Cash Advance

Score users for cash advance

The Problem

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.

The Solution

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.


Cashflow API

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.

Find out how cash advance apps leverage Pave’s Cash Advance Scores to increase revenue up to 27%

Featured Posts

Interested in exploring more of this use case?

Explore other use cases

Reduce NSFs

Personalize payment plans to prevent NSFs and overdrafts.

Credit and charge cards

Set dynamic credit limits for credit and charge cards.

Cashflow Underwriting

Supplement credit data with cashflow underwriting.

Debt Consolidation

Project affordability scenarios for debt consolidation.