Continued Improvement in Loan Performance Anticipated for Non-prime Consumer Segment in Second Half of 2018

As we look ahead to the next half of the year, it is important for auto service providers to understand recent trends among the non-prime consumer segment in order to fine-tune business practices for successful future results.

Background: The industry reaches new heights

From 2010 to 2015, new vehicle sales grew at a compounded annual growth rate of 9 percent, largely due to the pent-up demand following the financial crisis of 2008-2009. During this period, delinquency rates (calculated at 60-plus days past-due) remained well below their peak levels. Looking ahead, analysts expect delinquency rates in auto to stabilize; while they will continue to rise, they will do so at a more moderate pace.

The combination of increasing demand and healthy loan performance allowed lenders to extend credit to non-prime borrowers (those with a credit score below 660 – using the VantageScore 3.0). As a result, new account balances from non-prime borrowers grew from 10 percent of total balances in 2010 to 14 percent in 2015.

Lenders grow cautious

However, starting in 2015-2016, captives, large banks and other auto finance companies began to notice the early signs of deteriorating loan performance, particularly in the non-prime segment, and declining used vehicle values. As a result, many lenders began to tighten their underwriting standards (e.g., limiting terms on new loans) and in the process, pulled back on non-prime originations. Analysts believe that underwriting will continue to tighten at least in the short term with the biggest drivers continuing to be in sub-prime, or credit score of 300-600, (12 percent YOY decline in Q4 2017) and near-prime, or credit scores of 601-660, (8 percent YOY decline in Q4 2017) markets. The decline overall for the same timeframe was 4.8 percent.

Additionally, originations across the entire credit spectrum have declined year-over-year, with the pullback in originations being more pronounced in the non-prime segment, as well.

Delinquencies begin to stabilize

Delinquencies in Q4 2017, declined (ever so slightly) for the first time since Q4 2014. This slight decline is due to two factors:
1) a share shift from non-prime to prime-and-above originations, and
2) the stabilization of non-prime loans

These factors, particularly the improvement in loan performance in the non-prime consumer segments, have given some lenders a reason to consider (re)entering the non-prime segment.  Furthermore, the increasing competition for prime-and above borrowers as lenders flock to safety, and the expanding use of alternative data, have given some lenders more motivation for entering the non-prime space.

In particular, alternative data is being used more and more to help lenders score thin-file consumers, enhance risk selection and pricing in down markets. As such, alternative data provides these lenders more confidence to buy deeper and originate loans they otherwise wouldn’t have approved.

Essentially, implementing such data will not only assist lenders in obtaining a more comprehensive profile of net new consumers, but will subsequently provide increased opportunities for consumers to better their credit options now and in the future.

Brian Landau is the SVP and auto business leader, TransUnion. Landau joined TransUnion in 2014. He is responsible for executing TransUnion’s growth strategy for auto and providing thought leadership to the market. Landau has more than 15 years of experience in general management and management consulting, working for and serving many of the largest financial institutions in North America.

The Evolving Ecosphere of Consumer Data

Before technology transformed the financial services industry, traditional credit reporting agencies (CRAs) captured mainly traditional credit data on consumers for their databases and solutions. Lenders typically only reviewed this traditional or conventional credit data when evaluating a consumer for a loan. In addition to their mainstay header information (name, date of birth, address and social security number), consumers’ files consisted almost entirely of conventional credit activity, such as credit card, mortgage and auto loans, and subsequent credit amounts/payment history on these loans.

Traditional credit data provided by CRAs is governed by the Fair Credit Reporting Act (FCRA), which governs the collection of credit information and access to consumer credit reports. All users must have a permissible purpose under the FCRA to obtain a consumer report.

Traditional credit data has been used for FCRA permissible purposes such as credit decisioning, account management, collections, and prescreen marketing applications.

Yet this traditional data-only model excluded a large segment of consumers that did not use traditional credit loans and banks – “non-prime” consumers with little credit history or largely unestablished standard lines of credit. These consumers, while not prime, are still considered primarily mainstream and creditworthy, as 99 percent of non-prime loan applicants have a checking account, and more than 90 percent have a direct deposit.

As the credit market began to become flooded with more and more competitors vying for the same consumer segment, lenders and auto financing companies had to begin to dig deeper, considering more consumers and becoming savvier in how they considered the consumers to whom they extended credit. As such, lenders began to look at consumers’ files a bit differently. Traditional data alone was not telling the full story – or at least not nearly enough of the story.

Enter alternative data. More data on consumers began to emerge, shedding light on the consumer’s ability to pay, providing affirmation or contradiction related to the consumer’s willingness to pay and highlighting assets a consumer may have to leverage as collateral. Alternative data points include non-traditional lending channels outside of traditional credit bureau data, like pay day loans and club or magazine subscriptions. In addition, alternative data assets such as checking and debit information, property, tax and deed records can also help add depth to a consumer’s credit file and can have tremendous impact on business growth.

With some adoption of alternative data in the ecosphere of consumer data – it still did not convey enough of the picture of today’s consumer. Enter alternative credit data, which is helping to complete the picture and truly identify potential high-opportunity or high-risk performers. This next generation of data introduced tradeline data on predominantly non-prime consumers. This includes data heretofore excluded, including non-prime, short-term loan tradelines, ACH payments, employment attributes, income, payroll type and payroll frequency. Generally, alternative credit data, like traditional credit data, is used for FCRA permissible purposes, such as credit decisioning, account management, collections, and prescreen marketing applications.

Trended traditional credit data scores are newer models that provide deeper insight into an individual’s changes with credit usage and payment behaviors over time. Trended credit data can incorporate more than two years of account history.

The most successful lenders in today’s ever-changing landscape are the lenders that have embraced the use of all these segments of data – traditional, alternative, trended and alternative credit data. These lenders get a complete view of the credit and financial profile of individuals, allowing them to make the best decisions about their customers, ultimately enabling lenders to be more profitable and helping to enrich the financial profile for many consumers.

Randy Bobb is the vice president, Sales, Auto Finance with FactorTrust/TransUnion. Bobb has more than 20 years of experience with information services, software, analytics and consulting. He is responsible for leading the auto finance sales team at FactorTrust around risk management solutions for underwriting, account management, servicing, and marketing for large auto finance companies, captives, banks, credit unions and buy-here, pay-here companies. Connect with him at

Opportunities Uncovered with Alternative Credit Data in 2018

When it comes to helping auto financing sources improve profitability in the new year, one crucial element is alternative credit data. Several years ago, this type of data was still in its infancy. But in 2017, we saw alternative credit data begin to turn the corner. Now we are seeing many lending institutions beyond traditional finance companies not only considering its impact, but fully embracing alternative data. Use cases have shown that alternative credit data has helped with loss mitigation and pricing, as well as expanding the consumer universe for financial service providers. While it wasn’t long ago that alternative credit data was considered an emerging concept, it is now becoming increasingly more mainstream.

In 2017 we also saw ongoing declining originations among auto finance companies. This decline began in the third quarter of 2016. As a result, lenders are pulling back in the sub-prime market, with a corresponding reduction in the lending community on prime, near prime and sub-prime originations.

Reduction leads to gaps, new players revealed
With a reduction in originations, a gap is exposed. This gap presents itself as an opportunity as we move into the new year. Some prime plus and super prime lenders are investigating opportunities within the near prime consumer market. With the reduction of lenders in the near prime and sub-prime markets, newcomers now have the ability to price appropriately, while buffering some risk exposure.

chartNear prime sweet spot
As lenders are finding out, near prime can be a true sweet spot if they can make a more informed credit decision, offer competitive pricing, and remain efficient with their servicing strategies. Also, near prime often includes used vehicles which are of interest to dealers because of high inventory levels. In addition, with the change of strategy to exit sub-prime lending by major full-spectrum lenders (those who lend to all consumer categories), opportunities have been created for others to gain new market share.

This new lending opportunity can be a welcome offset to some of the potential unfavorable trends anticipated for 2018, including increasing interest rates and slowing vehicle sales. Although, higher interest rates can mean financing sources are able to charge more and, if done right, generate more revenue. In fact, the auto industry reached new heights in terms of total balances ($1.17T) and total number of borrowers (83M) in 2017 (Q3).

Credit unions looking to buy deeper too
Many credit unions are looking into the near-prime segment, as well. They are evaluating and validating the same opportunities that other lenders are considering. The underwriting process can be different for them because they spend more time getting to know their members, and in turn, these consumers become more familiar with the credit union. Credit unions also tend to have a large interest in the refinance market. Consumers in this market are becoming increasingly savvy and taking advantage of competitive credit opportunities. One example: a consumer buys a car from the dealer, then goes to a credit union shortly thereafter to get a better, lower rate. Meanwhile, the consumer has benefitted from receiving a higher trade-in amount on the front end and a lower rate on the back end.

Many of these lenders in the past would not have been as aggressive to enter the market were it not for alternative credit data. With alternative credit data, they now have the ability to underwrite consumers at almost all credit levels, or close to it. By having more information than they’ve had in the past, they are better equipped to find these opportunities and to price more appropriately. Alternative credit data is typically defined as unique tradeline, employment, banking, or contact data reported by alternative lenders that generally have not reported this data to traditional credit bureaus in the past.

Specialty finance companies that get funding from secondary markets were among the first to embrace alternative credit data. Most of these companies have also primarily focused on near prime and sub-prime segments. Now we are seeing other traditional companies, such as banks and captives, considering alternative credit data. It is in the next state of adoption. One example is the recent announcement by a top captive auto finance company to look beyond traditional credit scores to boost sales – including specifically looking at alternative credit data and applicants with limited credit histories to help accomplish this goal. The two-year pilot will research what alternative credit data attributes work best to most effectively set pricing and evaluate risk appropriately.
The changing market conditions have impacted these lenders and will likely motivate other lenders to be more effective and efficient with their underwriting and pricing strategies and to embrace new technologies. With sub-prime and full-spectrum lenders, their first objective is to understand the complete financial view of a consumer’s obligations, past performance and current stability. Alternative credit data can help with this key objective and provide a more full credit picture of consumers, allowing lenders to identify pockets of profitable consumers across all credit tiers—especially in sub-prime markets. As a result, lenders have opportunities to serve more consumers looking to build better lives.

Brian Landau is the SVP and auto business leader, TransUnion. Landau joined TransUnion in 2014. He is responsible for executing TransUnion’s growth strategy for auto and providing thought leadership to the market. Landau has more than 15 years of experience in general management and management consulting, working for and serving many of the largest financial institutions in North America.

Randy Bobb is the vice president, Sales, Auto Finance with FactorTrust |TransUnion. Bobb has more than 20 years of experience with information services, software, analytics and consulting. He is responsible for leading the auto finance sales team at FactorTrust around risk management solutions for underwriting, account management, servicing, and marketing for large auto finance companies, captives, banks, credit unions and buy-here, pay-here companies. Connect with him at

Using Unique Data in Portfolio Management Provides Improvements, Returns

To stay competitive and within budget, many auto financing companies are evaluating and determining which emerging technologies and other resources to tap into and which to pass on or postpone.

Fortunately, not all innovations include costly modern technology systems or trends. And not all business challenges require big overhauls in spending and processes.

Sometimes the most tried-and-true options—the obvious fixes—yield the most beneficial outcomes.

These can include staffing or policy changes, new equipment and new software, to name a few. In addition, adding unique data to traditional sources can offer big returns in the areas of underwriting, servicing and collections. By leveraging proprietary, alternative credit data—in real-time—financing companies better know how to interact with the consumers they serve, thereby growing and protecting their company’s portfolio.

Such unique data sheds light on underbanked consumers, a real bonus for auto financing companies who are dissatisfied with a lack of visibility into the rapidly changing alternative credit market—an estimated 20 percent of all households, or 51 million adults, according to the FDIC. This proactive tactic provides insights into the underbanked market that the Big 3 bureaus don’t have. By pairing unique alternative credit data with traditional data, auto financing companies begin to get the complete picture of their customers and prospects. And consumers begin to receive the credit they deserve.

Case study: Uncovering life events increases net returns

A case in point: Let’s look at a real-world example from an active non-prime automotive finance company. The company leveraged alternative credit data to efficiently monitor all its consumer accounts that were 30 days past due. By using this data, the company was able to identify when customers had varying life events—a change in address, mobile phone number, employment or salary, new loans or inquires, for instance—that might affect their ability to pay their auto loan. For this scenario, the file being monitored included 74,000 records.

Within the first 30 days, there was about a five percent level of activity, meaning that 3,870 of the company’s customers from this file were found to have had some type of life event that might impact their ability to pay on their existing loan. This access to timely, relevant information helps auto financing companies determine when and how to proactively start a conversation with customers and respond with the appropriate servicing or collections activity.

By identifying these customers with life-event issues, the auto financing company was able to help their customers manage their payments, provide a new credit product or even refinance, in an effort to avoid repossession of the vehicle. It also enabled the company to give reliable and current right-party contact (RPC) information, when needed, to its servicers, skip-tracers and collectors, eliminating otherwise time-consuming searches for each past-due consumer.

Within 60 days, 11,380 customers, or 15 percent of the total file on the accounts that were 30 days past due, showed some sort of level of activity or change. However, when that timeframe moved out to 180 days, that figure jumped to 29,660 customers.

Therefore, in a six-month timeframe, by monitoring this one batch of records of 30-day past due customers, the company was able to identify 40 percent of its customer base as having had some sort of life event significant enough to impact their original loan terms.

With these results, the company was able to build a use case about alternative credit data based on its monthly net savings return alone. By identifying 40 percent of its customers in this file as having a life event, the company was able to speak to these consumers on their level and help them by adjusting the terms of their loans.

After implementing alternative credit data and incorporating this approach into its portfolio management, the company conservatively estimated that it kept at least five customers’ motor vehicles from being repossessed each month. Considering that the average net charge-off rate per unit per repossession totals about $5,000 in costs and fees, it is estimated that the total monthly loss avoidance totaled about $25,000. Even with nominal monthly fees in monitoring the data at about $3,500, the company had a net monthly return of $21,500, or an annual savings of about $258,000.

Auto financing companies can continue business as usual and see the same results. Or they can take a look at available, cost-effective, easy-to-implement resources like alternative credit data, and see immediate improvements to their bottom line.

Dallas Munkus is director, customer analytics, with FactorTrust, The Alternative Credit Bureau, where he helps customers leverage the power of FactorTrust data to positively impact their business. He has more than 20 years in consumer finance, leading analysis and strategy on diverse teams, including organizations, operations, servicing, collections and more. Connect with Dallas at Learn more at