AI’s Future in Banking Preparing for CECL Automation By KATE RANDAZZO Content Marketing Manager, Abrigo AI Assistance for the CECL Calculation Is Moving from Theoretical to Practical For community financial institutions, the conversation around the future of AI in banking is no longer theoretical. Leaders are asking practical questions about how AI helps banks operate more efficiently, where it delivers measurable value and how it can be applied while maintaining transparency and trust. Nowhere is transparency more important than in a community financial institution’s CECL calculation. Strengthening CECL Processes with AI Advances in automation and AI are creating new opportunities for teams to strengthen their CECL processes while maintaining the governance the standard requires. Now that the initial CECL implementation period is behind us, banks and credit unions are entering a new phase of figuring out how to manage their calculations most efficiently. The impact of AI on CECL processes will be most visible through enhancements that make complex processes easier to execute, explain and defend. The Evolving Role of AI in Banking and Why It Matters for CECL Across the industry, AI is helping banks reduce manual effort, improve consistency and find insights more efficiently. In areas like CECL, where accuracy, governance and documentation carry significant weight, these benefits are especially meaningful. Most community financial institutions (CFIs) have already made the foundational CECL decisions: • Which methodologies are appropriate for a portfolio • How reasonable and supportable forecasts should be applied • What governance framework supports consistent qualitative adjustments But making those decisions was only the beginning. Many institutions are discovering that CECL’s real challenge lies in execution. Manual workflows, disconnected systems and spreadsheet-driven processes can limit an institution’s ability to fully leverage the insight CECL is meant to provide. As portfolios grow and regulatory expectations mature, execution becomes the primary challenge. This is where many of the advantages of AI in banking begin to take shape, especially when paired with purpose-built CECL solutions. Using Automation and AI to Strengthen CECL Execution One of the most immediate benefits of AI in banking is its ability to reduce friction in operationally intensive processes. When it comes to CECL, automation streamlines data ingestion, accelerates calculations and standardizes workflows across portfolios and reporting periods. These capabilities help support more reliable reporting cycles and enable teams to manage documentation requirements more effectively. For decision-makers, this is where AI begins to deliver a tangible return on investment. Faster close cycles, fewer errors and greater confidence in results all contribute to stronger operational outcomes and better use of expert time. CECL teams no longer need to spend excessive time navigating tools or managing workarounds. Instead, they can focus on understanding results and making informed decisions. Platforms that incorporate AI will evolve from calculation engines into end-to-end systems that support analysis, documentation and review — without sacrificing human control or judgment. 8 In Touch
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