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When to Pull Back or Pause Originations

Written by Andrew MacDowell, Director, DecisivEdge™

Every once in a while I hear or read about auto lenders pulling back on or pausing originations to make small or large adjustments to things such as improving credit underwriting procedures, ensuring compliance with new regulations, or selecting and implementing auto-decisioning software.  Although it’s a painstaking decision, I applaud leaders in finance companies who have the foresight to plug the holes in the bucket.

A little while back, I read Crediauto USA Financial restarted originations after a one year hiatus.  Earlier this year, Pelican Auto Finance halted originations and transferred 95% of its portfolio to Westlake Portfolio Management, LLC.  Furthermore, according to S&P Global Ratings, Flagship Credit Auto Trust announced at the end of 2017, “it reduced its managed portfolio by 8.5% citing the increase in losses was driven by the prior year originations that are now approaching their peak loss period.”   

With interest rates on the rise, higher costs of funds, and 60+ day delinquency rates on the rise in certain segments, I am sure other auto lenders are a little nervous about their portfolios.

This blog post will explore three areas you might want to consider making adjustments to in your business as you contemplate pulling back on or stopping originations for the time being.  All three are tied to the loan/lease origination process.

First, let’s start with risk-based pricing: Do lenders need to employ risk-based pricing strategies to loans they are approving?  I think the answer is “YES.” Here’s why; risk-based pricing is a strategy lenders use to determine customer risk before assigning interest rates on their loan.  If a loan application comes in with a previous bankruptcy, low fico scores, and a spotty history of employment, a lender should apply a higher interest rate on the loan. Risk-based pricing lets the lender grant loans they might not otherwise approve and charge a higher interest rate to hedge against the potential increase in delinquency rates and potential losses associated with approving such loans.  Just like automated decisioning, risk-based pricing models pre-configured in origination software can help lenders accurately and consistently apply equations to loans that need higher interest rates attached to them.

Second, let’s talk about concerns with dealer compliance as it relates to indirect auto finance transactions:  Not only is the CFPB cracking down on unfair auto lending practices, but state agencies are as well.  For example, the New York Department of Financial Services recently published a press release urging auto lenders to closely monitor, audit, and take action when they see potential unfair dealer lending policies and procedures such as eliminating dealer discretion to markup interest rates by using a different method of dealer compensation. The announcement goes on to say, “The lender should take prompt corrective action if it finds any differences in interest rates that are unexplained by objective credit factors, such as restricting or eliminating a dealer’s ability to mark up, terminating the lender’s relationship with a dealer, and providing restitution to affected consumers.”

Auto Lenders are easy targets for auditors and various Federal and State agencies.  Well documented policies, timely audits to ensure policy adherence, quick and easy reporting, and integrated software will help you determine if originations need to slow down or cease with partner dealers.  

Third, let’s explore automated decisioning:  Is auto-decisioning a “nice to have” or a “need to have?”  If you are just starting out, auto-decisioning loans is a “nice to have.”  If you are processing thousands of loans per month, auto-decisioning tools in place are a “need to have.”  Why?  At some point even some of the most organized leaders and managers become overwhelmed with the many manual processes that are involved in making the right credit decision for your customer and for the lending institution.  In other words, there is or will be a degree of human error in play when processing loans “the old fashioned way.” Unless the algorithm or software has a bug that goes undetected, using software to apply the predetermined metrics to make the decision for the lending company makes a lot of sense and removes human error from the equation.  Auto-decisioning loans also lets you gather consistent data to mine and employ data scientists to make recommendations on the health of your portfolio using scoring methods against long-term performance of loans.

Expertise in both financial services and data science can be leveraged to help optimize credit decisioning and help you weigh the tough decision to slow down or pause originations for a certain period of time while you make the right business adjustments to improve the overall health of your loan/lease portfolio.

I hope you found this post useful and if you have questions or would like to talk about our lending and leasing services and solutions, please feel free to reach out to me directly at andrew.macdowell@decisivedge.com.

About the Author:

Andrew MacDowell has over two decades of senior management experience in the credit card industry with Fortune 500 financial institutions such as MBNA Corporation and Bank of America.

Andrew has specific expertise in areas such as Business Development, Loyalty Marketing, Corporate Project Management, Bank Operations, Payments, and Fraud. Most notably, Andrew was a key founding stakeholder of MBNA Canada during its peak growth phase in the Canadian marketplace, which ultimately led to it becoming the largest MasterCard issuing bank in Canada.

Andrew is the product owner of Lending and Leasing as a Service (LLaaS), a DecisivEdge software solution built for small to medium sized lenders.

Andrew is a graduate of Georgian College where he holds a diploma in Business Administration and majored in Marketing Management.