Modern lenders often tout automation as the ultimate virtue. Many tech-driven private credit funds boast that automated underwriting can approve million-dollar loans to sponsors in minutes, relying on vast datasets and valuation algorithms to deploy investor capital. While this low-friction approach may work well for standardized consumer loans, real estate-backed private credit is far too complex—and far too high-stakes—for a “black box” approach.
Underwriting requires more than data—it requires experience. While a spreadsheet can calculate a loan-to-value ratio or project a debt service coverage ratio, it cannot meet a developer in person, walk a job site, capture the nuances of local processes, or detect optimism embedded in assumptions.
For accredited investors interested in real estate private credit funds like the DLP Lending Fund and DLP Preferred Credit Fund, understanding the difference between automated and algorithmically driven lending versus relationship-driven lending using data underwriting is key. True risk mitigation requires a hybrid approach: using data to verify the math, but relying on human judgment, local market knowledge, and deep industry experience to verify the reality.
More fiction has been written in Excel than in Word
In private credit, particularly in construction and development lending, mitigating risk takes looking at more than financial metrics.
A project might look flawless on paper—boasting strong margins and a healthy equity cushion—but responsible lenders know that’s only part of the story. It’s why complex models with too many variables or overly optimistic forecasts risk precision without accuracy.
“It is better to be roughly right than precisely wrong.” – John Maynard Keynes, 20th century economist and the “father of macroeconomics.”
The most significant risks in development often lie in the intangibles:
- Sponsor Character: Does the borrower have the integrity to prioritize debt service over their own profit?
- Operational Resilience: How has this team handled adversity in previous business cycles?
- Local Nuance: Is the project designed to meet the demand of the local demographic or is the product too scaled up or down for the area?
Experienced lenders recognize that evaluating financial metrics is necessary but not sufficient for underwriting. That’s because the sponsor—the team behind the project—is often the most critical factor in private credit.
“When it comes to underwriting sponsor risk, the most important things are the depth of the borrower’s experience, their ability to execute, time and time again, and their financial ability to back things up if there are challenges down the road.” – Dean Kirkham, President of Lending at DLP Capital
Why relationships matter in lending
If an algorithmic lender sees a healthy set of personal financial statements and a track record of success, it may advance the borrower based primarily on surface-level indicators. A human underwriter takes it a step further by verifying additional information, including how the sponsor’s wealth was built and who contributed to its growth.
Relationship-driven underwriting involves treating the borrower’s reputation as a form of qualitative risk mitigation. Background checks are conducted to look for past litigation or bankruptcy, which signal how a sponsor operates under pressure.
Public records aside, evaluating the sponsor’s credibility within the industry is just as important. Before committing capital, a disciplined lender requests references and proactively calls other lenders, suppliers, and partners in the market who have worked with the sponsor.
“One of the more intangible things that we do in this business is that we talk to our relationships in the market to evaluate whether a sponsor can do a transaction. This is simply something an algorithm cannot do” – Dean Kirkham, President of Lending at DLP Capital
Case study: The perfect deal that wasn’t
Relying on manual due diligence and human relationships sounds disciplined in principle. But can it prevent costly mistakes in practice?
DLP Capital’s lending team recently put the firm’s human-driven data underwriting approach to the test when evaluating an opportunity that, on paper, appeared sound. Both the sponsor’s financials and the business plan made sense.
Rather than relying solely on the data, the team went a step further and leveraged their network:
- They reached out to a known contact who had previously done business with the borrower.
- They received transparent feedback.
- They made four additional calls to trusted relationships in the market to corroborate the story.
Despite the project’s theoretical profitability, DLP Capital’s lending team discovered character risks that a model would have missed. Leveraging this knowledge, the team decided the deal was not a risk worth assuming and did not extend the loan. This ability to exercise judgment and discernment to say “no” to an opportunity that looks good on paper is a hallmark of defensive lending.
Local market expertise: Understanding the situation on the ground
Real estate is hyper-local. While a zip code analysis can reveal information about population growth in Charlotte, it cannot provide insight into the challenges of a muddy site with a 50-foot drop-off in North Carolina.
To mitigate execution risk, private credit funds should have “boots on the ground” to validate assumptions with local market experience. DLP Capital puts this into practice by employing originators, relationship managers, and appraisers who live and work in the markets where the firm lends, including Dallas, Charlotte, and Jacksonville.
This local market intelligence allows lenders like DLP Capital to:
- Understand Jurisdictional Differences: Entitlement and permitting timelines vary from city to city, even for those in close proximity.
- Verify Construction Costs: The budget is validated based on current local labor and material rates, rather than national averages.
- Gauge Sponsor Reputation: Understanding how local contractors and industry peers view the borrower.
Vertical integration as a hedge against risk
The final layer of human-driven risk management is technical expertise. Generalist lenders can lack the in-house knowledge to challenge a borrower’s construction timeline or budget because they aren’t operators themselves.
Lenders that are vertically integrated like DLP Capital—meaning they also develop, build, and operate real estate themselves—possess a distinct advantage. When a lender also manages active developments, their lending officers have the advantage of walking down the hall to consult with their own construction management team.
This peer-to-peer reality check and interdepartmental expertise ensure that loans are underwritten based on feedback from operators rather than the lender’s evaluation of the deal alone.
“If the opportunity isn't clearly straightforward, we’ll dig in very deep and rely on the expertise of our development and construction team. That’s the advantage of our vertical integration: it allows us to evaluate the risks of the deal before we even get going and enables us to conduct much more thorough due diligence than most other lenders.” – Don Wenner, Founder & CEO of DLP Capital
Lending risk: The accredited investor’s perspective
Despite the push towards automation, technology remains a tool, but it is not a substitute for human judgment or expertise. Algorithms can process data, but they cannot assess character, navigate local politics, or foresee execution challenges on a construction site—factors that can make or break a complex private credit deal.
Private credit funds that prioritize relationship-driven underwriting, a local market presence, and deep sponsor due diligence may offer accredited investors a level of protection that automated data alone cannot provide. After all, it’s the integrity and capability of the sponsor that offers reliable security for a loan.