Welcome!

News Feed Item

TransUnion: Rising Auto Loan Debt Trend Reaches Three-Year Mark; Delinquencies Continue to Remain Low

CHICAGO, IL -- (Marketwired) -- 05/19/14 -- Auto loan debt per borrower has now increased for three consecutive years, according to the latest TransUnion auto loan report. Auto loan debt per borrower has risen nearly 13% -- more than $1,900 -- since this trend began in Q1 2011.

Auto loan debt per borrower jumped 4.1% from $16,191 in Q1 2013 to $16,862 in Q1 2014. On a quarterly basis, auto loan debt increased from $16,769 in Q4 2013.

The auto loan delinquency rate (the ratio of borrowers 60 days or more delinquent on their auto loans) increased to 1.00% in Q1 2014, up from 0.95% in Q1 2013. However, auto loan delinquencies dropped sharply on a quarterly basis from 1.14% in Q4 2013. The delinquency rate remains below the Q1 average of 1.10% observed between 2008 and 2014.

The data provided are gathered from TransUnion's proprietary Industry Insights Report (IIR), a quarterly overview summarizing data, trends and perspectives on the U.S. consumer lending industry. The report is based on anonymized credit data from virtually every credit-active consumer in the United States.

"The continued increase in auto loan debt is a healthy sign that auto sales and the auto loan market continue to perform well," said Pete Turek, vice president of automotive in TransUnion's financial services business unit. "It's also encouraging to see auto loan delinquency rates remain at low levels; the 14-basis point drop this last quarter is especially encouraging."

TransUnion recorded 70.0 million auto loan accounts as of Q1 2014, up from 57.4 million in Q1 2013. Viewed one quarter in arrears (to ensure all accounts are included in the data), new account originations increased to 5.69 million in Q4 2013, up from 5.29 million in Q4 2012. "The fact that there are nearly 13 million more auto loan accounts than just one year ago points to strong demand for credit and the wide availability of credit in the marketplace," added Turek.

The subprime delinquency rate (those consumers with a VantageScore® 2.0 credit score lower than 641 on a scale of 501-990) increased from 5.11% in Q1 2013 to 5.52% in Q1 2014. The share of non-prime, higher risk loan originations (with a VantageScore 2.0 credit score lower than 700) grew by 34 basis points (from 31.62% in Q4 2012 to 31.96% in Q4 2013). This percentage is still lower than what was observed at the beginning of the recession (37.34% in Q4 2007). "Auto loans to the subprime population are growing as are delinquency rates for that group, but as an industry the level of risk is well managed," said Turek.

Eleven states experienced a decline in their auto loan delinquency rates between Q1 2013 and Q1 2014. The largest delinquency declines occurred in Oregon, Hawaii and California. The largest increases occurred in Michigan, Arkansas and Alaska. Auto loan balances rose in every state between Q1 2013 and Q1 2014.

This information is reported by TransUnion and is part of its ongoing series of quarterly analyses of credit-active U.S. consumers and how they are managing credit related to mortgages, credit cards and auto loans. To subscribe to TransUnion news releases, please click here.

Q1 2014 Auto Loan Statistics - Consumer-Level Delinquency Rates

Quarter over Quarter                         Q4 2013    Q1 2014  Pct. Change
----------------------------------------------------------------------------
USA                                              1.14%      1.00%    (12.3%)
----------------------------------------------------------------------------


Year over year                               Q1 2013    Q1 2014  Pct. Change
----------------------------------------------------------------------------
USA                                              0.95%      1.00%       5.3%
----------------------------------------------------------------------------


Auto Loan Consumer Delinquency Rates for Select States             Q1 2014
----------------------------------------------------------------------------
California                                                             0.76%
----------------------------------------------------------------------------
Florida                                                                0.97%
----------------------------------------------------------------------------
Illinois                                                               1.09%
----------------------------------------------------------------------------
New York                                                               0.79%
----------------------------------------------------------------------------
Texas                                                                  1.18%
----------------------------------------------------------------------------


Largest Year-over-Year Increases             Q1 2013    Q1 2014  Pct. Change
----------------------------------------------------------------------------
Michigan                                         0.92%      1.12%      21.7%
----------------------------------------------------------------------------
Arkansas                                         0.95%      1.15%      21.1%
----------------------------------------------------------------------------
Alaska                                           0.64%      0.77%      20.3%
----------------------------------------------------------------------------


Largest Year-over-Year Declines              Q1 2013    Q1 2014  Pct. Change
----------------------------------------------------------------------------
Oregon                                           0.62%      0.54%    (12.9%)
----------------------------------------------------------------------------
Hawaii                                           0.79%      0.71%    (10.1%)
----------------------------------------------------------------------------
California                                       0.82%      0.76%     (7.3%)
----------------------------------------------------------------------------

Q1 2014 Auto Loan Statistics - Auto Loan Debt Per Borrower

Quarter over Quarter                         Q4 2013    Q1 2014  Pct. Change
----------------------------------------------------------------------------
USA                                            $16,769    $16,862       0.6%
----------------------------------------------------------------------------


Year over year                               Q1 2013    Q1 2014  Pct. Change
----------------------------------------------------------------------------
USA                                            $16,191    $16,862       4.1%
----------------------------------------------------------------------------


Auto Loan Debt per Borrower for Select States                      Q1 2014
----------------------------------------------------------------------------
California                                                           $17,093
----------------------------------------------------------------------------
Florida                                                              $16,939
----------------------------------------------------------------------------
Illinois                                                             $16,304
----------------------------------------------------------------------------
New York                                                             $14,784
----------------------------------------------------------------------------
Texas                                                                $21,208
----------------------------------------------------------------------------


Largest Year-over-Year Increases             Q1 2013    Q1 2014  Pct. Change
----------------------------------------------------------------------------
New Mexico                                     $18,719    $20,042       7.1%
----------------------------------------------------------------------------
Arizona                                        $17,279    $18,421       6.6%
----------------------------------------------------------------------------
Texas                                          $19,985    $21,208       6.1%
----------------------------------------------------------------------------


Largest Year-over-Year Declines            Q1 2013    Q1 2014    Pct. Change
----------------------------------------------------------------------------
*
----------------------------------------------------------------------------
*No states experienced declines in their auto loan debt per borrower.

About TransUnion
As a global leader in credit and information management, TransUnion creates advantages for millions of people around the world by gathering, analyzing and delivering information. For businesses, TransUnion helps improve efficiency, manage risk, reduce costs and increase revenue by delivering comprehensive data and advanced analytics and decisioning. For consumers, TransUnion provides the tools, resources and education to help manage their credit health and achieve their financial goals. Through these and other efforts, TransUnion is working to build stronger economies worldwide. Founded in 1968 and headquartered in Chicago, TransUnion reaches businesses and consumers in 33 countries around the world on five continents. www.transunion.com/business

Image Available: http://www2.marketwire.com/mw/frame_mw?attachid=2596033

Contact
Dave Blumberg
TransUnion
E-mail Email Contact
Telephone (312) 972 6646

More Stories By Marketwired .

Copyright © 2009 Marketwired. All rights reserved. All the news releases provided by Marketwired are copyrighted. Any forms of copying other than an individual user's personal reference without express written permission is prohibited. Further distribution of these materials is strictly forbidden, including but not limited to, posting, emailing, faxing, archiving in a public database, redistributing via a computer network or in a printed form.

Latest Stories
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will d...
While DevOps most critically and famously fosters collaboration, communication, and integration through cultural change, culture is more of an output than an input. In order to actively drive cultural evolution, organizations must make substantial organizational and process changes, and adopt new technologies, to encourage a DevOps culture. Moderated by Andi Mann, panelists discussed how to balance these three pillars of DevOps, where to focus attention (and resources), where organizations might...
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-c...
When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Le...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
As Cybric's Chief Technology Officer, Mike D. Kail is responsible for the strategic vision and technical direction of the platform. Prior to founding Cybric, Mike was Yahoo's CIO and SVP of Infrastructure, where he led the IT and Data Center functions for the company. He has more than 24 years of IT Operations experience with a focus on highly-scalable architectures.
CI/CD is conceptually straightforward, yet often technically intricate to implement since it requires time and opportunities to develop intimate understanding on not only DevOps processes and operations, but likely product integrations with multiple platforms. This session intends to bridge the gap by offering an intense learning experience while witnessing the processes and operations to build from zero to a simple, yet functional CI/CD pipeline integrated with Jenkins, Github, Docker and Azure...
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Dhiraj Sehgal works in Delphix's product and solution organization. His focus has been DevOps, DataOps, private cloud and datacenters customers, technologies and products. He has wealth of experience in cloud focused and virtualized technologies ranging from compute, networking to storage. He has spoken at Cloud Expo for last 3 years now in New York and Santa Clara.
Enterprises are striving to become digital businesses for differentiated innovation and customer-centricity. Traditionally, they focused on digitizing processes and paper workflow. To be a disruptor and compete against new players, they need to gain insight into business data and innovate at scale. Cloud and cognitive technologies can help them leverage hidden data in SAP/ERP systems to fuel their businesses to accelerate digital transformation success.
Containers and Kubernetes allow for code portability across on-premise VMs, bare metal, or multiple cloud provider environments. Yet, despite this portability promise, developers may include configuration and application definitions that constrain or even eliminate application portability. In this session we'll describe best practices for "configuration as code" in a Kubernetes environment. We will demonstrate how a properly constructed containerized app can be deployed to both Amazon and Azure ...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.