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"One key benefit to implementing AI is how fast all of this processing, verification, and classification can be done. There are more than 600 rules that could apply to a loan, so from a volume and capacity standpoint, there is a significant advantage to automating loan and rules processing."

AI and machine learning could be transformative for mortgage—if they’re leveraged properly.

MReport, February 2019
By Jill Jones

There are significant changes taking place to mortgage lending rules. To proactively stay informed of the changes, be in compliance, and remain competi-tive it will be important for both bank and nonbank lenders to embrace leading-edge technology solutions that are based on artificial intelligence (AI) technology for processing loans and maintaining compliance. Using both AI and machine learning (ML) can help lenders process more mortgages in less time while conforming with all of the federal, state, and other rules.

Mortgage Rules Are on the Rise
After the 2008 housing crisis, government-sponsored enti-ties (GSEs) such as Freddie Mac and Fannie Mae enacted a set of standard rules that must be followed when processing a loan. There are also state and local rules with which lenders need to comply, and government-backed and Veteran Administration (VA) loans also have specific rules. Additionally, the Home Mortgage Disclosure Act (HMDA), originally enacted by Congress in 1975, was updated with changes that were signed into law by the president on May 24, 2018. For HMDA, 47 different data points need to be monitored for key documentation in a loan package. It is essential to identify the new critical data points required and take action to provide the additional HMDA data, or you could face fines by the CFPB. Keeping up to date and compliant with HMDA should be a priority for lenders in 2019 and beyond. In a tight mortgage market, there are naturally fewer mortgage loan applications. To stay competitive and profitable, the industry is responding to this lack of loans by offering different, nontraditional products to try to generate revenue. Examples include home equity lines of credit (HELOCs) and non-qualified mortgages (non-QM). These products have their own unique set of rules, which again increases the overall number of rules that a lender needs to be aware of and meet for compliance purposes.The bottom line is that there are more rules today, which adds complexity to loan processing and makes compliance more challenging.

Accelerating Loan Processing (and Rules Processing) with AI
How can lenders stay on top of all these rules? Using AI and ML can help automate a significant amount of mortgage loan processing, which includes rules processing and compliance. This not only creates a faster system, but a more accurate one that can help reduce errors and improve compliance. AI allows much of the work that was previously done manually to now be automated, including reading through hundreds of loan documents and verifying information against the particular set of rules for that loan.With ML, rules can be pre-loaded into the system and “learned” in advance. When new loan documents are entered into the system to begin processing a mortgage, it will use vision-based learning technology that scans the documents, collects the right information, and then matches it against the correct set of rules for that loan for verification. The system will know to check and verify for only the specific set of rules that apply to the loan that is being processed. As the AI-based system identifies missing information and errors, it can organize and classify documents by error level, identi-fying and isolating all of the risks. And, lenders can classify documents as “accepted” or “denied,” and then organize the denied documents based on why they have been denied. This allows lenders to prioritize their efforts for correcting errors and gathering additional information. All of this helps lenders in their efforts to comply with federal, state, HMDA, and other rules.

The Benefits of AI—Speed, Accuracy, Customer Service 
One key benefit to implementing AI is how fast all of this processing, verification, and classification can be done. There are more than 600 rules that could apply to a loan, so from a volume and capacity standpoint, there is a significant advantage to automating loan and rules processing. In addition to speed, accuracy is also important. Having a human read through hundreds of documents can lead to fatigue, which opens up the potential for errors. These errors could lead to compliance issues—and fines—so it is important to be as accurate as possible. AI technology can run on a near constant basis without fatigue, so there are advantages to deploying this technology when processing loans and the rules associated with them. 

Improved speed and accuracy can lead to other benefits too. First, productivity increases—lenders can process more loans in less time, which ultimately reduces costs. Together, all of this can give lenders a competitive advantage—you can compete more effectively against other companies that are not using AI technology. Being able to process loans faster and more accurately will make your organization a more attractive lender, which will help you to win more business in today’s highly competitive mortgage market. 

And when the compliance process can be done faster—both the verification of what is correct and identification of errors or missing information—it helps all of the different parties involved in the mortgage process. This includes the borrowers, who do not want to wait for a week to find out if all of their loan application documents are correct or if they need to provide more information. Having this process happen more quickly reduces customer frustration and improves satisfaction. Creating a better experience for buyers is the most critical aspect of customer service and can help lenders generate repeat business and referrals. 

A faster, better buying experience is especially crucial for millennials, who make up a significant portion of today’s home buying population. According to the National Association of Realtors 2018 Home Buyer and Seller Generational Trends Report, buyers aged 37 years and younger (millennials and Gen-Y) continue to be the largest generational group, making up 34 percent of all homebuyers. The study also notes that millennials have been the most active homebuyers for the last five years in a row. These numbers could continue to rise as the overall millennial population grows. According to population projections from the U.S. Census Bureau, millennials are expected to surpass baby boomers in 2019 as their numbers increase to 73 million people. 

This age group, which has grown up using technology and continues to use it heavily for personal and professional purposes, wants a faster, more “retail-like,” digital experience from lenders, similar to other services that they buy. When they shop for a mortgage, their first instinct is not to call a real estate agent but to search online. Millennials are comparison shoppers, and speed and ease-of-use are important criteria for them in nearly every-thing that they purchase. 

Having the ability to offer a seamless, all-digital experience that can process loans quickly is important to attracting and retaining the millennial home buying market. And, being able to process a loan even one-two days faster than another lender can make a big difference on who they select for a mortgage. In addition, millennials are quick to share their buying experiences (both good and bad) using social media, which can either help build a lender’s business or damage their reputation. Positive peer reviews are important to this group, so it is vital to create a positive experience for buyers that may be quick to share their opinions of a mortgage lender online.

AI also provides analytics tools that can help organizations optimize business operations. For example, you can determine the number of loans that your company is processing over time, enabling you to do forecasting that can help project future revenue and what resources will be required. Also, once a loan enters the system, lenders can determine the probability of that loan closing, and approximately how long the process will take. This gives the lender more predictability in its revenue stream. 

How is AI Being Used Today?
Most companies have historically processed loans and rules manually, which is a prolonged, time-consuming process. Today, about 30-40 percent of vendors are still using this “old fashioned” approach. 

Now, many lenders are embracing AI technology to do at least a portion of their processing, and it is a top priority for the future. To compete, survive, and grow in today’s tight lending market, now is the time to embrace AI and ML technology. The capabilities of these technologies not only improve compliance, but also speed, productivity, and accuracy. This is important in a dynamic environment with a wide range of different rules that could change and expand over time. Those organizations that fail to embrace this new technology, or are too slow to adopt it, could be left behind.

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JILL JONES is VP of Marketing at AI Foundry. She leads the marketing strategy, program creation, and analysis including digital marketing, demand generation, content marketing, communications, and operations to drive marketing and sales funnel activities. She has an extensive background in enterprise software and marketing that spans across numerous industries. She is based in Wakefield, Massachusetts