Banks need to manage their interest expenses carefully. When interest rates rise, the stakes get much higher. But those rate decisions also have a big impact on customer behavior—from where they will invest, what they will buy, and whether they will remain customers at all.
With the likelihood of interest rates rising and concerns about the quality of current pricing models, this large U.S. bank was determined to move to a customer-centric, data-driven solution. If they were to use advanced analytics to predict how rate pricing changes would affect customer behavior, they could price deposit products to optimize revenue.
Better deposit rate decisions would depend on a significant improvement in advanced data analytics from their current models. Bank leaders knew that KPMG had the very specific combination of banking industry knowledge, system implementation experience, advanced data science capability, and regulatory skills to deliver true customer-centric pricing optimization.
KPMG's predictive analytical solution allows for real-time modeling of rates, supported by what-if scenarios and agile responses to specific customer circumstances and market growth targets.
Six months after pilot rollout, the portfolio experienced a 3-basis-point reduction in net interest expense equating to a 20% improvement on interest expense, allowing the bank to pay off its deployment in less than a year. Although the initial focus was on reduced interest expense, share of wallet and customer balance grew, while deposit balance attrition declined.
The sales team was enthusiastic because the pricing logic was easy to explain to clients. For the first time, branch associates could move beyond the gimmick of promotional rates to a sustainable relationship pricing solution, a deeper understanding of the customer as individuals, and confident cross-selling.
KPMG recognized it was theoretically possible to use analytics to predict deposit customer behavior down to the individual level, even though no one else had successfully managed it in this context. Building the first truly end-to-end predictive analytics and pricing optimization solution, KPMG needed to put the platform into the hands of the sales force who were actually interacting with customers.
The ideal approach would combine the complexity of advanced analytics with the ease and simplicity of execution, as the value would ultimately be manifested in a deeper, more productive interaction between bankers and customers.
KPMG worked to develop a dynamic relationship pricing solution based on a deep understanding of “who the customer is today” and “who they will become tomorrow.” Together, a platform for pricing deposit accounts at the most granular level was built and implemented, and it immediately delivered significant business value based on deeper, insight-driven relationships.
KPMG’s automated, closed-loop pricing optimization solution breaks the paradigm of simply pricing deposits by product, balance tier, and “what competitors are doing”, and instead measures and differentiates customers across a range of behavioral dimensions that impact pricing decisions, from:
Predictive models feed the optimization model, which determines deposit rates from the customer-product level based on the bank’s pricing strategy and growth objective.
Creating the solution was only half the story—rollout involved working closely with the bank’s in-house data analytics team to help them understand and master the solution.
Deposit pricing optimization is a breakthrough in data and analytics that sets a new standard for customer-centric pricing strategy. At a time when organic growth can only be delivered through deeper, strong relationships with customers, banks can now fine-tune their product offerings to deliver against their strategic objectives and drive optimum performance.
Although the solution is highly sophisticated, this is a story about professional collaboration as much as technical virtuosity. On the journey to a successful outcome, mutual respect and shared interest drove progress. When reorganization and personnel changes created uncertainty, KPMG provided strategic support to keep things on track. Sometimes that meant sharing more knowledge and providing training to the client team. At other times it meant working longer, harder, and faster to hit the milestones.
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