Case Study: LEVERAGING AGGREGATED DATA AND ANALYTICS FOR FASTER DECISIONING AND REDUCED COSTS
A $2 billion independent bank achieves a 20% increase in predictive lift and a 37% increase in “hit rate” in its equipment finance lending business.
When it comes to equipment financing and small business lending, more and more borrowers are expecting a faster, more efficient underwriting process coupled with the highest levels of customer service. When our client — a $2 billion independent Midwest bank specializing in nationwide small business lending and equipment financing — underwent leadership changes, we consulted with their new credit and risk executives on how to use external data and scores to achieve their
revised underwriting goals.
We started with the bank’s equipment finance lending business. At the time, an army of forty
analysts were manually underwriting up to 3,000 transactions per month. The process was labor intensive, costly, and slow. Their goal: faster and more consistent decisioning and increased efficiencies. We recommended an automated, score-based underwriting process.
Merging Three Separate Credit Scores into One
First, we evaluated the bank’s current process for assessing risk. At the time, they were making Pass/Fail decisions manually based on three separate scores — PayNet MasterScore® v2, a consumer FICO score, and a commercial trade score — each with different hit rates ranging from
64–75%. Their risk assessment process was inconsistent and was not optimized for accuracy, efficiency or speed.
To achieve maximum predictive lift and hit rate, we conducted a retro analysis using the bank’s portfolio data which combined three individual scores into one aggregated “score of scores” called the PASS™ advanced score model. As part of this analysis, we took their existing consumer score files for the past five years and appended the PayNet MasterScore® v2 and the Equifax Commercial Insight Delinquency Score (CIDS), our commercial trade reporting score. The purpose of the analysis was to show how each score worked individually versus combined. The results of the analysis were remarkable. By using our aggregate PASS™ scoring model, the bank was able to achieve the following.
- A 97% combined hit rate (versus 64–75%)
- A 20% increase in predictive lift
Ensuring Results with Risk Consulting
Based on this comprehensive score analysis, the bank implemented the new PASS blended score model immediately and decided to use it on every equipment finance lending transaction. Now, the bank is auto-scoring each transaction and using the PASS Model for both auto-approving and auto-declining transactions. Unlike the previous manual process, the bank now only manually reviews those borrowers with higher risk levels that require additional analysis.
As part of the Score Implementation process, our Scoring Team meets weekly with our client to provide “best practices” advice and further refine the underwriting process with the purpose of achieving specified goals, including:
- Efficiencies — Automating as much of the underwriting process as possible which gives the bank the ability to redeploy analysts to other functions including back-end portfolio management.
- Automation — Assisting the bank by helping to integrate the PASS Model into their front-end system which allows them to make decisions faster with more automated approvals and declines.
- Decreased Costs — Supporting growth with automation instead of headcount which allows the bank to reduce headcount, redeploy resources and reduce expenses.
Elevating and Expanding the Offering for Further Results
Our value to the bank goes far beyond quality data and analytics and showcases our risk consulting capabilities. Our Scoring Team is teaching them how to migrate from manual to automated underwriting and walking them through the entire process, from start to finish.
Once the bank’s new Auto-Scoring process is fully implemented, they plan to expand the strategy to their small business lending and commercial credit card businesses, where they will achieve additional cost savings and efficiency gains.
PASS™ enables lenders to improve efficiency and decision strategies with a single, blended score with higher hit rates and greater predictive lift.
MasterScore® v2 allows lenders to automate and improve credit decisions while delivering predictive abilities that are superior to trade credit data.
Commercial Insight Delinquency Score (CIDS) predicts the likelihood of a business’s financial trades becoming severely delinquent.
To learn more about automating your underwriting, reach out to firstname.lastname@example.org