If you think your institution is not utilizing artificial intelligence (AI), you’re very likely to be mistaken. In its simplest form, your employees are likely using ChatGPT to draft memos or emails. The reality is that AI-based technology has infiltrated the banking industry for years now. Every BSA transaction-monitoring software utilizes AI in some form. So do many credit underwriting and marketing systems. Are you aware the extent of your institution’s use of these technologies? Have you identified the risks? How about where these processes are going in the future?
There has been quite a lot in the news lately regarding the use of models, algorithms, AI, and evolving technologies in the banking industry. But there is more to it than just AI – financial institutions are increasingly using and so-called “big data” or “nontraditional data” in their operations. This is information that not traditionally considered financial in nature – it could be information from a consumer’s social media profile, web surfing habits, and more. And this information is available from an increasing number of third parties. The benefits are obvious – more effective marketing, more efficient underwriting of credit, and just an overall sense of better knowing the customer.
But there are two sides to every coin; there are significant risks to using AI and nontraditional data when dealing with customers and prospects. The regulatory agencies (as well as Congress and the Administration) are keenly focused on these risks, and are looking very carefully at what the industry is doing. We have fintechs to thank for many of these advancements, but they are not regulated the same way as traditional banks, thrifts, and credit unions, so usage of these exciting tools and strategies must monitored carefully.
In this webinar we’ll discuss these concerns and risks, so that you can properly monitor and establish controls for these technologies so you can best manage regulatory expectations as you su