If an organization offered the same “average” price to every customer applying for a loan, low-risk customers would secure better rates with other organizations, while high-risk customers would not.
Only the relatively higher-risk customers would select the average product, skewing the population down, increasing average losses, and reducing profitability. The combined effect of average pricing is twofold: fewer low-risk customers and additional high-risk customers. To increase share value and stay competitive in a tight market, banks require a strong analytical foundation comprised of business intelligence, optimized pricing models, and streamlined execution.
Improved Operational and Financial Management
Driving significant improvement in volume and profit for any position on the efficient frontier by understanding the impact of rate changes on customer behavior and defining pricing strategies accordingly.
Dynamic ability to respond to changing economic and competitive environments.
Support the field with key competitor metrics updated daily to easily track pricing, marketing, and sales campaigns.
Our flexible, collaborative approach helps organizations increase speed to market, enhance business agility, and improve the quality of customers’ experiences.
KEY METRICS & DELIVERABLES
- The NPV-based breakeven margin for each transaction. This metric informs analysts that pricing below this level means losses for the financial institution.
- Other risk-appetite based pricing metrics, including Lifetime Risk-Adjusted Return on Capital, Risk-Adjusted Return on Risk-Weighted Assets, and Economic Value Add.
- Economic profit-based performance metric.
Unconstrained baseline pricing for each segment based on fully customized risk-adjusted performance
A range of different optimization scenarios to show the tradeoff among different options by
evaluating different optimization objective functions.
Database of quoted prices, rates, and loan portfolio.
Quarterly profitability analysis.