AI can read the mortgage file, but who decides which facts are true?

The increasing use of artificial intelligence in mortgage lending is raising questions about how to verify the accuracy of data. With AI able to quickly analyze large amounts of information, including payroll, loan origination system (LOS), tax, and bank data, lenders are facing challenges in determining which facts are true. This is particularly problematic when different sources provide conflicting information, leaving lenders to decide when evidence is supported or unresolved.

In the context of mortgage lending, accurate data verification is crucial to ensure that loans are approved for qualified borrowers and to minimize the risk of defaults. The use of AI can help streamline the process, but it also requires lenders to establish clear guidelines for evaluating evidence. This may involve setting thresholds for acceptable discrepancies between different data sources or developing more sophisticated algorithms to identify and weigh the reliability of various inputs.

As the mortgage industry continues to adopt AI and other digital technologies, it will be important to watch how lenders address the challenge of data verification. Specifically, we should look for developments in the areas of data standardization, validation protocols, and regulatory compliance. Additionally, industry stakeholders will need to consider how to balance the benefits of automation with the need for human oversight and review, particularly in cases where AI systems produce uncertain or conflicting results.

Originally reported by housingwire.com. ArchitectureNews adds analysis for real estate & property readers.