.png)
Part 2 of the Cashflow Scoring Series
Earned Wage Access (EWA) products promise flexibility: give users access to the wages they’ve already earned, when they need it, not just on payday. But to deliver on that promise at scale, EWA providers face a fundamental risk challenge: knowing whether a user will repay an advance without introducing friction into the experience.
This is where cashflow scores come in. While Part 1 of this series introduced the broader concept of cashflow-based scoring, this post focuses on its impact within EWA, specifically why real-time affordability matters, how cashflow data can fill critical gaps in underwriting, and how providers are using it to boost repayment, reduce NSF rates, and increase user trust.
The Real Risk in EWA Is Timing, Not Creditworthiness
Traditional credit scores were built to assess long-term repayment risk typically over the life of a multi-year loan or revolving credit line. But EWA is different. You're not evaluating whether someone will repay $15,000 over 36 months. You're assessing whether they’ll have $80 in their account next Thursday.
Many EWA users don’t fit the mold that credit bureaus were built for. They’re hourly workers, gig economy participants, or part-time earners. Some have multiple income streams. Others have irregular schedules. Many are thin-file or credit-invisible. Traditional tools don’t account for this complexity, and more importantly, they can’t provide real-time answers.
Why Cashflow Scores Fit EWA
Cashflow scores are built using live transaction data from linked bank accounts. They assess income stability, outflows, spending patterns, and signals of financial stress—providing a snapshot of how someone manages their money right now, not months ago.
For EWA providers, the biggest advantage is the ability to predict timing and availability of funds. A well-designed cashflow score doesn't just tell you if a user looks stable. It tells you if they’re likely to have the right amount of money in the right account when repayment is due.
These scores enable:
- Pay date prediction using historical deposit behavior
- Detection of irregular or inconsistent income streams
- Risk signals from outflows, such as frequent overdrafts or high volatility
- Loan and Advance Stacking detection, surfacing users with multiple active advances or payday relationships
The Problem With Relying on Balances Alone
Some providers use a user’s account balance as a proxy for affordability. But this often leads to false confidence. A balance of $200 might look good until rent, utilities, and a car payment clear the next day.
Cashflow analysis goes deeper. It looks at patterns in expense timing, account volatility, and past repayment behavior to understand how likely a user is to have funds after obligations are met. It considers whether payday is approaching, how often a user gets paid, and whether their income sources are recurring or one-off.
It’s not just about how much money is in the account. It’s about when money comes in, what needs to go out, and what’s likely to be left when repayment is due.
Use Case: Aligning Repayment With Payday
One of the most impactful applications of cashflow scoring in EWA is repayment timing. Many NSF (non-sufficient funds) events occur not because the user can’t repay, but because the repayment was mistimed.
Pave’s Income Prediction Model detects paycheck deposits and forecasts the next pay date with over 90% accuracy. This enables EWA providers to time repayment to the most likely moment of fund availability, directly after income hits the account.
One leading provider used this model to shift from fixed repayment windows to cashflow-aligned collections. The result: a 27% drop in NSFs, without reducing approval volume.
Catching Risk Signals Early
Cashflow scoring also helps detect at-risk users before repayment fails. For example:
- A user who used to receive weekly deposits but hasn’t been paid in 10 days
- An increase in outbound P2P transfers, often a sign of account sharing or cash burn
- A second advance provider showing up in recent transactions
These are early indicators that risk teams can use to pause re-advances, adjust limits, or trigger additional verification. It’s a more responsive approach than waiting for chargeoffs to occur.
Improving User Experience and Retention
Users don’t want their accounts hit with surprise charges, especially if the funds aren’t there. Misaligned collection attempts damage trust—even when the advance terms are clear.
By using cashflow scoring to understand each user’s financial rhythm, EWA providers can offer a smoother experience: repayment that lands when it should, fewer overdrafts, and greater confidence in future advances. This builds stickiness and reduces support costs associated with failed payments or disputes.
Operational Efficiency for Risk Teams
Cashflow scores also reduce manual work. Underwriting teams no longer need to parse raw bank data line-by-line to evaluate gig worker stability. Instead, they can rely on pre-built signals and attributes:
- Consistent income detection
- Account volatility measures
- Repayment readiness scores
- Flags for high-risk behaviors (e.g., stacked advances, repeated NSFs)
These insights can be automated into existing workflows, enabling real-time approval and collection decisions at scale.
Why Cashflow Scoring Is a Competitive Advantage
Cashflow scores help risk teams identify reliable users who might be missed by credit-based rules while protecting against mistimed repayments, stacking, and emerging risk.
They’re not just a better underwriting tool. They’re a better user experience engine.
As income becomes fragmented and flexible, the ability to evaluate and predict live financial behavior, not just static credit history, will be essential to underwriting the next 100 million workers.
Next up in this series: how cashflow scores drive better performance in Small Dollar and Personal Loan underwriting. Want to see how EWA leaders are using these tools today? Book a demo.
.png)