Mortgage underwriting is a highly specialized and complicated task. It involves multiple process steps and volumes of paperwork. This makes it very time consuming and error prone. To compound matters, underwriters have to deal and comply with frequent and sudden changes to mortgage rules. Much of these challenges can be mitigated if not eliminated with the help of automated underwriting tools.
Automated mortgage underwriting help lenders to expedite and make lending operations more effective. An automated mortgage underwriting tool is built on cutting-edge machine learning algorithms and robotic process automation (RPA). It automates the entire process of retrieving loan applicants’ information, analyzing it, and recommending parameters that loan applicants need to meet to get their loans approved.
In this article, we will dig deep into the lending aspects that can be improved by automated mortgage underwriting and how it will help lenders to operate seamlessly despite a fluctuating economy.
Significance of Automated Mortgage Underwriting Across Lending Stages
Mortgage Loan Application
Mortgage underwriters have to check borrower employment information to determine their capability of repaying their loan. This task became all the more challenging during the pandemic because the employment status of borrowers had become very volatile. The chances of sanctioning loans to a jobless borrower became high and beyond the control of the underwriter.
Automated mortgage underwriting involves using AI-powered models that track and analyze borrowers’ transaction details in real-time. The models can identify any sudden changes in borrowers’ transaction pattern. Such changes can hint at either an upgrade or a degrade in borrowers’ financial health. Based on this analysis, if a borrower appears to be at high risk of default, the automated underwriting software advises lenders to cut out unique deals for such risky borrowers.
Loan Processing Documentation
Mortgage lending process involves multiple systems, several databases, and various workflow tools. This results in generating large volumes of documents that are critical to process loan application. Underwriters have to manually access each system and tools to retrieve documents. This prolongs the lending process to a significant extent.
Intelligent automation underwriting tool pulls documents from these systems and stores in a central repository in digital format. Such a tool uses naming conventions like applicant’s name, property name, and others to label and classify customer data. This makes it easier for underwriters to access a specific information in an instant.
Borrower Risk Assessment
Manual underwriting involves dealing with siloed data sources that brings extreme inefficiency in risk assessments. There is no central reserve where data can be gathered, segmented, stored, and quickly accessed. This causes underwriters miss out on critical data that could make a key difference in a borrower’s risk profile.
Automated underwriting systems are fitted with reporting and visualization tools that breaks data siloes, streamlines, and gathers data that can be viewed and accessed on a central dashboard. These tools segregate and group data based on its type such as tax form, income details, and so on. Automated risk rating tool based on loss given default and probability of default models effectively captures key risk metrics for a proper borrower risk assessment.
FHA TOTAL (Technology Open to Approved Lenders) is an advanced algorithm developed by the Department of Housing and Urban Development. It is added to enhance automated mortgage underwriting process as it automates the process of identifying an applicant’s eligibility for an FHA insured mortgage loan. Such an automated evaluation decreases the risk of clearing a bad FHA mortgage loan.
Borrower Credit Assessment
Manual underwriters have to sift through multiple documents such as payment stubs, employment details, financial transactions, rent payments, among others to establish borrowers’ creditworthiness. Not only does this process consume time but is also prone to errors. Dealing with such a massive amount of paperwork increases the risk of a human underwriter to overlook a critical piece of information. Such a mistake can eventually lead to disbursing a bad loan.
An automated mortgage underwriting solution is based on natural language processing algorithms and predictive analytics. These features empower the solution to intelligently identify specific trends from multiple borrowers’ documents in a matter of moments. This frees manual underwriters who can devote their time to review more complex loan applications.
Fannie Mae had further taken off the burden from manual underwriters by automating the process of checking borrowers’ rental payment to check their financial health. Last year, Fannie Mae announced including borrowers’ rent payment in the credit evaluation process done by automated underwriting solution. With due permission from mortgage applicants, Fannie Mae’s automated underwriting tool, Desktop Underwriter will analyze borrowers’ rent payment history to provide an inclusive credit assessment.
Borrower Credit Decisioning
Mortgage credit decisioning is largely dependent on human judgement. This becomes a problem for retail mortgage lenders who have varying sets of policies and business rules to decide on sanctioning a loan. There are no set template rules which a human underwriter can follow for credit decisioning and this can create confusion. While robots are not an alternative for human judgement, automated underwriting system can assist human for better credit decisioning.
Advanced automated mortgage underwriting tools are equipped with graphical editors that allows designing, implementing, and testing credit decisioning models. These models are built by machine learning algorithms based on a range of programming languages. It helps in rapid deployment of ML-based credit decision tools in real-time. This automates all credit decision-related workflows, thereby bringing more acceleration and accuracy throughout the entire process.
Tools that Support Automated Mortgage Underwriting- Introducing MSuite
M-suite is an easy to use and intelligent optical character recognition-based platform powered by AI and ML algorithms designed to handle Mortgage Loan documents. AI and ML algorithms automate a wide range of critical mortgage lending processes. MSuite’s advanced OCR engine identifies and captures data from printed documents, gathers, and stores it in an easy-to-view digital format. This solution suite is also enhanced with statistical models that can enhance image that helps in processing loan information and digitizing documents at an impressive speed. It is based on the automation-as-a-service business model. This means to use MSuite one does not need to do any major changes to their existing IT infrastructure. They can access MSuite on return of a minimum upfront investment.
This rule-based engine simplifies complex underwriting tasks such as property review, income calculation, 1003 review, asset liabilities, and many more. Besides, the tool can also be used for upfront underwriting of files with salaried borrowers. MSuite can effectively manage multiple mortgage-specific rules and can be customized to manage rules specific to a particular mortgage lender.
MSuite’s data extraction and validation engine accepts digital data points from multiple sources such as credit information, appraisal SSRs, and so on. While doing so, guarantees over 98% data accuracy with exceptions only on those data that comes with less that 90% OCR confidence score. Such data accuracy is extremely critical for underwriters to take the right decision of determining borrowers’ financial credibility.
Here’s enlisting the ways by which MSuite supports a mortgage loan underwriter:
- MSuite captures data from multiple loan documents and stores in recognizable digital formats. This makes it easy for underwriters to search and access any file in an instant.
- MSuite takes a checklist-based approach to analyze loan documents. This approach eliminates the chances of missing or overlooking any important document.
- MSuite alerts underwriters on any missing piece of critical information in loan documents. This results in an automatic disqualification of the loan documents.
How We Assist Lenders with the Mortgage Underwriting Process?
Implementing automated mortgage underwriting does not take away the entire responsibility of a human underwriter. It takes off a chunk of repetitive tasks from an underwriter’s table to help them not to rush with their judgement.
We streamline and execute all the back-office tasks to facilitate quick and a sound judgement by underwriters. Our experts conduct multiple rounds of data validation before entering it into an automated underwriting system (AUS).
Your complex and critical mortgage underwriting requirements are signed off by industry veterans assigned by us. We leverage our over- a-decade of experience in underwriting to quickly identify risk elements in mortgage loan processing. This experience helps us to guide your underwriters to ask questions to borrowers consistent with the current market situation. We also help them to identify and flag any inconsistency in loan documents.
Partnering with us will get you an access to our proprietary tool, MSuite. This tool easily integrates into your legacy IT infrastructure and can enhance your underwriter’s productivity to a significant extent. For instance, we have successfully leveraged MSuite to help a leading US residential mortgage lender witness 2x improvement in underwriting productivity within three months. The tool also helped the lender reduced underwriting TAT to about 40%.
Who Are We and Why Are We Considered as an Industry Authority?
This article is penned by experts at Expert Mortgage Assistance, a leading mortgage underwriting solutions provider. We have more than a decade of experience of catering to lenders and credit unions with cutting edge mortgage underwriting support services to expedite their lending process.
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