Technology is Changing How Lenders Look at Loan Applicant Income
Income verification and income validation may sound similar, but key distinctions between the two methods can make for substantial differences in how loan applications are processed. Learn how technology-assisted income validation is changing how lenders are evaluating applicant income.
Income is one of the key metrics lenders use when determining if a potential borrower is capable of repaying a loan. According to some estimates, about one in ten loan applicants misrepresents income, making it imperative that lenders substantiate such information. However, income verification is cumbersome for both applicants and lenders.
Banks, credit unions, auto lenders, and other financial institutions have relied on pay stubs and tax filings to confirm the accuracy of employment and income information. Savvy fraudsters know that these documents can be fabricated; Point Predictive has uncovered thousands of fake employers in recent years. To combat this trend, lenders oftentimes resort to outsourcing the verification process, paying firms per-head fees to go to such lengths as calling HR departments to cross-check employment histories. Other techniques involve leveraging relationships with payroll providers. Such services can come at a premium, costing as much as $40 per individual verification.
Enter Income Validation
Income validation represents a new income confirmation process. While verification and validation sound similar, income validation represents a departure from analog methods. With income validation, a select few companies are pioneering ways to leverage technology to streamline the process for lower-risk applicants while identifying those that warrant further consideration.
Point Predictive draws on two primary resources to validate income through its IncomePassTM product.
Its Proprietary Data Repository
Point Predictive maintains a continuously-growing data repository currently containing information derived from 148 million loan applications representing 72 million unique consumers. If there is an identity match against data derived from one or more previously submitted loans, the solution provides a score that evaluates whether the income provided for validation is likely to have been misrepresented. A reported income that is more than 15% higher than expected is flagged for further review.
For applicants without an identity match to the data repository, income data modeling compares stated occupation to equivalent job titles to estimate applicant income. The analysis accounts for regional differences in incomes.
In either case, analytic modeling results are passed through a documented API, including the score of material income misrepresentation, the predicted income range, lowest reported income, highest reported income, alert flags, and descriptions of factors that influenced the score.
By choosing validation as a first step and then relying on verification for only a small subset of risky applications, lenders can speed up the consumer’s experience while maintaining the same risk exposure. With income validation, the lowest risk applications can be processed automatically with no manual intervention. In addition, operational costs can be reduced dramatically, as the number of income verification transactions can be reduced by as much as 70%. Validation solutions provide wider coverage compared to verification solutions and don’t require “heavy lifting” from the consumer or the lender.
How you can make income validation your default approach
Learn more about Point Predictive’s solutions, how we can help you validate income as your primary approach, and how our solutions help flag those applications that need further investigation.
Many of our clients find that using income validation as the primary approach helps save time and money while increasing capture rates. Speak with our product solution experts to learn more about how we can help.