Predictive Risk Analytics Can Save Lenders in Troubling Times
In light of increasing defaults and foreclosures, a new Deloitte & Touche USA LLP report recommends mortgage lenders pay special attention to collection operations based on predictive risk analytics technology strategies "which would enable them to manage the current economic situation and prepare for the troubling times that lie ahead."
The Deloitte capital markets group report analyzed current default and risk in the subprime market on "how adopting a risk-based collections operation can increase efficiency and drive profits" and states these operations are much more important now than they were just one year ago.
According to Deloitte, the proven tools and techniques studied were designed to help organizations reduce the cost of collections by 30%, reduce collection call volumes by 35%-40% and reduce the number of accounts 30 to 60 days past due by 25%.
The report notes benefits of implementing a risk-based collections operation overweigh costs. It suggests investments needed for a risk-based collections operation only require a 12-month payback period.
The subprime mortgage lending industry is a challenging marketplace that can benefit from more cost-efficient collections operations that use highly accurate risk-assessment tools, lower cost, increase amounts of funds collected, secure better reporting capabilities and overall efficiency that makes a lender more competitive.
As of now, the survey found institutions usually focus on the lending process and how to increase origination volume, rather than monitoring the entire lifecycle of the loan. Only 23% of the surveyed executives think "there is a close, cooperative working relationship between credit and collections at their institutions." And only 36% of the survey participants use predictive analysis in managing collections.
The report states, "The investor's focus has shifted to collections and defaults and institutions that are able to weather the current market situation, and should have appropriate collection operations that maximize their processes, technology and resources beyond their basic capabilities."
Deloitte recommendations are especially valuable to lenders under pressure by investors who often show "unwillingness to wait for loans to default before taking action" and are forcing liquidity-challenged lenders to buy back defaulted loans.
The report calls on institutions to make greater use of statistically sound and empirically derived predictive tools that, for example, use behavioral scoring models that use past customer payment habits to predict future default risk. Changes in the structure of collection operations so customer evaluation is grouped by risk level (high, medium or low) as compared to payment days past due ensure more accurate evaluations.
Also, automation of the collections workflow, using the same processes with various collectors along with accurate metrics when measuring collections performance, makes for a more efficient evaluation.
Finally, lenders need to build technology infrastructure that includes decision engines, data mining tools, workflow management tools, predictive dialers and enhanced portfolio management dashboards.
The report stresses that given the current state of the industry and economy, "it is even more important" for companies operating in the subprime mortgage industry to adopt this newly emerging collections model.
As to current delinquency and foreclosure marketplace challenges, the report highlights the following data:
* In recent months there has been a significant increase in the number of subprime loans that are defaulting within the first six months.
* Since 2002, the foreclosure rate has doubled to 20%, according to a Center for Responsible Lending study released in December 2006.
* One in every five loans originated to a subprime customer in the last two years is expected to go into foreclosure.
* Subprime loans made in 2006 are defaulting at a 50% rate faster than loans originated in 2005, a UBS report found.
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