Compounding high costs of bad data are the opportunity losses banks risk with slow efforts to scale their Data Analytics function. Not as a set of discrete projects, data analytics must evolve into an actual business discipline. The imperatives to do so are the twin... View
In the recent times, microservice architecture, or simply microservices, has become quite popular. To put it into simple terms, microservices is a characteristic method of developing software systems and applications as a suite of independently deployable, small,... View
AI pilot count has become one of banking’s least useful measures of progress. A regional bank can have experiments running across customer service, fraud, compliance, lending and engineering and still have very little AI producing value in live operations. For a large global institution, a broad experimentation portfolio can be absorbed across substantial innovation, data […]
A banking AI use case can make perfect sense on a presentation slide and still be the wrong initiative to put into production. The economics may be attractive. The model may perform well. The executive sponsor may be committed. None of those answers the harder question: can the bank operate it reliably inside a live […]
The AI problem inside many regional banks is no longer a shortage of ideas. It is a shortage of capacity to pursue all of them well. Fraud, KYC, lending, Customer service, Compliance, Software Engineering, Data Operations, and Cybersecurity can all produce credible AI use cases. But every initiative competes for the same finite pool of […]