Housing MarketMortgageOriginationTechnology

Operational efficiency is primary motivation for lenders to adopt AI: Fannie Mae

Top recommended AI application ideas included compliance, underwriting and property valuation

Lenders that adopt artificial intelligence (AI) or machine learning (ML) into the mortgage lending landscape want to see operational efficiency, Fannie Mae’s mortgage lender sentiment survey showed. 

The survey found that lenders’ motivation to adopt AI and ML for operational efficiency has increased significantly (73%) compared to 2018 (42%) when Fannie Mae conducted a survey on the same topic.

AI and ML applications for the mortgage industry include automating and streamlining manual processes, detecting fraud and managing risk, among other tasks.

About 22% of surveyed lenders responded they started deploying AI or ML on a limited or trial basis, a jump from only 13% in 2018.

Top recommended AI application ideas included compliance, underwriting and property valuation.

“The latest results indicated that lenders most value AI applications that might help automate this sort of data processing and identify potential anomalies,” Peter Ghavami, VP of modeling and data science at Fannie Mae, said. 

“Given the rising costs of today’s business environment, AI applications intended to improve operational efficiency are clearly highly valued by lenders and could function as a starting point among industry stakeholders to encourage wider adoption.”

A total of 242 senior executives from 219 lending institutions completed the survey between Aug. 1 and Aug. 14. Lending institutions included mortgage banks, depository institutions and credit unions. 

When asked to recommend AI application ideas for the government-sponsored enterprises (GSEs) to develop for the mortgage industry, lenders pointed to appraisal automation, borrower income/employment verification, data/documentation reconciliation and standardization, and compliance management.

Among lenders who have not used AI or ML technology, the biggest barriers to adoption in 2023 remained the same as 2018. 

Lenders cited integration complexity with their current infrastructure, lack of proven record of success and high costs as barriers to adoption, Fannie Mae found.

Mortgage banks were more likely than depository institutions to cite integration complexity as a serious challenge. Data security and privacy concerns have also grown significantly since 2018.

Survey results also showed that, despite the growing ubiquity of AI and ML, mortgage lenders’ familiarity, current adoption status and adoption challenges with the technologies are largely unchanged over the last five years.

Nearly two-thirds of lenders (65%) in 2023 said that they are familiar with AI/ML technology, consistent with 2018 (63%). 

“As these technologies mature, we expect humans and AI/ML to play to their respective strengths within the mortgage industry, with the latter likely to handle more of the back-end processing and the former continuing to build and maintain the customer relationships necessary to drive sales,” Ghavami said. 

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