SBIR-STTR Award

This Small Business Innovation Research (SBIR) Phase I project seeks to develop a software product that will optimize sweep regimens in retail banks. The purpose is to demonstrate feasibility of a decision-support system that uses past customer behavior, qualitative input from managers and stochastic optimization to improve bank sweeps. Sweep programs were initiated in 1994. The current cumulative revenue from sweeps have reached approximately $700B. Still, sweep technology has been out of reach for small to medium size banks due to complexity of the heuristic models. The goal of this project is to bring a product to market which will allow small to medium size banks to engage in regular sweep transactions thus enabling more efficient use of resources and higher yields for the bank's customers.

This Small Business Innovation Research (SBIR) Phase II project will advance the scale up and validation of a tool which enables small and medium-sized banks to optimize their "sweep" programs for managing their deposit balances. To date, most optimizations are based on heuristics and are out reach for small to medium sized institutions. The approach of the proposed effort, which will be embodied in a cost-effective software application, deploys a proprietary algorithm based on analytics and stochastic optimization. It should provide a 15-25% improvement over the current heuristics effort and be affordable for small to medium sized banks. If successfully commercialized, the proposed solution will enable more efficient deposit optimization in small to medium-sized banks; addressing an approximately $150M market opportunity. The solution also has the chance to enhance cash management at branches, vault cash/ATM networks and other cash logistics operations. Further, improved modeling of customer behavior has potential applications for customer relationship management in all financial services including credit cards, insurance, brokerage services and e-commerce in general.