Story by Kenon Chen for HousingWire
These days I start every conversation with, “Yes, I have used ChatGPT,” just to get that out of the way for the sake of efficiency. The speed of discourse about Generative AI in all aspects of life from personal to business topics has been astounding. And while the use cases for generative AI as a consumer, such as internet searching, customer service and random poem writing for hours (who, me?) have been immediately obvious, specific application of this tech in the mortgage industry has been a more involved discussion.
The thing that separates Generative AI from other types of artificial intelligence is that it can create new types of patterns and data such as narratives, images and even code, based off of existing data used to train the model. The possibilities are endless; however, the risks are also plenty since models that are not properly managed and tested can produce biased or incorrect results.
The highly regulated nature of the mortgage industry, paired with the mandate of ensuring fairness in the process for borrowers, tends to give pause in terms of introducing new tech that is not always easy to explain. Like any other form of automation and modeling, effective controls that curate data input and robust regular testing of output results are essential to this tech being adopted. That being said, there are a couple areas where Generative AI could have a transformative impact, such as increasing underwriting explainability without adding inefficiency, and breaking out of our old patterns of thinking when it comes to solutioning.
The cost to originate a mortgage loan has continued to rise annually. According to the MBA, it cost an IMB $12,450 to originate a loan, on average, in the fourth quarter of 2022. So, the last thing lenders want is to add additional steps or cost to the loan process. However, recent public statements from regulators suggest that demand for visibility and transparency into underwriting decisions is increasing.
