CUSTOMER: Personfiy

Applied Data Finance, via its online lending platform Personify Financial makes it easier for Americans to get the money they need through online personal loans that are clear, simple, and built to fit their lives. In an effort to approve more credit-worthy applicants, the company turned to optimizing real-time cash flow insights to strengthen its decisioning. What began as a cautious incremental approach became a meaningful shift in strategy, helping Personify scale bank data collection across the vast majority of applicants while improving its ability to assess repayment capacity and identify risk signals beyond traditional credit bureau data.

Problem: While Personify wanted to expand loan access to more borrowers who were not covered well by the traditional bureau, it struggled to consistently identify the riskiest profiles or fully understand a consumer’s ability to pay given their limited use of bank transaction data. 

Initially, the company was worried that expanding use of cash flow data requires bank linking in the application flow would increase abandonment, creating a tradeoff between richer data and customer conversion.

Solution: By implementing Plaid, Personify fundamentally changed the way it applied cash flow data to underwriting. Rather than relying on bank transaction data only in edge cases, the company integrated Plaid directly into the application flow and scaled usage to more than 90% of applicants. This allowed Personify to collect verified bank transaction data at scale and embed cash flow insights directly into underwriting and risk decisioning models.

With Plaid data and insights incorporated into its initial risk strategies, the company strengthened its ability to assess repayment capacity and identify risk signals that were not visible in traditional credit or incremental use of cash flow data alone. The shift moved Personify from a selective, reactive use of bank data to a core, proactive underwriting approach.

Key results:

• Personify scaled Plaid to power over 90% of all applicant traffic without impacting conversion, making verified bank transaction data a core part of its underwriting rather than an edge-case input.

• The company expanded approvals by up to 8% to underserved segments while maintaining strong customer conversion rates and maintaining credit costs.