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 lower- quality 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 more high-risk customers. To increase share 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
Drive 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
- NPV-based breakeven margin for each transaction: This metric informs analysts that pricing below this level means loss 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 metrics
Range of different optimization scenarios to show the tradeoff between different options by evaluating different optimization objective functions
Database of quoted prices, rates and loan portfolio
Quarterly profitability analysis