Cost per loan is a decision problem

Solutions

Common questions

What operators ask before the first call

How long before an AI agent in loan manufacturing pays for itself?

Stipulation clearing and fallout prediction typically show cost-per-loan improvement within one or two origination cycles, because the labor being displaced — document chase, re-verification — scales directly with volume. The bigger variable is origination volatility: the same automation that saves money in a high-volume quarter needs to keep paying for itself in a slow one, which is why we cost it against your worst realistic volume scenario, not your best.

What data do we need before we can start?

Access to your LOS or servicing system, a sample of historical files including the ones that fell out, and clarity on your current stipulation and condition definitions. You don't need a data warehouse or clean historical records — most of the value comes from reading unstructured documents and correspondence that's already messy, which is exactly the kind of work agents are built to handle.

How do we keep this auditable for investors and regulators?

Every automated borrower-facing action — a status update, a document sufficiency determination — is logged with the evidence that produced it, so it holds up under investor quality control review or a regulatory exam. We treat borrower communications the same way a compliance team already treats disclosures: documented, traceable, and reviewable after the fact, not just accurate in the moment.

Will this change how quickly we can react to rate or volume swings?

Yes, and that's often the more valuable outcome than the cost-per-loan number — agents don't need to be hired or laid off with volume, so the operation can flex without the lag and cost of staffing changes. That doesn't mean zero fixed cost, but it changes the shape of your cost curve relative to volume, which matters more in a cyclical origination business than a fixed percentage reduction.

How does this account for climate and insurance risk in underwriting?

Insurance availability and cost are increasingly the variable that moves an asset's real risk profile faster than rate does, and that data changes frequently enough that manual tracking falls behind. Agents can continuously monitor insurance cost trends, climate exposure data, and operating assumption changes at the asset level, surfacing repricing needs before they show up as a surprise at renewal or in a covenant test.

Perspectives