Every member of community bank leadership is searching for an AI use case in banking worth bringing to the board, but most folks don’t know what’s real and what’s just buzz. Especially in lending. There’s a lot of noise about automation and personalization, but very little about what actually helps
Lisa Pent
45 posts
AI in financial institutions isn’t some far-off fantasy cooked up by Silicon Valley. It’s already shaping how money moves, how risk is managed, and how decisions get made, quietly and behind the scenes. For CFOs in community banks, that shift is no longer optional. Budgets are tight, regulations are brutal,
The way banks use AI isn’t about robots taking over jobs or fancy buzzwords on a PowerPoint slide. It’s about real stuff: handling fraud faster, serving customers better, and keeping up with expectations that just won’t sit still. AI solutions for banks aren’t some shiny thing for tomorrow they’re the
Corporate treasury used to be a backstage crew role, quietly keeping liquidity flowing and making sure the business could fund its plans. But the rise of AI in banking and finance has dragged treasury into the spotlight, especially when it comes to risk. Suddenly, board members are expected to understand
Banks using AI used to sound like a tech conference buzzword or a wild prediction someone made back in 2010 while sipping stale coffee in a boardroom. Now, it’s plain reality. Small and midsize banks, not just the giants, are leaning into it. But here’s the thing: the benefits they’re
AI is picking up speed inside banks, but governance isn’t keeping pace. That’s the tension Lisa Pent is tackling at the IBANYS Regulatory Compliance Update on February 3rd. Banks are trying to push forward with smarter tools and automation, while examiners are asking sharper questions about ownership, oversight, and monitoring.
In 2026, AI automation options for community banks won’t just be tools on a wishlist, they’ll be the lifelines leaders use to cut through legacy red tape and customer service lags that have haunted the industry for years. From tired back-office workflows to the constant pressure to speed up digital
Banking and AI are crashing into each other like rush hour in downtown Atlanta, where everyone’s in motion but few know which lane actually gets you there. Everyone’s talking about transformation, automation, and data-powered decision-making, but behind the scenes, way too many plans stall out before they hit production. That’s
Credit unions are showing rising interest in AI, yet many assume they need fully consolidated data or advanced analytics environments before they can begin. In practice, the earliest wins come from internal workflows that require far less data than expected. Leaders see how AI can strengthen lending review, enhance operational
AI Execution in Mid-Tier Banking is reshaping how regional institutions strengthen workflows, improve decisions, and advance their operational capabilities. Banks in the $10 billion to $250 billion range are already moving through modernization. Many have active AI initiatives in lending efficiency, fraud detection, document intelligence, and operational review. Leaders understand
Old banking cores weren’t built for AI in banking. They weren’t built for real-time anything, honestly. And yet, they’re still the default under the hood of thousands of banks trying to keep up in 2026. The result? Slow rollouts, patchwork integrations, and a whole lot of duct tape holding together
The Sept 25th Adirondack TechTalk event didn’t feel like a typical meetup. It happened in the heart of Saranac Lake, where autumn hits early, the Wi-Fi gets moody, and the entrepreneurs are as gritty as they are curious. People showed up because they needed something that’s rare in rural tech