No industry stands to benefit more from AI and machine learning than the mortgage industry.
According to a whitepaper by LoanLogics, many lenders are devoting large sums of money to new technologies to improve data and document processing, but they may not be getting the most out of their new investment.
Some mortgage businesses “lack an understanding about the proper and practical applications of AI in the mortgage production process and have yet to reap its benefits of lowering costs, improving loan quality and providing a better consumer experience.”
AI is one of the least understood terms in the mortgage industry, the paper stated.
“AI is like a parent teaching a child who eventually makes his/her own judgement call and decisions, based on logical and cognitive reasoning.” Machine learning falls under the umbrella of AI and is meant to learn and improve as new information presents itself without needing more instruction.
Mortgage companies usually have to deal with a large volume of data, and according to the whitepaper, there aren’t many other industries that deal with as much information and differing regulations and guidelines as the mortgage industry. This means it’s important for lenders to be “tactical” when leveraging AI and machine learning.
A survey by Fannie Mae found 63% of lenders were familiar with AI and machine learning, and 27% are currently using the technologies.
Many of the lenders that are already using AI and machine learning use it for data and document processing, since one of the biggest benefits to machine learning is recognizing documents so that it’s easy to extract information.
Optical character recognition (OCR) technology is currently quite popular among lenders, according to the report, as it’s meant to save time and money that would otherwise be spent on manually inputting information into a system. While these tools are important, the whitepaper adds that machine learning tools are adding greater value and improving “transparency and auditability of loan documents and the accuracy of extracting the loan data found within them.”
The key to maximizing results is by blending OCR tools, machine learning and other data extraction programs, according to the whitepaper. This is defined as Capture 2.0 technology. “The global capture software market is expected to reach more than $11 billion by 2026,” the paper stated.
Machine learning tools allow lenders to evaluate loan quality more easily and in less time. “Properly leveraged, AI and machine learning tools can help lenders and servicers take full advantage of the digital mortgage, which has the benefit of improving the customer experience and lowering loan costs.”
Through this technology, information can be analyzed as fast as it’s collected. It can also help eliminate how frequently borrowers are asked for the same information multiple times, increasing the overall speed of the process.
The report says one of the biggest benefits to AI is the cost savings by automating tasks and reducing human capital, and therefore allow staff to refocus their attention and skills. The rise in AI will also drive higher demand for mortgage professionals who can instruct and guide AI and machine learning tools.
Lenders are doubling their auditing speeds and reducing loan processing times from hours to minutes, according to the report. “Not only has this resulted in lower costs, but it enables lenders to create stronger, more productive relationships with investors by delivering higher quality loans.”