Candor Technology Launches First-Ever Loan Quality Services Underwriting Engine

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To further help its clients transform their business models, Candor Technology has introduced its first-ever automated underwriting engine for loan quality services (LQS).

This will enable clients to adapt to current market conditions while still offering borrowers best-in-class service.

Candor’s LQS addresses many pressing concerns such as QA’s impact to fallout, QC impact to loan profitability, leakage of recurring defects from QA to QC, and originator’s quality ranking with investors.

LQS gives client members access to automation of numerous capabilities, including primary source document and data validation; thorough re-underwrite of income and asset; application of guidelines and overlays; defect identification and resolution; and reporting and repurchase defense data.

Clients can monitor for defects in real time, mitigate repurchase risk and achieve repurchase claim defenses.

“Our goal at Candor is to provide clients with cutting-edge technology solutions that enhance their business operations at a price that makes sense for their bottom lines,” says Tom Showalter, CEO of Candor, in a release. “Now, more than ever, it is critical that we find ways to use technology to better serve consumers while keeping costs low. Our Quality Services do exactly that, and we’re proud to bring it to market.” 

The news follows the company’s announcement that its CogniTech decisioning platform was awarded a U.S. Patent earlier this fall.

The CogniTech platform uses Expert Systems, Natural Language Processing, and other AI techniques to successfully reproduce the critical thinking of an underwriter, thus effectively reducing the cost and time it takes to close a home loan.

“Candor is dedicated to finding new and innovative ways to leverage technology to enhance the lending process,” Showalter says. “We work passionately every day to uncover the in-numerous ways that data and analytics can be used to better the lending lifecycle.”

Photo: Bill Oxford

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