The rush to automate commercial real estate lending decisions could lead to significant market inefficiencies, according to Philip Bennett, President of Bennett Capital Partners Mortgage Brokers, who warns that over-reliance on technology risks missing crucial deal nuances that only human expertise can evaluate.
“In commercial real estate lending, there’s no substitute for human judgment. I’ve seen deals that would have been rejected by any algorithm but turned out to be some of our best performing loans because we understood the broader context,” Bennett explains.
He points to several recent deals as evidence that automated systems often overlook critical qualitative factors that can determine success. A borrower’s track record and reputation, for example, may signal reliability in ways an algorithm cannot quantify. Local market dynamics, such as neighborhood trends or upcoming infrastructure projects, also play a decisive role in shaping long-term value. Similarly, the potential for property improvements, the strength of a management team, and the broader community development impact are all elements that require human judgment to properly assess.
Bennett advocates for a measured approach to lending automation. “Technology should enhance, not replace, the fundamental relationship between lender and borrower. The most successful lenders will be those who know when to rely on automation and when to dig deeper,” he states.
Critical areas requiring human expertise often extend far beyond what automated models can capture. Complex deal structures demand nuanced analysis that considers variables outside of standard underwriting frameworks. Unique property characteristics, from historic designations to zoning quirks, also require specialized knowledge. Market-specific factors, such as local economic drivers or shifting demand patterns, can only be fully understood by experienced professionals. Just as importantly, borrower relationships and tailored risk mitigation strategies rely on trust, insight, and adaptability — qualities that remain firmly in the human domain.
According to Bennett, successful lending depends on evaluating factors that algorithms struggle to quantify. The experience and track record of a management team can reveal stability and reliability in ways data alone cannot capture. Similarly, assessing a property’s improvement potential requires vision and contextual understanding that go beyond numbers. Local market knowledge, built through time and presence in a community, also provides insights into trends and risks often invisible to automated systems. Just as important are the relationship history between lender and borrower, and the borrower’s broader strategic vision, both of which require human judgment to fully appreciate.
Bennett suggests that the future of commercial real estate lending lies in combining technological efficiency with human expertise. “We need to leverage technology to handle routine tasks while preserving the crucial role of experienced professionals in making final lending decisions,” he concludes.
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