Carrington Labs, a leading provider of credit risk analytics and cash flow underwriting models, has partnered with US fintech DigiFi, an AI-powered digital loan origination platform that offers a fully configurable, no-code environment for banks and lenders worldwide.
The partnership integrates Carrington Labs’ cash flow underwriting and credit risk solutions directly into DigiFi’s platform, enabling lenders to test and deploy cash flow-based credit strategies using Carrington Labs within existing DigiFi workflows. The integration accelerates setup times and supports more accurate, data-driven lending decisions.
Carrington Labs enhances traditional credit assessments by combining transaction data, credit bureau records, and lender-specific inputs to generate a more complete view of borrower risk. Its explainable AI models enable lenders to identify both risk and opportunity with greater confidence.
The new integration will allow DigiFi clients to access Carrington Labs’ product suite—including the Cashflow Score, loan term recommendations, and early-warning credit risk indicators—directly within their existing DigiFi workflows.
“Lenders these days are looking for opportunities to integrate alternative data and smarter analytics into their lending decisions, and Carrington Labs exists to fill that gap in the market,” said Jamie Twiss, CEO of Carrington Labs. “Partnering with a best-in-class provider like DigiFi allows them to access our capabilities quickly and easily, and existing DigiFi customers can add our analytics inside the system they already use and trust to accept applications.”
“By integrating Carrington Labs’ cash flow underwriting capabilities into our origination platform, we’re giving lenders instant access to deeper insights and helping our customers act on richer data from day one without any friction,” added Jorge Calderon, Executive Chairman at DigiFi.
Leveraging Carrington Labs’ solutions within the DigiFi platform will enable lenders to improve portfolio performance, increase approval rates and broaden access to credit by accurately assessing thin-file and non-traditional applicants.
