In this case study Sandi Papenfuhs, SVP, Consumer Lending at First Tech Federal Credit Union shares about Using Data Analytics to Manage Lending Complexity while Driving Higher ROA She shares how First Technology Federal Credit Union navigates the intricacies of consumer loan pricing with a comprehensive strategy covering seven channels, 27 product categories, 51 unique products, and 138 pricing plans, resulting in 860 rates reviewed monthly. The pricing model incorporates factors like cost of funds, risk costs, operational costs, and desired profit, critical in a sector where 70-85% of financial institutions' income stems from lending. Missteps in pricing can have severe consequences, leading to loss of volume, revenue, and reputation.

The pricing strategy at First Tech is a blend of art and data analytics, incorporating inputs such as loss predictions and operational costs. A case study on auto loan pricing highlights the complexity involving five channels, 12 regions, and 36 pricing plans, resulting in 432 unique rates. The challenge lies in comparing these rates with competitors who have different programs, but First Tech has devised a proxy model for effective analysis.

Through this comprehensive approach, First Tech achieved significant results, increasing the return on assets on their indirect portfolio by 173% and their direct auto return on assets by 42% in the last 18 months. This success underscores the importance of a well-managed and adaptive pricing strategy in the competitive landscape of consumer loans.