UNDERSTANDING AUTO LOAN ORIGINATION DATA TO DRIVE BETTER BUSINESS INSIGHTS

The Federal Reserve Bank of St. Louis recently noted that the consumer price index (CPI) for both new and used vehicles, along with the cost of financing these vehicles, rose sharply in 2022. In fact, this key indicator of inflation reached its highest level in this category since 1953, when the Federal Reserve started tracking such costs. A big factor in this involved the average rate paid for auto loans over a 60-month period, which rose to 5.5 percent from 4.85 percent, a rate not seen for auto loans since 2011. According to Experian, for the third quarter of 2022, average auto loan payments jumped by 13.3 percent for new vehicles, 11.2 percent for used vehicles, and 12.1 percent for vehicle leases, putting average payments respectively at $700, $525, and $567 per month. Add to this the average loan amounts from September 2022 of $40,156 for new vehicles and $24,997 for used vehicles (up from $19,008 prior to the pandemic), and buying a car is at its costliest in nearly three-quarters of a decade.

Auto balances look set to surpass student loans by mid-2023 overall as the largest debt held by US consumers after mortgages, according to the Consumer Financial Protection Bureau (CFPB). As such, being able to interpret auto loan origination data has never been more important. Yet, and apparently counterintuitively, auto loan delinquency rates continue to drop, according to the New York Federal Reserve Bank. Currently, 3.9 percent of auto loan payments are 90 days overdue, compared to 5.3 percent in 2010, while payments on another 6.2 percent are 30 days late, which was 10.9 percent in 2009. While these lower numbers may be partly due to stricter guidelines after the Great Recession, increased analytics technology adoption has lent a helping hand. When coupled with analytics technology, origination data creates detailed insights that allow lenders to understand better why certain events occur, such as delinquent accounts or loan defaults. 

What’s So Important About Auto Loan Origination Data?

Modern analytical software that’s integrated into a loan origination system (LOS) offers lenders capabilities to evaluate a whole host of auto loan origination data. Lenders can analyze the performance of loan portfolios, certain categories of loans, and just about any sort of data derived from auto loans. Origination data can even be collated into easily understood reports that help lenders track trends within the auto loan market.

Using auto loan origination data, lenders can:

• Categorize which auto loans must follow Servicemembers Civil Relief Act (SCRA) regulations.
• Determine delinquency rates of various dealerships from which loans originate.
• Discover the proportion of overridden loans that have defaulted over a specific period of time.
• Identify delinquency rate trends that help determine credit policies or borrower traits that contribute to delinquencies.
• Provide insights on loan distribution based on age, dealer, loan type, vehicle make and model, or other factors within assorted portfolio segments.
• Reveal which underwriting override decisions show the best judgment.
• Show when subprime auto loan interest rates could violate state usury laws.
• Unveil applicant characteristics of those purchasing certain makes or models of vehicles.

By carefully analyzing their loan portfolios, lenders can better determine their performance and where they can be improved. Without utilizing data-driven insights, it’s difficult to find the underlying reasons why certain segments within a lender’s portfolio underperform.

The CFPB & Auto Loan Origination Data

Lenders may soon be able to access more than just their own auto loan origination data as the CFPB seeks to create new datasets that will better reveal market trends. This will enhance data analytics capabilities, especially when it comes to those with subprime credit scores, as many lenders don’t provide data to credit reporting agencies on such loans. This will offer lenders a more holistic view of the auto loan market, with access to more robust origination data affording greater transparency.

Providing lenders with auto loan origination data through such datasets will enable all stakeholders to glean better insights. This will not only support a more competitive auto market but will also allow lenders to improve risk management, identify new loan opportunities, and expand credit access. Currently, the auto lending industry lacks reliable information on loan delinquencies and how they relate to repossessions, including their impact on both borrowers and lenders. With the provision of more consistent auto loan origination data, lenders will be better able to correlate how credit scores, income, and geography affect delinquencies.

Tools for Analyzing & Understanding Auto Loan Origination Data

Analytics tools give lenders the means to wade through and leverage data that helps them understand trends and make better-informed decisions. To promote growth, lenders need to be able to offer competitive rates and terms. Yet much of the availability for portfolio growth lies in underserved communities and population groups, often involving people with low or no traditional credit scores. However, many potential borrowers without conventional credit histories may offer lenders less credit risk than those with good credit ratings. By developing robust analytics capabilities, lenders can expand the type of borrowers who they can approve for an auto loan. Origination data paired with analytics allows auto lenders to target those who are most likely to, and most capable of, paying off a loan.

Creating Insights With Auto Loan Origination Data Analytics

Financial analytics for auto loans used to be the sole domain of highly educated experts with an understanding of both statistics and the finance industry. To sift through large amounts of lending data, analysts were sometimes required to use Structured Query Language (SQL) to interpret data and maneuver through databases. With such expertise, analysts could reveal hidden patterns in the data, discovering developing trends and opportunities in the process. Often, such highly trained individuals were only affordable by big banks and other large lenders Today’s data analytics software allows small and medium-sized (SME) lenders the ability to access and glean insights from data more affordably through enhanced insights of data from auto loans. Loan origination processes benefit from modern analytics software, which allows lenders to analyze large amounts of data inexpensively, allowing them to compete with larger lenders. Much of this analytics software is available through subscriptions via cloud-based software-as-a-service (SaaS) providers. Regardless of size, it’s more important than ever for lenders to invest in analytics, a key digital tool that enables lenders to add value to their portfolios without increasing risk.