Checkr is buying Truv in a deal that reflects an increasingly urgent mortgage-industry problem: Artificial intelligence can make borrower documents look more convincing, but it cannot make the underlying income real.
The acquisition gives Checkr direct connections to payroll providers and financial institutions, allowing mortgage lenders to verify borrowers’ income, employment, and assets using consumer-permissioned source data rather than relying primarily on uploaded paystubs and bank statements.
Financial terms of the transaction were not disclosed.
Checkr, best known for its background-checking technology, has been moving into mortgage, tenant, and personal verification over the past year. The company said acquiring Truv will deepen its mortgage capabilities while advancing its broader effort to create a single verification platform for high-stakes financial and employment decisions.
“In an AI world, human verifications have become essential to nearly every industry, but too often they’re fragmented across different systems and providers,” Checkr co-founder and CEO Daniel Yanisse said in announcing the deal.
“Our vision is to build a single platform that helps businesses, government agencies, and individuals navigate those decisions with greater accuracy, speed, and confidence,” Yanisse continued. “Getting it right matters just as much for the organization relying on that information as it does for the person being verified. Bringing Truv into Checkr helps accelerate that vision.”
Verification Moves Closer To The Source
Generative AI has lowered the time, cost, and technical skill required to create polished but fabricated financial records. A paystub or bank statement can appear legitimate even when the underlying employment, income, or assets do not exist.
Truv’s technology is designed to bypass that problem by allowing borrowers to authorize direct connections to payroll systems and financial institutions. The company says its network reaches 96% of the U.S. workforce.
Rather than asking an underwriter to determine whether an uploaded paystub looks real, the platform can retrieve income and employment information from its source. Bank connectivity can similarly be used to verify assets and cash flow without relying exclusively on statements submitted by the borrower.
That does not eliminate the need for underwriting judgment. Payroll records, bank deposits, stated income, liabilities, and other information can still conflict. Direct-source verification can, however, give lenders an independent dataset against which borrower-provided information can be checked.
It may also allow discrepancies to be identified earlier, before they become last-minute conditions or threaten a closing.
Truv Had Already Been Expanding In Mortgage
Truv has been building its position within mortgage origination technology before the Checkr transaction.
In June, Truv integrated its income and employment verification technology into Pylon’s mortgage platform, allowing participating lenders to request verification during the application process. Truv is approved for Fannie Mae’s Desktop Underwriter validation service through Day 1 Certainty and for Freddie Mac’s Asset and Income Modeler.
Truv says its platform can verify payroll, bank, self-employment, education, and volunteer data through application programming interface connections to source systems.
“From day one, we’ve believed people should have greater visibility into and control over their own financial information,” Truv co-founder and CEO Kirill Klokov said.
“Checkr shares that belief of transparency and fairness, along with a commitment to making verification faster, more accurate, and more transparent,” Klokov added. “Together, we’ll bring trusted, accurate data to more organizations while creating better experiences for the people whose lives are impacted by these high-stakes decisions.”
AI Creates Both The Problem And The Sales Pitch
Checkr describes itself as an AI-powered verification platform, placing artificial intelligence on both sides of the transaction’s rationale.
AI can help verification providers interpret fragmented financial and identity data, automate comparisons, and flag inconsistencies. The same technology can also help bad actors create credible-looking documents and identities.
Checkr cited Fannie Mae investigative findings showing that income-related fraud accounted for 47.4% of identified mortgage fraud findings. Fannie Mae lists income, employment, asset, identity, occupancy, and liability misrepresentation among the fraud risks lenders are responsible for detecting.
For Checkr, acquiring Truv provides more of the source data needed to support those automated decisions. For mortgage lenders, the deal is another indication that verification is moving away from determining whether a document looks authentic and toward establishing whether the information can be confirmed independently.
