Pricing: Case Studies

Deposit Pricing

Problem: A $15 billion bank desired help in understanding how to manage their deposit portfolio.

Solution: Analysis of their current deposit book found an overdependence on CD funding relative to MMDA. We deployed deposit pricing analytics to measure market and customer segment price elasticity as well as develop a more customer demand driven pricing process. Applied elasticity based pricing tools to change the pricing and mix of the deposit portfolio through optimizing internal relative rates between products (CDs and MMDA).

Result: Shifted the mix of CDs down five percentage points in the first year. Generated an additional $6 million in spread income through mix shifts as well as lower funding costs.

Funds Transfer Pricing

Problem: The client had an undifferentiated deposit pricing strategy and wanted to increase volumes and profitability through more focused pricing capabilities.

Solution: The retail practice led the assignment and used precision pricing knowledge and tools to identify maximum volume opportunities for alternative strategies. The risk practice helped to refine the profitability model using funds transfer pricing, operating expenses, and balance sheet strategy tools to develop profitability profiles for alternative strategies. This was accomplished by adjusting funds transfer prices based on customer elasticities, setting appropriate liquidity premia, aligning operating and acquisition costs for each strategy which were all incorporated into a refined pricing model.

Result: The client has new tools to optimize pricing and volumes aligned with strategies that will improve the return to the bottom line.

Home Equity Loan Pricing

Problem: The client had undifferentiated home equity pricing and was looking to improve total revenue without making significant investment in new footprint.

Solution: Novantas conducted a review of risk measures and performance metrics. From there, we developed a number of tools to measure and manage pricing, including a risk-adjusted hurdle rate, risk-based pricing “floors,” and an elasticity model that established customer elasticity responses relative to competitive market prices. This information was used to establish target prices for each cell to optimize total revenue and return across the portfolio. Finally, we developed an approach to operational execution of the pricing grid; supported the client in pilot phase and through the roll-out phase.

Result: This established new tools and capabilities for ongoing management of competitive pricing. In addition, client realized significant gain in overall portfolio revenue and risk-adjusted profitability through increased volume, improved spread revenue and improved customer pull-through.