TLDR: Generative AI is transforming how financial institutions develop and implement deposit pricing strategies, drastically reducing the time from analysis to market action. This allows banks to respond to market changes and secure deposits more efficiently, gaining a significant competitive edge.
Financial institutions are on the cusp of a major shift in their deposit pricing strategies, thanks to the advent of generative artificial intelligence (AI). New tools powered by generative AI are poised to accelerate the implementation of fresh deposit strategies from weeks down to mere hours, providing banks with a substantial competitive advantage in a dynamic market.
Historically, deposit pricing has evolved from relying on competitive surveys and intuition to sophisticated optimization models. These models leverage extensive industry-wide and market-segmented data, along with advanced analytics. Current platforms enable financial institutions to identify opportunities for margin improvement and quantify the impact of pricing decisions on new deposit growth, customer retention, and acquisition. This is achieved through constrained optimization modeling of pricing elasticity and marginal cost of funds, utilizing advanced machine learning to capture variations across products, geographic regions, and customer segments, which then rolls up to overall portfolio performance.
Evidence from the rising rate environment that began in March 2022 demonstrates the effectiveness of such optimization. Banks that adopted these methods saw greater deposit growth compared to their peers, expanding their cost advantage to 15 basis points by the second quarter of 2023.
However, a significant limitation of the current state-of-the-art is the ‘time to action.’ This bottleneck arises from inefficiencies and accessibility issues, as pricing analytics teams typically run numerous scenario models that require extensive further analysis and distillation before being presented to decision-makers, such as the head of retail, for implementation.
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Generative AI addresses this critical gap. When applied to deposit-optimizing technology, generative AI can dramatically speed up decision-making and time to market for deposit pricing refinements. It reduces the effort needed to interpret complex results and presents findings in clear, straightforward language, supported by data assets that virtually any responsible party within the organization can act upon. This enhanced accessibility means that the results of scenario-based queries can be delivered to a decision-making audience within hours, rather than weeks. This timely action is crucial, enabling banks to ‘garner deposits when they’re needed at favorable costs, leaving competitors in the dust.’ The output from AI can be ‘executive- and execution-ready,’ streamlining the entire process from analysis to market deployment.
