Your auto loan risk management strategy should include fraud recognition, alternative credit data for quality decisioning, and portfolio risk factor analysis.

AUTO LOAN RISK MANAGEMENT FOR YOUR PORTFOLIO

The defi Team defi INSIGHT, Originations

Your auto loan risk management strategy should include fraud recognition, alternative credit data for quality decisioning, and portfolio risk factor analysis.

With auto sales down from last year and interest rates rising, lenders are looking for the best available options to build a profitable portfolio. In the auto lending industry, there’s always a temptation to assume greater loan volume and risk. Over the past few years, auto lenders have become more aggressive in pricing new originations. They’re now offering longer loan terms to help borrowers with other debt and increasing the volume of subprime loans to build their business.

Successfully balancing risk with profitability is both an art and a science. Lenders with years of experience might have mastered the art of lending, developing an innate ability to fine-tune credit policies in response to market conditions. Those new to the auto lending market should look into recent advances in financial technology (fintech), which provide lenders with an important set of tools to guide auto loan risk management. Even those auto lenders who’ve been in the business for a while should take note as a means to supplement their experience.

There are three stages in the end-to-end lending cycle—applications, decision-making, and servicing—where the use of advanced fintech capabilities can positively impact auto loan risk management.

  1. Applications eliminate risk at the outset, helping lenders avoid lending to the borrowers most likely to miss payments or even default on their loans.
  2. Decision-making enables better quality loans with minimal risk of delinquencies and defaults.
  3. Servicing that regularly analyzes portfolio performance helps lenders proactively identify risk factors, adjusting credit policies and practices accordingly.

A lending cycle approach to auto loan risk management lets lenders use tactics powered by fintech to identify, reduce, or eliminate risk as early as possible.

3 Tactics for Auto Loan Risk Management

Identify Fraudulent Applications

Traditional auto thefts are down, thanks to ever-more sophisticated anti-theft technology installed in vehicles. Yet there’s now another method of auto thievery, and it utilizes fraud. Key strategies of fraud committed on a loan application include:

  • Income misrepresentation – As many as 20% of applications are inaccurate.
  • Employment misrepresentation – Any Internet search for ”fake pay stubs” shows how easy this can be.
  • Synthetic identity – This blends disparate and fictitious data, including Social Security numbers, names, and addresses used to create fake identities.
  • Fake documentation – This includes counterfeit utility bills, doctored identity documents, or fake proofs of residency.
  • Misrepresented collateral – Over-valued or non-existent vehicle or other security put up for a loan.
  • Straw borrower – An individual whose name, social security number, and credit history hide the identity of fraudsters.

Based on extensive analysis of millions of loan applications, cloud-based software platforms can analyze loan applications in real time. With this technology, lenders can recognize misrepresented personal information, falsification of documents, and other subtle indications of fraud.

Such analysis by fintech tools then returns a risk score of 1 to 999, low to high, and a code that describes the risk in more detail. A low-risk score and a high applicant credit score could then immediately auto-approve an applicant. Mid-range scores could move on to a human underwriter for further review. High-risk scores could then be auto-declined, with adverse actions automatically generated and sent electronically to the applicant.

The best way to manage risk is to prevent it. The analytic capabilities of today’s fintech enable lenders to identify and decline fraudulent applications before they become loans that can undermine a lender’s business.

Minimize Risk With Data-driven Lending Decisions

Fraud-free applications aren’t necessarily risk-free. Credit bureau scores and attributes provide lenders with a means of determining creditworthiness. They’re useful for validating the creditworthiness of applicants at the extreme ends of the scale, from exceptional to very poor credit scores. As applicants move from very good to fair, a bureau score may not be entirely indicative of creditworthiness. In these ranges, additional sources of consumer data help provide a more detailed and accurate picture of an applicant’s creditworthiness.

This alternative credit data (ACD) can be captured, aggregated, and provided as a service to lenders by a third-party vendor. This data may include monthly payment records for electricity, gas, water, cable, and mobile phone. It can include rental or lease locations and other payment histories, along with proof of ownership of or liens on real estate. Alternative credit data helps lenders make better quality lending decisions by:

  • Providing an accurate picture of current creditworthiness when ACD is combined with a bureau’s credit score.
  • Giving lenders confidence that they’re offering the best rates and terms to applicants with high credit bureau scores that are also supported by solid ACD credentials.
  • Allowing lenders to use decision rules for those with high credit bureau scores that contrast against weak ACD credentials to determine the appropriate rate and terms, such situations call for a review of the application by an experienced underwriter to assess creditworthiness.
  • Indicating improvements in the fiscal position of an applicant with low credit bureau scores yet strong ACD credentials may indicate a lower risk.
  • Identifying those with low credit bureau scores and weak ACD credentials as risks that should be avoided.

The rich data sources now available, whether from a credit bureau or an alternative resource, enable better quality lending decisions. These data sources are based on more current assessments and will often more accurately describe an applicant’s creditworthiness.

Use Reporting and Analytics to Continually Identify and Mitigate Risk

Modern lending systems provide users with integrated analytics, allowing lenders to conduct analyses of portfolios with nearly infinite variations. Analytics allows lenders to identify and evaluate risk factors that influence portfolio performance. This will enable them to adjust credit policies and practices to mitigate risk. In addition, regular portfolio risk analysis and reporting allow lenders to:

  • Identify underwriters whose overrides result in an unacceptable number of defaults.
  • Determine which borrower attributes or credit policies contribute to delinquencies for loans with 5-year terms.
  • Investigate any correlation between delinquencies and specific dealers.
  • Tighten underwriting criteria for applicants with credit scores below the defined thresholds to reduce delinquencies in that segment.
  • Calculate the optimum advance rates for borrowers seeking extended terms.
  • Decline applications from dealers whose loans during the past year show an increasing number of delinquencies.

Analytics allow lenders to make data-driven decisions. With this technology in their arsenal, lenders can better mitigate risk while continuing to improve portfolio performance.

Fintech Capabilities

Identifying fraud during the application process prevents risk at the outset. Data-driven lending decisions reduce the risk of delinquency and defaults. Analytics enables lenders to identify and eliminate risk factors by continually fine-tuning credit policies. Together, these advanced fintech capabilities are essential tools for auto loan risk management.

Getting Started

defi SOLUTIONS offers a total solution for a lender’s complete loan or lease lifecycle. Partnering with captives, banks, credit unions, and finance companies, defi’s market-leading solution helps lenders exceed borrower expectations. From digital engagement through the complete lending process, defi sets new standards for flexibility, configurability, and scalability in originations and servicing (by your experts or ours). defi SOLUTIONS has the backing of Warburg Pincus, Bain Capital Ventures, and Fiserv. To learn more about auto loan risk management, please visit www.defisolutions.com.

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