Picture this: A major airline’s check-in system crashes for 45 minutes. The result? Over 100 flight cancellations, thousands of stranded passengers, and a staggering $6.5 million in losses. This real-world scenario underscores a stark reality: software failure... View
As data and connectivity continue to reshape industries, the financial services landscape is undergoing a paradigm shift. Gone are the days when consumers were content with fragmented financial information across multiple institutions. Innovations like Open Banking... View
With the foundational understanding of Open Finance laid out in the first part, we now delve into its specific benefits, adoption challenges, and broader implications for the financial services industry. Building on the concepts introduced earlier, Part II provides a... View
The financial services industry is experiencing a transformative period marked by rapid technological advancements. Traditional banks are now confronted with the pressing need to adapt to the swift innovations introduced by fintech companies. While established banks... View
The financial sector is grappling with a formidable adversary: Authorized Push Payment (APP) fraud. This sophisticated financial deception has swiftly become the biggest threat to banks and their customers. Projections indicate that losses from APP fraud could reach... 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 […]