Florida Banking July 2024

Artificial intelligence AI can analyze and synthesize large sets of internal data more quickly than human resources. It can also recognize inconsistencies and identify non-obvious patterns, making it an ideal tool for data-intensive functions such as loan underwriting and fraud mitigation. There are a growing number of open source AI platforms available for lower-resourced banks. Third-party specialists Many smaller banks may not have the technical acumen, employee capacity or adequate time to manage their data analysis needs. It may make sense for these institutions to partner with specialized providers that have the appropriate expertise. This can still be a cost-effective strategy for banks compared to building out the technology infrastructure themselves and training employees in its use. Starting small and other considerations Most experts agree community banks should begin their data analytics journey with small steps. Start slowly and learn from it: what worked, what didn’t, did it achieve the intended result? Let one success lead to another and use those victories to fund larger, future efforts. Along the way, take the time to ponder the following: • Consider hiring a data analyst or data scientist to start reading and analyzing data • Decide whether to keep data analytics in house or outsource it •Consider data aggregation tools that can combine data from different systems • Talk to technology partners about their ability to aggregating and analyze data •Map out current data sources and systems to understand gaps and opportunities • Consider roles like Chief Data Officer or Chief Data Scientist to oversee data strategy and execution. Closing thoughts Community banks have an opportunity to thrive by combining their local expertise and personalized service with data-driven insights and automation. This combination can help a community bank level the playing field against larger competitors while still maintaining its traditional values of personal service and community support. Melissa Whelan is EVP, Institutional Relationships, for BHG Financial. Whelan has been with the company for 18 years, joining in 2006 as a member of the credit team. She later managed the closing department and held other leadership roles within the company, then continued her career in Institutional Sales. Whelan grew up in Syracuse, NY, before moving to Louisiana. She studied exercise physiology from Louisiana State University (LSU), before returning to New York. She enjoys traveling around the country to attend her three children’s sporting events.

average cost of a data breach in 2023 was $4.45 million. 2 Fortunately, today’s advanced analytics like Machine Learning and Artificial Intelligence (AI) can scrutinize data in real time and flag suspicious patterns and irregularities. Banks can leverage these insights to identify questionable transactions and thwart attempts to gain unauthorized system access. Risk management By integrating market, economic and internal customer data, community banks can detect changes to underlying conditions and develop more-timely response strategies. Armed with these insights, banks can address and predict what risk factors may affect such functions as information security, operations and Through data analytics, community banks can attain a more holistic view of their customers. This can lay the groundwork for more relevant marketing messages, enhance acquisition strategies and improve engagement by allowing a bank to personalize its offerings in alignment with customers’ specific needs. Operational efficiency From enhancing a bank’s ability to make faster and more confident loan decisions to automating internal reporting processes, data analytics can help banks lower costs, streamline or replace manual processes and increase revenue. Making operational functions simpler and less time consuming also allows bank employees to devote more personal attention to Community banks can take multiple approaches to analyzing their internal data. They vary in cost and sophistication level and can be conducted internally or by an external third party. Here is a look at several examples: Surveys By posting a simple customer survey on its website, a community bank can receive immediate feedback on what it is doing well, what is not working and how to better serve its customers.“Gathering customer feedback through surveys is an efficient and cost-effective way to identify policies and practices that may need adjustment,” said Meghan Crawford-Hamlin, President, Institutional Division, for BHG Financial. “Surveys can quickly highlight low-hanging fruit for local banks to address.” Open source software “Open source” data analytics provide universal (and often free) access to a product’s design. In banking, the leveraging of open source tools can be an effective way for lower-capitalized banks to launch new products and services quickly and without a significant outlay of capital. There are many popular open source software tools available that offer data analysis applications for banks. compliance, among others. Target marketing and customer segmentation customers and enhance their loyalty. Technologies and techniques

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