The banking industry is at an inflection point. Core systems that once powered growth are now holding innovation back. As banks race to deliver hyper-personalized experiences, ensure compliance, and modernize legacy platforms, AI in core banking modernization has... View
Walk into a gathering of senior executives today and you’re unlikely to miss a mention of Artificial Intelligence (AI). Business leaders across industries are grappling with AI’s immense potential to transform processes, enhance decision-making, and improve customer... View
In 2025, the financial sector faced unprecedented volatility and disruption. Banks are challenged by accelerating digital adoption, competitive new entrants, pervasive compliance obligations, and mounting customer expectations for speed, security, and personalization.... View
Why Trust is Central When we talk about AI in banking, most of the conversation revolves around economics and ROI. In my first article, I proposed a bold idea: New England’s community banks pooling resources into a Shared AI Exchange to level the playing field against... View
Why Economics Matter When I first floated the idea of a Shared AI Exchange for New England’s community banks, two reactions came up immediately: “Sounds great, but who’s paying for it?” “What about security, controls, and governance?” Both are valid concerns. I’ll... View
Regional banks are not behind on AI in software delivery. They are ahead. The real question is whether test automation moved with them. Most bank technology leaders have this backwards. The assumption, understandably, is that regional banks and credit unions are playing catch-up on AI, that megabanks with larger technology budgets are further along. The […]
Development moved faster this year. Most quality engineering functions did not move with it. Here is how to tell if yours is one of them. Ask most CIOs, CTOs, and Heads of Engineering at regional and challenger banks whether their development teams got faster this year, and the answer comes quickly: yes, obviously. Ask the […]
Banks increasingly consume AI through vendor APIs, SaaS platforms, cloud services, and embedded features. Proprietary architecture can limit visibility, but it does not transfer accountability. SR 26-2 states that model risk principles remain applicable to vendor products and calls for institution-specific understanding, validation, monitoring, and outcome analysis. A vendor model card is an input to […]