrupted or altered in misleading ways? Who owns the data you type into the tools? These are all points that a wellcrafted AI policy should address. What precautions will you take to prevent bad actors from using AI against your bank and customers? What controls can you enact to keep a criminal from impersonating a customer and fooling your AI platform? These are all questions you should consider and address in your policies and procedures before adopting any new AI-based technologies at your bank. CONSIDER USING OUTSIDE EXPERTISE Your community bank likely already faces pressure from larger competitors that presumably have internal experts in AI for financial institutions. You can benefit by leaning on reputable fintechs, including your core processor. They have the resources to test and refine AI software to meet banking requirements, and they understand the business problems you are trying to solve. But beware — there are many startup companies in the marketplace offering AI-powered fintech for banks. With recent interest rate changes, many have or are quickly running out of capital. Exercise good judgment during due diligence. Even then, consider consulting with a company that routinely assesses IT and AI services for its clients. They can help you choose the correct solutions for your bank’s specific issues and, in some cases, help curate the best tool(s) for your bank. THE TROUGH OF DISILLUSIONMENT Gartner, a leading research and advisory firm, has coined the phrase “Gartner Hype Cycle” to represent the social reaction to new technology. The cycle includes the “Technology Trigger,” introducing a new or breakthrough technology, followed by the “Peak of Inflated Expectations.” AI hit peak excitement in Q1 2023. Now AI is in Gartner’s “Trough of Disillusionment,” where a new technology fails to deliver on its early promise. To be sure, the Hype Cycle continues as more people work with and understand this emerging technology, leading to “Mainstream Adoption.” But for now, we don’t want our community banker friends disillusioned over costs, mistakes and disappointment with their plunge into AI. If you follow the measures above, you will be ahead of the curve. Milton has more than 25 years of experience assessing and mitigating risks for regulated organizations. He serves as virtual chief information security officer for several client banks and as an active board member of the InfraGard Middle Tennessee Members Alliance. He also is active in the national InfraGard Cyber Finance Working Group. ImageQuest is an associate member of the Indiana Bankers Association. Milton Bartley Co-Founder, President & CEO ImageQuest info@ImageQuest.com How can AI help your bank? What exactly would AI help you do faster or more accurately? “ JANUARY/FEBRUARY2024 53
RkJQdWJsaXNoZXIy MTg3NDExNQ==