Florida Banking July 2024

BANCSERV ENDORSED PARTNER: BHG FINANCIAL

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DATA ANALYTICS: A FOUNDATION OF GROWTH FOR COMMUNITY BANKS

BY MELISSA WHELAN, EVP, INSTITUTIONAL RELATIONSHIPS, BHG FINANCIAL

E very customer account at a community bank tells a story. Each data point, whether it’s a mortgage balance, small business loan, credit card transaction or even a home address, reveals valuable insights into the behaviors and needs of a bank’s clientele. This wellspring of intelligence can provide banks with the opportunity to multiply their revenues and improve the economic health of their communities. Embracing data analytics is a foundational game changer for local banks. Harnessing internal data can enhance customer engagement, improve underwriting decisions, strengthen operational efficiency and boost marketing effectiveness. An integrated approach to data analytics can also increase the competitiveness of community banks relative to larger regional and national counterparts. However, smaller banks may not have the resources to audit and interpret customer data as thoroughly as large banks. Nevertheless, as this article explains, there are several ways smaller banks can harness their customer information without overtaxing operational budgets and staff. The article also highlights examples of how local banks can use their data to effectively segment, retain and grow their current customer base. A complement to personal relationships Before discussing the benefits of conducting data analysis, the article acknowledges that there is no substitute for the personal relationships community banks have with their customers. The banks’ local roots, homegrown insights and first-name familiarity are an irreplaceable competitive advantage relative to larger banks. Still, a deeper analysis of customer data is essential for local banks to thrive in the modern financial ecosystem. Bank boards, CEOs and CIOs who

recognize the practical use of their data and devote the necessary analytical resources can better position their banks and communities for growth. Practical applications of data analytics Data analytics extract insights that can inform decision making, drive product development, identify new markets and deliver a more personalized customer experience. Here are some of the more prevalent use cases. Lending Incorporating data analysis into loan underwriting models can tell community banks more about an applicant’s creditworthiness than FICO and credit scores alone. For example, analyzing behaviors that traditional metrics don’t capture — such as bank deposit history, property ownership and rent and utility payments — often provides clues about the stability of an applicant's financial situation and ability to manage debt. Data of this nature can also supplement or replace traditional measurements of credit risk. This is especially useful when determining the creditworthiness of individuals with short credit histories or who recently moved to the U.S. These borrowers often have weak bureau scores or no scores at all. In fact, about one in 10 U.S. adults have no credit record at the nationwide credit bureaus, according to the Consumer Financial Protection Bureau (CFPB). Another 19 million consumers have too little information to be evaluated by a widely used credit scoring model. 1 In these cases, using alternative data analysis is an indispensable way to evaluate an applicant’s propensity to repay a loan. Fraud and cybersecurity Data analytics play a crucial role in the fight against fraud and cyber intrusions. According to IBM, the

1 Source: ICBA, Artificial Intelligence: Hype vs. Reality and What it Means for Community Banks. https://www.icba.org/newsroom/ blogs/main-street-matters/2023/10/26/artificial-intelligence-hype-vs.-reality- and-what-it-means-for-community-banks 2 Source: IBM, Cost of a Data Breach Report 2023. https://www.ibm.com/reports/data-breach

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