The mortgage lending landscape is continuously evolving. While several years ago, origination volumes were rising unimpeded, now the market has swung in the opposite direction. In the current low-volume origination environment, the stakes are higher than ever for maintaining accuracy and integrity in the loan verification process.
In May, Fannie Mae’s Quality Insider article brought the critical issues surrounding loan verification to the forefront of the industry conversation. In the report, Fannie Mae explicitly highlighted lenders’ challenges in income calculation, employment verification, asset documentation, the management of undisclosed liabilities, and collateral valuation. These challenges, which were also prevalent in the 2023 quarterly review, underscore the need for innovative solutions.
Thankfully, there is a future where technology bridges the current gaps in the loan verification process. Clients using CoreLogic’s AutomatIQ Borrower platform can circumvent these challenges to focus instead on responding adeptly to client needs.
Unpacking Fannie Mae’s Findings
In Fannie Mae’s article covering Q4 2023 statistics, the GSE provides a measured view of the recurring verification issues that lenders grapple with. Key takeaways include:
- Defects in income verification and calculation: A critical examination of the Q4 2023 review illustrates various facets where verification and calculation can falter, significantly impacting the underwriting process. Key areas of concern include calculating base income, accurately documenting self-employed income, and evaluating variable income, such as bonuses, commissions, and overtime. Notably, the report found that over half the defects related to qualifying rental income stem from the misuse of rental income as a departing residence, especially when such properties are not currently rented.
- Asset documentation shortcomings: Effective verification of a borrower’s assets is foundational to accurately assessing loan eligibility. There are a myriad of cases showing incomplete or poor-quality asset documentation, which throws the magnitude of this issue into sharp relief.
- Undisclosed liabilities: The persistence of undisclosed liabilities, as flagged in the sampled cases in this report, underscores this critical area of improvement for lenders. Issues around liability disclosure amplify the risk of inaccuracy in debt-to-income calculations and can potentially lead to invalid loan decisions.
The Strategic Edge of AutomatIQ Borrower
Addressing the gaps highlighted in Fannie Mae’s newsletter is imperative if lenders want to remain effective and profitable. That is why CoreLogic’s AutomatIQ Borrower has significantly advanced the automation and efficiency of the underwriting process by adding Borrower’s Income Assets and Liabilities Analysis.
Learn More About The Mortgage Industry’s Digital Transformation
Enhanced Liabilities Management
The forthcoming AutomatIQ Borrower Liabilities Analysis and Loan Quality Debt Monitoring systems are pivotal to detecting undisclosed debts throughout the loan processing phase.
The Liabilities Analysis tool meticulously scrutinizes documents and data to identify hidden liabilities, including the often-overlooked student loan calculations, which emerged as the number one issue among initial significant loan defects in the latest Fannie Mae report. On the other hand, Loan Quality Debt Monitoring provides ongoing surveillance of new debts and financial alterations, allowing for precise debt-to-income ratio calculations.
Combined, these tools equip lenders with a comprehensive set of tools for mitigating risks associated with undisclosed liabilities.
Enhanced Income Analysis Through Strategic Integration
AutomatIQ Borrower Income Analysis both standardizes borrower income calculations for various investors, such as Fannie Mae, Freddie Mac, FHA, VA, Portfolio, etc., as well as facilitates income calculation and analysis through strategic integrations with the GSEs’ frameworks. These framework integrations include the Fannie Mae’s Representations and Warranties (R&W) program and Freddie Mac’s Asset and Income Modeler (AIM) for Income program.
This integrated approach allows underwriters, processors, and loan officers to compare income data accurately, meet specific investor requirements, and create detailed reports showcasing compliant income calculation and documentation. Having such an ability to defend data accuracy is crucial since documenting and verifying diverse income sources is a complex undertaking, which the Fannie Mae report found was done improperly in many samples.
CoreLogic’s AutomatIQ Borrower solution further elevates income analysis precision by leveraging verification of employment and income (VOEI) data orchestration. This data plugin ensures that income analyses meet the stringent GSE standards, minimizing errors and providing dependable assessments of repayment capability.
Advanced Asset Verification for Financial Stability
Our asset verification process is designed to provide a seamless and accurate evaluation of a borrower’s financial health. We reduce documentation inaccuracies by automating asset checks with AutomatIQ Borrower and issue a comprehensive asset report.
In parallel, our asset verification process is designed to reduce documentation inaccuracies by providing digitally sourced data methods and includes automated asset data checks to help avoid common documentation misses. It provides comprehensive asset reports with audit trail tracking for all data updates, ensuring transparency throughout the verification process.
Forward-Looking Solutions
With an emphasis on continuous improvement, AutomatIQ Borrower integrates learnings from current challenges to preempt future obstacles, promising lenders an earlier resolution for a more economical process. Resolving issues early in the process can also help prevent more serious consequences down the road.
Fannie Mae’s Quality Insider article from May 2024 sheds light on the pressing risks for mortgage lenders and lays the groundwork for more stringent and accurate loan processing methodologies. CoreLogic’s AutomatIQ Borrower responds to these recommendations by offering a tech-forward solution that is tantamount to a pivotal shift in how lenders can leveraging technology to enhance the integrity and reliability of the loan calculation process.
Find out how to enhance your workflow with AutomatIQ Borrower.
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