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The Impact Of AI On The Mortgage Sector

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In the not-too-distant future, you may participate in a video conference and speak with a virtual agent about your mortgage alternatives. Based on the chat, an AI-written document will then provide tailored suggestions. Lastly, an algorithm will evaluate your application before a human underwriter decides whether to accept or reject it.

Everywhere, artificial intelligence is having an impact, and the mortgage sector is no exception. According to mortgage specialists, there are several applications of AI in their industry, ranging from creating marketing text to identifying fraud. However, don’t anticipate many businesses to rely on the technology exclusively for critical tasks like property valuations or credit risk assessments until it becomes more dependable.

AI’s Place In The Mortgage Sector

Financial technology companies’ usage of AI may be divided into two categories: strategic and efficient, according to Pete Woodhouse, chief technology officer of Prosper, a fintech lending platform.

Analyzing consumer behavior for marketing purposes or searching for early indicators of loan default are examples of strategic applications of AI. Other efficiency-focused AI uses include chatbots, autonomous code generation, and services that let businesses accomplish more with fewer employees.

Many of these applications take place in the background, and according to Woodhouse, “clearing out technical debt” is one useful application of AI. He refers to older systems’ use of “ancient code,” which may be foreign to modern programmers and engineers. Artificial intelligence, on the other hand, can interpret that data and assist in updating it.

AI may also be used to create marketing materials in the mortgage sector. Artificial intelligence may aid with keyword research, which helps a mortgage lender rank higher in search engine results, in addition to generating ad text and website content.

AI’s Past Applications In Mortgage Lending

Although it may seem futuristic, the concept of a computer evaluating mortgage applications is not new.

According to Steven Sless, a 20-year veteran of the mortgage sector and the chief operating officer of Trius Lending Partners, a financing company for real estate investments, “[Fannie Mae and Freddie Mac] have been automated for many years.”

Lenders can enter borrower data into Fannie Mae’s Desktop Underwriter program to produce automated underwriting choices. Loan Product Advisor is a comparable software used by Freddie Mac. But through a process called machine learning, artificial intelligence presents the possibility of advancing these systems’ decision-making capabilities.

An article from the Massachusetts Institute of Technology (MIT) claims that machine learning, a subfield of artificial intelligence, “gives computers the ability to learn without explicitly being programmed.” According to MIT, machine learning and artificial intelligence are frequently used interchangeably.

AI and machine learning are a little different from automation. In one of its most popular forms, automation entails a system that, when certain conditions are met, does particular actions. For example, an automated system such as Desktop Underwriter may provide the identical response to all users who submit an inquiry to a lender. The same automated system may evaluate data from multiple sources and gradually learn to choose the optimal answer for every borrower with the use of artificial intelligence and machine learning.

AI’s Benefits For Mortgage Lending

The following are the most alluring applications of AI and machine learning from the perspective of lenders, per the Mortgage Lender Sentiment Survey released by Fannie Mae in October 2023:

Review of compliance
Fraud detection
Tailored loan products
Property appraisal
Verification and processing of underwriting data

In the meanwhile, borrowers might discover that AI streamlines the mortgage application procedure and lowers human error. This could lead to quicker judgments and potentially earlier closures. Virtual assistants and chatbots might offer round-the-clock client support, making it easy to look for loans outside regular office hours.

However, the advantages of AI are mostly hypothetical. According to the Fannie Mae poll, only 7% of lenders have used AI into their present mortgage process, despite the fact that 65% of them are aware of it. Twenty-two percent more say they are experimenting with AI solutions.

The possible drawbacks of this new technology could be the reason why so few mortgage companies are implementing artificial intelligence.

AI’s Drawbacks For Mortgage Lending

A major issue with many modern AI systems is hallucinations. Stated differently, these systems have a history of fabricating information and passing it off as fact. The largest danger associated with deploying AI, according to the lenders surveyed by Fannie Mae, is disinformation.

According to Woodhouse, “no AI-generated content can be used in production without a human review.” At the moment, Prosper does not employ AI for home equity lines of credit; instead, it only uses it for certain services associated with personal loan products.

The possibility of unintentional prejudice is another issue with AI. Although it could appear that a computer will make impartial choices, there are worries that bias could infiltrate its code or the information it uses.

The Consumer Financial Protection Bureau has released guidelines stating that lenders must give particular justifications for a denial to businesses that use AI to make lending decisions. The bureau stated in a press release that “creditors generally cannot state the reasons for [a mortgage denial] by pointing to a broad bucket.”

AI And Mortgage Customer Experience

AI in the mortgage sector may be most noticeable to customers when it comes to online chatbots and other customer support systems. These act as virtual agents that can respond to questions from both present and future clients.

“It seems like the chatbots are getting smarter and more robust every day,” Sless explains. At his company, however, chatbots are programmed to only respond to simple inquiries; human agents offer more complex information. According to Sless, “I still think people enjoy the personal touch.”

That was another conclusion from Ice Mortgage Technology’s 2023 Borrower Insights Survey. Just 9% of the more than 2,000 respondents polled by the data and technology supplier said they wanted mortgage borrowing to be entirely digital.

It is also unclear if consumers will accept or object to the idea of speaking with a virtual agent, even though technology is on pace to provide lenders the ability to offer AI-powered video chats. Advanced chatbots are more likely to be employed in the background to assist human representatives in promptly responding to inquiries and providing information.

AI In Underwriting And Servicing Mortgage Loans

Sless claims that identifying possible fraud and offering real-time transaction monitoring are two of AI’s advantages. Machine learning can be a useful tool for loan servicers to proactively spot issues before they become serious losses.

On the underwriting side, meanwhile, the dangers can be greater than the possible advantages. Government fines, punitive damages, and other costs may follow violations of the Fair Housing Act, which forbids discrimination in financing. Some businesses are reluctant to entrust underwriting decisions to AI because to concerns about unintentional bias.

Although “there’s going to be a long journey to get there,” Woodhouse notes that this does not exclude AI from eventually playing a bigger part in loan underwriting.

For the time being, some lending professionals are more interested in AI’s capacity to expedite procedures than in its capacity to evaluate credit risk or carry out other crucial underwriting tasks. It is hoped that this technology would lead to new prospects for consumer acquisition, engagement, and retention with the correct cues and inputs.