Why This Article Matters The CIO’s mandate in banking has not just become harder – it has become structurally different. In the digital-first era, success was measured by whether systems functioned. In the AI-first era, the CIO is accountable for whether... View
Why This Article Matters Generative AI is not a more capable version of traditional AI. It is a different risk class – and the governance frameworks most institutions have built for traditional AI are not designed for it. This article makes the critical... View
Why This Article Matters The AI banking solutions market has a structural problem that no one is naming clearly: solutions are evaluated on the dimensions where they are all strong, and purchased on terms that do not predict the dimension that actually matters –... View
Why This Article Matters Core banking modernisation is not a new challenge. What is new is the standard that AI-first operations require it to meet – and the consequence of meeting that standard partially rather than fully. This article makes the insight that... View
Why This Article Matters Compliance is not simply another domain where AI creates opportunity and risk in equal measure. It is the domain where the quality of every other AI trust decision the institution has made – in data governance, model design, system... 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 […]