Auto Loan Delinquency Statistics

AUTO LOAN FRAUDS: TIPS FOR IDENTIFICATION AND PREVENTION

The defi Team 3rd party integrations, auto loan origination software, Automation, defi INSIGHT, defi LOS, defi Partners, Fraud, Loan Origination Software, Technology, Webinars

Auto Loan Delinquency Statistics

With technology growing and evolving by the second, fraud is more prevalent than ever. In its July 2020 white paper, the Federal Reserve reported that “synthetic” fraud is the fastest-growing type of financial crime. The latest estimates indicate synthetic identity fraud is a $1.4 billion burden. TransUnion says questionable lending transactions have increased by 11% since the beginning of March, even though the number of originations has declined. 

Auto loan frauds are an unfortunate aspect of the industry. While borrowers have benefited from increasingly automated lending processes, fraudsters are taking advantage of financial and personal information obtained illegally (data breaches, phishing) at the expense of consumers and lenders. 

In order to best combat auto loan fraud, it is first necessary to understand the types of fraud you’re likely to encounter, as well as who is likely behind them. 

Identifying the Different Types of Auto Loan Fraud

Lenders need to be concerned with two general categories of auto loan frauds. The first involves nefarious individuals and cartels whose purpose is to acquire vehicles (typically of high value) with a minimum payment, ship the vehicles overseas, and immediately cease making payments. The second involves an individual experiencing financial struggles who nonetheless needs a vehicle. They may be tempted to misrepresent information with the goal of improving their chances of obtaining a loan or lease or getting better terms. Regardless of the motivation, every auto loan fraud attempt is a risk you don’t need.  

To combat auto loan frauds, lenders need to incorporate fraud detection capabilities into their originations process. Modern loan origination solutions allow lenders to select and easily integrate four capabilities that help detect the most frequent methods of auto loan frauds, which include the misrepresentation of income, employment, vehicle value, and identity. The tables below delve into each type of auto loan fraud and explain how innovations in lending technology help to identify and prevent them.

Employment Misrepresentation

Employment Misrepresentation

Problem: Fraud-enabling services offer a range of employment confirmation methods,  including company phone number, “confirmation letter” of employment, counterfeit employer website, false LinkedIn profile, and “references” from fictitious former managers. 

Prevention: Use an automated income verification platform like Equifax’s The Work Number, a database of payroll records from more than 1 million employers.

Income Misrepresentation

Income Misrepresentation

Problem: An applicant inflates annual income by providing false-yet-authentic-looking income statements that are easily created or edited online. 

Prevention: Income validation from PointPredictive analyzes the applicant’s stated income, comparing it with millions of reported salaries categorized by occupation, cities, census data, IRS income data, and other sources to detect misrepresented income.

Vehicle Value Inflation

Vehicle Value Inflation

Problem: It’s not just individuals and cartels that perpetrate fraud. Dishonest dealers inflate vehicle values on loan applications to boost their margins. The dealer’s sleight-of-hand rarely gets noticed by the borrower. 

Prevention: Vehicle valuation services from BlackBook use previous ownership records, usage, title, accident history, and other factors to calculate an accurate, VIN-specific vehicle value.

Synthetic Identity

Synthetic Identity

Problem: Consumer information from data breaches or careless management of personal information enables the creation of an identity. It is typically composed of a stolen SSN, borrowed tradelines, false employment, and other data sources combined with the fraudster’s actual address and phone number. Together, it generates a seemingly credible applicant profile. 

Prevention: Machine learning techniques from Point Predictive analyze loan applications to determine the likelihood an application contains a synthetic identity and provides a risk score and reason for suspecting identity fraud. 

 

Learn how you can boost your immunity to auto loan fraud by watching our informative webinar, Where Fraud Is Headed in a Post-Pandemic World. Get valuable insights and advice from fraud prevention experts as markets begin to shift and we begin to emerge in a post-pandemic world. 

Prevent Financial Loss with Integrated Auto Loan Fraud Identification Capabilities

Without the aid of the latest innovative lending technologies, lenders invite risk that otherwise could be prevented. An ever-widening range of data sources helps determine the validity of applicant information. Machine learning techniques continually improve their ability to recognize potential auto loan frauds. These capabilities are easily integrated into a model loan or lease origination solution, giving lenders the ability to identify and prevent loan applications that—subtly or obviously—indicate risk that is likely to result in financial loss. 

Getting Started

defi SOLUTIONS provides configurable lease or loan origination systems, loan management and servicing, analytics and reporting, and pre-integrated fraud identification services. If you’re struggling with the challenges of identifying and preventing auto loan fraud, contact our team today or register for a demo.

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