“Once the data is identified, the system can run a series of automated comparison checks or rules,” said Jennifer Fortier, principal at Stratmore.
Thank you for reading this post, don't forget to subscribe!Automated comparison checks could help solve one of the biggest issues in mortgage banking: a lack of trust in the data provided by borrowers and lenders.
Senior Garth Graham says, “We spend a lot of time and money trying to turn evidence usually provided in the form of images into data that we can use, then pass it on to the next person, Which doesn’t even trust the data.” STRATMOR’s partner said.
Ultimately, the lender packages the loan to sell to an investor who doesn’t trust any of the data in the file, and the process begins again, Graham noted.
According to Graham, if AI can verify for all parties including the lender, borrower and investor that the data is correct, the cost of loan origination will come down.
The average cost of loan origination reached a record high of $13,171 in the first quarter of 2023 as loan origination volume further declined. mortgage bankers association (MBA).
Other areas where AI could be beneficial to lenders include boosting conversion rates, improving the automated underwriting process, fraud detection and providing a personalized customer experience, the report said.
“AI needs to be powerful in the near term to handle even the most mundane tasks assigned to low-cost resources within lending organizations, especially for work that follows very predictable patterns,” said Brett McCracken, senior advisor at Stratmore. obeys.”
But when it comes to the question of when more lenders will adopt AI implementations, there are some hurdles that must be overcome. Concerns over data quality, regulatory compliance, model bias, lack of AI literacy, and potential job displacement are barriers to AI technology adoption.
In addition to potential legal and ethical challenges, lenders will need to review how workflows need to be changed to fully optimize the benefits of AI solutions. Lenders will also need leadership to understand what AI can and cannot do – and the lender will have someone in the shop who understands implementation to monitor and manage AI.
“I think AI may eventually replace most of the tasks faced by the non-borrower on mortgage lending. When AI can do more to emulate human thinking and intelligently evaluate questions that aren’t as simple as ‘pass or fail’, we will have reached a tipping point in AI,” Jennifer Fortier, principal at Starmore he said.
