The world of work, accelerated by the pandemic, is set for a monumental transition. McKinsey predicts that 14% of the global workforce may have to switch occupational categories as digitization, automation, and advances in AI are disrupting the world of work. By 2030,... View
Financial institutions use data and predictive analytics to improve customer experience and amplify business success. Today, banks want more than incremental gains. They want data-driven revenue breakthroughs. Banks increasingly rely on data. It’s the future of... View
Post-pandemic employment choices proliferate with a higher acceptance of hybrid work models, especially in the technology sector. Add to it the novelty of Metaverse that brings experiments in employee experience and employer empathy. Just as digitization and social... View
Regulatory compliance aims to ensure the bank operates within regulation, safeguarding its integrity and industry reputation. The function oversees multiple duties: protecting bank data, avoiding government fines, avoiding tax evasion, monitoring and reporting... View
Corporate banks can establish a successful digital strategy by following digital business rules: digital experience, operations, innovation, and ecosystems. Enterprise clients want improved service and innovation. Corporate banks that value real-time analytics and... 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 […]