“The goal is a radically different model of banking, characterized by highly personalized customer engagement, hyper-responsive product management, and structurally transformed operations. The performance profile could be dramatically different from today’s banking model, aspiring to 10 times greater productivity, 100 times more experimentation throughput, 90% shorter time to market, and a 10-percentage-point improvement in the cost-to-income ratio.
The strategic prize does not center on efficiency. Rather, it involves velocity in time to market and experimentation. Faster trumps slimmer.
Most institutions can envision these performance goals but remain constrained by legacy estates, skills shortages, inadequate data foundations, capital allocation pressures, talent, and operating model. And institutions that treat AI as a set of tools layered onto existing operations will underinvest in the changes that create enduring advantage.
Banks that currently capture the most value from AI treat it as a lever for growth. An AI-native modern bank requires investment and enduring commitment across five elements:”