Modern lending solutions take advantage of the latest fintech capabilities to help you assess and effectively manage risk throughout the lending cycle. When speaking about auto loan risk assessment, we include both lending and compliance risks. There are three fintech capabilities that really help lenders make smart auto loan risk assessments:
- New sources of consumer and automotive industry data that enable lenders to make well-reasoned lending decisions;
- Decision rules that allow lenders to translate myriad regulatory requirements into consistently-applied and auditable lending tasks and processes; and
- Analytics that empower lenders to continually evaluate lending processes and policies to identify potential sources of risk.
If it’s been a while since you last evaluated your lending software, it’s time to catch up. Each of these auto loan risk assessment capabilities pays benefits throughout the lending cycle. Here’s how each helps improve your lending portfolio performance.
New Sources of Data Support Well-Reasoned Auto Loan Risk Assessment
Our highly-interconnected digital economy generates volumes of securely-accessible data that gives lenders a clearer, more detailed understanding of applicant credentials and vehicle valuations. Lenders can now access consumer data for a clearer depiction of an applicant’s payment histories, in addition to credit bureau scores. The payment histories can include household utilities, cell phone, and/or rental payments, and show trends of consistent, erratic, or overpayments that indicate stable, declining, or improving financial strength. Payment trends provide a clearer assessment of applicant lending risk, and help lenders make well-reasoned lending decisions that align with their established credit policies.
Fintech advances also allow lenders to calculate accurate vehicle valuations. History-adjusted valuations use VIN-specific data and analytics to determine vehicle value based on its history. Vehicle valuation is a key factor in determining deal structure. Valuation accuracy brings an added level of confidence in assessing potential loan risk and helps lenders offer terms to minimize portfolio risk.
While these new data sources give lenders greater ability to assess loan risk across all credit tiers, they are particularly valuable to lenders who focus on subprime segments. Better quality data minimizes loan risk.
Decision Rules Transform Regulatory Requirements Into Consistent Processes That Reduce Compliance Risk
Risk assessment includes not only credit policies, but also lending processes. Lenders know that regulatory requirements are subject to change. Lenders that have multi-state operations have to deal with the added complexity of state-by-state variations. It’s impossible for underwriters, loan offices, or servicing agents to fully comprehend and consistently comply with these regulations without the aid of automation.
Decision rules reduce and even eliminate the risk of variation by automating previously-manual decisions, tasks, and processes. Through automation, decision rules provide consistently-executed and auditable processes to give lenders confidence in complying with regulatory requirements. A few decision rule examples demonstrate their power to reducing the risk of variation in your lending processes:
|
Regulatory Requirement |
Decision Rule Example |
| State Usury Laws | If the applicant’s FICO < 580, then verify that the offered rate does not exceed the maximum interest rate indicated on the lending system’s state interest tables. |
| Fair Credit Reporting Act | If decline = true, then automatically create the notification. Include adverse action reason, credit bureau, credit score, and consumer rights. Automatically send notification via email and retain a digital copy of the notification. |
| Fair Debt Collection Practices Act | If days delinquent > 90 then, then initiate a workflow to schedule the phone call and contact location per FDCPA guidelines implemented/described by decision rules. |
Decision rules provide evidence that you have eliminated variability caused by manual processes. They do this in two ways. First, the decision rules that you configure in lending workflows replace manual decisions, tasks, and processes. Second, modern lending software can record when any of these rules have been invoked during your lending processes, giving you an auditable record of compliance.
We’ve only scratched the surface regarding the power and value of decision rules. We invite you to investigate this topic in greater in our Using Auto Loan Decisioning Rules To Achieve Compliance blog.
Auto Loan Risk Assessment Through Analytics
One of the most most valuable capabilities of the fintech revolution is the application of analytics to nearly every area of the lending practice. Volumes of data captured and created throughout an automated lending process can be analyzed to assess auto loan risk in your lending practice.
Three examples:
- Identify underwriters who have an above-average number of overrides in the past six months. Is override frequency related to (lack of) experience? Are any of these overrides compliance risks? Should decision rules be added to obtain an additional level of override approval?
- Determine if there is a correlation between 90+ days delinquent and specific dealers or underwriters. Why do certain dealers present higher risks than others? Should credit policies be tightened? Do any underwriters need additional training regarding credit policies or risks?
- Are there any developing trends regarding delinquencies or defaults that indicate the need to refine credit policies to avoid future risk? Are there factors such as make, model, vehicle age, or loan terms that correlate with higher risk? How should scorecards be modified to mitigate these risks? Does your risk-based pricing need revisiting?
Analytic capabilities are critical to helping lenders assess and mitigate potential sources of risk in lending processes and portfolio performance. Lenders who are serious about auto loan risk assessment should make sure that analytics is an integrated component of their lending software.
Fintech Enables Auto Loan Risk Assessment
The demands of today’s auto lending market cannot be adequately addressed by yesterday’s lending software. Fintech advancements give lenders the ability to far more accurately identify, assess, and mitigate risk throughout their lending practices. Make sure your lending software incorporates new data sources that enable well-reasoned lending decisions, rules that eliminate the variability of manual decisions and processes, and analytics to identify and mitigate sources of potential risk.
Getting Started
defi SOLUTIONS is a leading fintech provider of loan origination and analytics software. We understand the importance of accurately assessing and minimizing risk throughout your lending practice. Take the first step toward better risk management by contacting our team today or registering for a demo of defi LOS and defi Analytics.
