Instead of relying solely on customer-initiated interactions, institutions can proactively reach out when the data indicates a key moment – such as a large transfer, a job change or a shift in spending behavior. These tools work quietly in the background, scanning for patterns, and prioritizing and delivering bite-sized, actionable insights directly to frontline employees. Rather than requiring teams to comb through dashboards or reports, AI delivers intelligence directly where it’s needed – empowering bankers to engage proactively and purposefully. No dashboards. No digging. Just timely, actionable insights tailored to each role. Now, banks can identify critical relationship moments before they’re lost – retaining deposits, strengthening loyalty and generating new business without adding staff. Examples in Action ▶ Retention: A high-value client moves a large sum to a competitor. AI detects the transaction and prompts immediate outreach. ▶ Engagement: A shift in direct deposits signals a life transition. Staff receive an alert to check in and support the customer. ▶ Acquisition: A potential advocate is identified based on network or employer data, prompting the launch of a referral playbook. Critical First Step The most important component of all AI systems is the quality and structure of the data itself, and the data model they reference to generate answers and perform human-like tasks. Without a solid data foundation, AI efforts often struggle with fragmented, inconsistent or incomplete data, limiting their effectiveness and scalability. Therefore, the first step is to create a reliable knowledge base to serve as the source of truth. Operating in an environment that requires impeccable accuracy and traceability, community-based financial institutions must prioritize the underlying data model to set themselves up for success. From Analysis to Action Traditional business intelligence platforms often lead to dashboard fatigue – where insights sit unused and underleveraged. New AI tools flip the model, emphasizing decision-making over data review. By focusing only on the signals that matter most and delivering them in a personalized, accessible way, financial institutions free up staff time to focus on relationships, not reporting. Even a few hours saved per employee each week can compound into hundreds of hours redirected to strategic engagement across the organization. But realizing the full value of AI-driven insights requires more than just technology – it takes expert guidance to turn insights into sustained action. Leading service providers extend beyond software delivery to offer strategic partnerships – pairing advanced technology with hands-on guidance and deep industry expertise. Dedicated teams of data engineers and analytics professionals support implementation and long-term success, ensuring institutions can act on AI insights confidently and effectively. A Modern Strategy That Supports the Human Mission Community banks shouldn’t have to choose between digital transformation and human connection. With AI, they can have both. Intelligent systems can augment – not replace – the relationship model, making it possible to deliver the same high-touch service at greater scale. In a world increasingly driven by automation, relationships still win. And with the right AI strategy, they can win at scale. Tracy D. Graham Co-Founder & CEO Aunalytics info@Aunalytics.com Tracy’s focus is on developing and driving product growth at Aunalytics and overseeing company operations and finances. He specializes in investing in, and building, technology and technologyenabled companies. He is currently focused on leveraging analytics and artificial intelligence to help companies evolve via digital transformation. Aunalytics is an associate member of the Indiana Bankers Association. November/December 2025 59
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