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22 | M R EP O RT FEATURE repurchase risk. McKinsey recent- ly identified non-QM loans as one of five trends that will shape next year's housing market, as lenders look for ways to serve the grow- ing number of borrowers who are self-employed or have income streams that disqualify them from traditional mortgages. Since the early days of the COVID-19 pandemic, when non-QM loan volume virtually dried up, more non-QM lenders have been enter- ing or re-entering the market. Meanwhile, the number of secu- ritizations of non-QM loans grew steadily throughout 2021 and is expected to continue in 2022. Certainly, there are many self- employed borrowers who have the ability to repay. Problems occur, however, when lenders start working with borrowers but lack controls to document their underwriting decisions. It will be important for lenders to focus on all facets of credit, income, and assets to make sure the data they are using has been validated. The use of automated tools that can take some of the complexity out of the process will certainly help. Also, performing a more thorough credit analysis and increasing audit reviews for these types of loans can minimize issues. QM loans by nature come with a certain agreed-upon risk, yet it's important for lenders to have safe- guards in place to make sure they are not exceeding these levels. Fortunately, I see most lenders are taking a more serious view of risk in recent years. I remember a time when we would board a new client for our QC ser- vices, and the only person we spoke with at the lender was the Director of QC. We rarely spoke with the people they reported to. Today, I'm having far more conversations with Chief Risk Officers and other senior lead- ers—in fact, every one of our engagements is driven by these discussions. Lenders are also spending more resources on loan quality as well. For example, Fannie Mae only requires that lenders perform re- views on a sample of 10% of their files. Lenders have a choice to perform additional discretionary and target samples in addition to this 10% requirement. Our clients have always done these discre- tionary reviews, but only a mini- mal percentage of them. Recently, that's flipped around, and they're doing much more, because they realize the importance of main- taining good loan quality. Still, QC is viewed as a cost center, and is rarely given the same priority as loan production. It's also a widely outsourced func- tion. But given today's repurchase risks, lenders must make sure their third-party QC providers are dialed in to areas of growing con- cern. For instance, I mentioned appraisal quality earlier—this is an area in which QC vendors must leverage their underwriting expertise to make sure appraisal competency is baked into their loan audit services. Yet tradition- ally, this has not been a strong point among QC providers. Putting Plans into Action W hether lenders outsource QC functions or address them in-house, the ability to identify, handle, and clear loan defects quickly and cost-efficiently will be critical. For many, the best path forward will be leveraging automated QC technologies that are able to identify loan defects through automated audit rules, focus audit staff on these excep- tions, leverage portal technology to resolve conditions with the area of responsibility, and allow the portion of loans that are defect-free to sail through the pro- cess across pre-close, post close, TRID, HMDA, or pre-funding reviews. One of the newer options that lenders have are technologies that leverage machine learning-driven automated document process- ing technologies that can scan thousands of data points across hundreds of pages in loan file documents for defects, enabling the bulk of loans to be quickly cleared while identifying a smaller subset of files that need remediation. Not all of these technologies are the same, but the superior ones are those that work with a broad set of examples across document types that their machine learn- ing tools are able to "learn" from. Those that have robust APIs can empower lenders to integrate these tools with other systems and pause the process at any time to address errors or other find- ings as they appear. Lenders can also leverage confidence scores, the degree to which the machine thinks it got it right, to create their own thresholds for certain critical or non-critical document types. For example, this could be used to focus attention on documents that are most likely to contain defects which could result in a repurchase. Automation is the key for having the ability to automatically and quickly handle and clear defects as they are found, saving days and days of resource time. With more automation, you no longer need to wait for your out- sourced QC provider to complete the review of all your post-close loans and only provide you with a static report. With newer tech- nologies, defects can be identified and addressed as they are found in real time, often within hours. The bottom line, one way or another, is that every lender needs a sound strategy for mini- mizing risks in what will be a growing purchase market in 2022. That strategy needs to include technology automation that can catch defects early, optimize secondary market profits, and minimize future repurchase risk. The good news is that today's lenders have many more options to choose from when it comes to defining the strategy that works for them. With so many market variables and challenges affecting their profitability in 2022, the best time to choose the right strategy is now. As SVP Client Services for LoanLogics, RICK HALL has responsibility for managing LoanLogics' Account Management and Loan Audit Operations teams. His role creates greater alignment and coordination across these teams, enabling better service for clients. Through his leadership and focus on continuous process improvement, he looks for opportunities to optimize productivity in the company's audit operations, drive new audit best practices, and ensure an exceptional customer experience for clients using LoanLogics technologies and services through Account Management support. Automation is the key for having the ability to automatically and quickly handle and clear defects as they are found, saving days and days of resource time.

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