NSFs from failed collections. Cash advance providers face losses due to insufficient funds in users’ accounts.
Model limitations. Earlier-stage providers lack enough default history. Later-stage companies face difficulty expanding to new segments.
Lack of history. No visibility into how a user repaid cash advances across competitive cash advances.
Reduce NSFs. Retrieve predictions and signals about a user’s income, balance trends, and cashflows.
Proven models. Leverage Scores trained on our growing dataset of cash advance repayments.
Historical performance. Access a user’s cash advance payment history across competitors’ apps. Offer new users 2-3X more in advances without increasing defaults.
Unlock comprehensive customer financial data for intelligent credit decisions.
Drive lift in risk models with 1000+ Risk & Affordability Attributes.
Predict borrower cashflow behavior built on billions of data points.
Personalize payment plans to prevent NSFs and overdrafts.
Set dynamic credit limits for credit and charge cards.
Supplement credit data with cashflow underwriting.
Project affordability scenarios for debt consolidation.
