Auto loan application approved with a dollar and coins laying over it.

LENDING SOFTWARE: HOW IT HELPS IN A RECESSION

The defi Team defi INSIGHT, defi LOS, Thought Leadership

lending software

As of this writing, there’s no pending recession, though there’s frequent speculation of a downturn, perhaps in 2020. When that downturn eventually arrives, competition for lending will be intense. Lenders will have to employ every method to minimize lending risk and operational costs. Regardless of the type of your business—bank, credit union, or finco, the biggest factor in maintaining profitability during a recession is likely to be your lending software.

During a recession, financial institutions using monolithic, legacy lending software will be hamstrung. Cloud-based lending software will give lenders tools to make better-quality lending decisions consistently.

Lending Software Technology Gives Lenders a Clear Advantage

The Internet and cloud computing generate volumes of consumer data that can provide a more detailed, current, and accurate assessment of a borrower’s financial position. Powerful analytics use machine learning to evaluate applications and offer recommendations that minimize risk. The technology recognizes potential fraud efficiently, verifying income and employment, and uncovers previously-overlooked lending opportunities that could boost profit in a downturn. In any lending environment, and especially during a recession, lending software with these features gives lenders a clear advantage.

Expect Increased Fraud in When Credit is Tight

In an economic downturn, tight credit policies are likely to generate an increase in loan applications containing misinformation intended to improve the applicant’s ability to obtain a loan or better terms. There will be no letup from individuals and cartels who submit loan applications that are virtually guaranteed to become early defaults.

Lenders can prevent fraudulent loan applications from infecting their portfolio with analytics. Based on analysis of tens of millions of loan applications and the history of those loans, machine learning techniques can recognize indications of misrepresented information such as:

  • False identity;
  • Income that doesn’t synch with occupation; or
  • Fictitious employment.

When fraud analytics suspects information misrepresentation in an application, it reports the type—identity, income, or employment—and provides a score indicating the likelihood of fraud. High scores are candidates for declines, while medium-to-low scores can be queued for review by an experienced underwriter. If income or employment misinformation is suspected, an automated call to verification services can either confirm or refute the finding.

Lending software with fraud analytics is a powerful defense against loan applications with a high probability of becoming losses. Fraud analytics provide value in any stage of the economic cycle and are particularly effective during times of tight credit.

Income and Employment May Not Reflect Reality

Income and employment verification services incorporated into loan origination provide immediate confirmation or refutation of these critical application attributes. When income or employment discrepancies are noted, lenders can use decision rules to determine the next step in the loan origination process. Income discrepancies which are under a specified percentage can be ignored as the application proceeds to the next step. Income discrepancies exceeding the percentage can either be reviewed by an experienced underwriter and have a stipulation applied, or else declined. Similarly, when verification services fail to confirm employment, the application can be reviewed by an underwriter or automatically declined.

Lending software with verification services eliminates high-risk loans automatically with a minimum of underwriter overhead. At any time, a small percentage of loan applications are likely to inflate income or falsify employment. The percentage is likely to be higher during a downturn. Automated verification reduces the risk of granting credit to borrowers with questionable income or employment, which is more common during a recession.

Trended Credit Reveals Changes 

When an application is fraud-free, and income and employment have been confirmed, lenders can bring higher confidence to lending decisions with trended credit data. Credit scores characterize applicants’ financial strength with a single number. Trended credit data provides as many as 30 consecutive months of tradeline data that can reveal a changing financial position. A subprime applicant who has been assuming increasingly larger balances and paying them in full every month is a better credit risk than credit score alone indicates. A prime applicant who missed several payments in recent months is a greater risk than credit score indicates. Trended credit data is one more valuable tool in helping lenders reduce credit risk.

Reduce Credit Risk Today and be Well-Prepared for Tomorrow

Learn about these services by attending a webinar:

Lending Software for Any Economy

Cloud-based lending software natively integrated with fraud analytics, verification, and trended credit services help lenders reduce credit risk. Although the possibility of a recession appears remote at this time, proactive lenders will invest in the latest advancements in lending software—both to benefit now and to be well-prepared when fortunes change.

Getting Started

defi SOLUTIONS cloud-based loan origination software incorporates fraud analytics, automated verifications, trended credit data services, and more. Take the first step toward better lending decisions in any stage of the economic cycle by contacting our team today or registering for a demo of defi LOS.

Curious?

Get in touch with us today and get a demo!

REQUEST A DEMO

(Visited 105 times, 1 visits today)