PERSON OF THE WEEK: Arguably, the single thing mortgage lenders need most in today’s market is good quality data.
In fact, considering that data impacts almost every single facet of the mortgage process, it’s safe to say that it has become the lifeblood of the industry.
Using data, mortgage lenders are able to predict a borrower’s creditworthiness, detect fraud, accurately value properties, speed processing times, reduce manual errors, streamline document management, improve reporting, enhance compliance and mitigate risk, among a wide range of other goals.
In addition, lenders can use data to predict trends and navigate market uncertainty, the latter of which is gaining considerable attention in light of recent events.
To learn more about the role data plays in helping lenders navigate the current market volatility, MortgageOrb interviewed Joel Rickman, general manager and senior vice president of U.S. mortgage and verification services at Equifax.
Q: Uncertainty is a constant in the mortgage industry – and so is the need for data. What role does data play for lenders who are navigating economic uncertainty?
Rickman: Uncertainty in the mortgage market is nothing new. However, with the combination of rising costs, regulatory ambiguity and shifting consumer behavior, lenders face a new layer of complexity. Reliable, real-time data is not only an operational asset, but offers a stabilizing force and strategic advantage.
Data is becoming a primary tool for lenders to manage pipeline risk, improve decision quality, and anticipate market shifts. With questions swirling around potential GSE policy changes and economic volatility driven by interest rate fluctuations, lenders need tools that help them move quickly while maximizing resources and maintaining accuracy.
As lenders work to reduce loan repurchase risk, they are placing a greater emphasis on data integrity and consistency. One increasingly common strategy is to layer verification checks throughout the mortgage process, rather than just upfront. Reverifying a borrower’s income and employment before closing helps ensure the loan still meets eligibility requirements, especially in periods of job market instability. The goal is to strengthen confidence through each step of the lending lifecycle, using data to both reduce uncertainty and support smarter decision-making.
Comprehensive income and employment data provides lenders with timely insights, enabling them to adjust to changing market dynamics, gain new business, and enhance lending efficiency. A clear view into a borrower’s employment history or income trends can help identify potential risk earlier in the process, enabling lenders to take proactive steps to safeguard loan quality with confidence. This is particularly important as borrower circumstances may evolve between application and closing, and helps reduce the risk of downstream issues.
Q: How can automated access to income and employment information alongside the credit file help lenders fast-track mortgage originations and home equity loans, especially in a market constrained by staffing reductions and shifting consumer expectations?
Rickman: In response to the pressure to do more with less, many lenders are tasked with streamlining operations and reducing headcount while working to meet heightened borrower expectations for speed and convenience. In today’s resource-constrained environment, where every manual task adds strain to already stretched teams, automation is essential to scaling without sacrificing quality.
When income and employment verification is integrated into the process alongside the credit pull at the start of the application, lenders can see an early indicator of whether those important details are available without asking the borrower to submit additional information. This allows them to confidently wait to pull the income and employment verification until the borrower provides intent to proceed, without investing any additional labor.
This approach also helps minimize waiting on pay stubs or employer callbacks, while helping the lender reduce risk tied to outdated or potentially inaccurate information. Additionally, it can reduce documentation burdens on borrowers and accelerate loan decisioning while allowing teams to focus on higher-value activities, rather than chasing paperwork. And because the verification process is built on data provided directly by employers, lenders can proceed with greater confidence.
Integrating these verifications also sets lenders up to be more responsive in fast-moving market conditions. If interest rates drop and refinance demand spikes, lenders using automated verification are better positioned to handle that surge. The same applies to the uptick in home equity loan activity, allowing lenders to move quickly and confidently without sacrificing accuracy, even as volumes fluctuate. When consumers move quickly, lenders need to match that pace – or risk losing the loan altogether.
Another benefit of automation is its consistency. Manual processes are prone to delays, data-entry errors and inconsistent outcomes, while automated verification ensures that data is applied the same way across every file. This uniformity helps lenders deliver a more predictable, efficient experience while staying compliant with underwriting guidelines.
Q: What role does alternative data play in helping lenders gain a clearer picture of borrower risk and creditworthiness, particularly in cases where traditional data may fall short?
Rickman: Traditional credit data remains a cornerstone of lending decisions, and the three credit bureaus offer some variances that help give lenders and consumers a more comprehensive view of creditworthiness. However, a credit score alone often doesn’t tell the full story, especially for borrowers with thin credit files, younger consumers or those who are re-entering the credit market. Alternative data helps fill in the gaps, providing a broader and more dynamic view of a borrower’s financial picture.
Income and employment history can be an integral part of that equation. Using verified, real-time employment data can reveal stability and income consistency that may not be reflected in a credit score alone. Take a borrower with limited credit history that works a steady job with a growing income — this person may be a strong candidate for a loan, but without alternative data, they might be overlooked.
Other forms of alternative data, such as utilities and telecommunications payment history information from the NCTUE (National Consumer Telecom & Utilities Exchange), rental records or even professional licensure, can also contribute to a more comprehensive assessment of creditworthiness. These insights offer verifiable, consistent signals of financial reliability and prove especially helpful in expanding access to credit for underserved communities where traditional credit-building paths may be less common.
Lenders are also using alternative data to improve portfolio performance, including paying closer attention to factors that might fall below the surface, such as rising household debt or unreported buy now, pay later obligations. By evaluating a wider range of attributes, they can more accurately segment risk, identify resilient borrowers and avoid approving loans that may initially appear sound yet carry hidden vulnerabilities. This more holistic view of borrower behavior helps reduce default risk while also allowing lenders to responsibly approve more borrowers.