What Are Cashflow Scores?

Credit risk models are changing. Traditional credit scores, built on lagging and limited data, aren’t designed to evaluate how someone manages their money today. Cashflow scores fill that gap. They use real-time financial data to help companies assess risk with greater speed, precision, and inclusivity.

A New Lens on Creditworthiness

Why Traditional Credit Scores Are Falling Short

Credit scores like FICO were built to serve a different era of lending. They rely on historical data that’s often outdated, missing the nuances of how someone earns and spends today. This creates blind spots especially for gig workers, recent immigrants, and others without deep credit files. As new financial products emerge, traditional scoring methods fall further behind.

Enter Cashflow Scores

Cashflow scores shift the focus to real-time behavior. They analyze bank transactions to evaluate current income, expenses, and account health. By zeroing in on recent patterns—like income timing and bill obligations—cashflow-based models provide highly accurate insights into what’s likely to happen in the next few days or weeks.  For lenders operating on tight repayment windows, that distinction matters.

How Cashflow Scores Work

Data Sources That Power the Model

Cashflow scores pull data from bank aggregators like Plaid, MX, and Quiltt. These aggregators give credit risk teams access to applicant checking accounts, direct deposits, bills, transfers, and subscriptions. With this data, risk models can detect income frequency, identify financial stress, and observe repayment behavior. Unlike credit bureau data, it’s updated daily, not monthly.

What These Scores Measure

These scores go beyond basic cash-in, cash-out math. They evaluate the health and reliability of a user’s financial behavior by looking at patterns over time. These models consider signals like whether

• Income is stable (e.g., received on a regular cadence like payroll deposits)
• Expenses are predictable and manageable
• User has enough buffer to meet upcoming obligations
• Repeated overdrafts or repayment to multiple short-term providers

Beyond Rank-Ordering: Product-Specific Predictions

Cashflow scores use real-time bank transaction data to evaluate a person’s financial health—offering a more current and accurate view than traditional credit reports. But the most effective cashflow scores do more than just rank-order general repayment risk.

They’re called Product-Specific Probability Scores, and they’re designed to predict outcomes tailored to specific financial products—like the likelihood of repaying the first four installments of a small dollar loan or determining affordability for a charge card. A good score for a $1,000 loan won’t look the same as one for a credit card. This level of specificity helps teams make sharper decisions, improve approval rates, and better match users with the right financial solutions.

Why Lenders Are Turning to Cashflow Scores

Real-Time Visibility → Faster, Smarter Decisions

Lenders need answers quickly—especially when working with new or underserved customers. Cashflow scores help approve more applicants without waiting for credit reports to catch up. They make it easier and more accurate to assess someone’s financial position at the moment of decision. With bank transaction data, risk teams get a real-time view into likelihood to repay as customer behavior changes.

Increased Access Without Increased Risk

Cashflow Scores allow companies to approve more users without raising default rates. By analyzing patterns like consistent rent or loan payments—even when income is nontraditional— they can identify strong candidates who might have been overlooked by credit bureau data. For example, a user with volatile income but consistent rent payments may be a healthier applicant than their FICO score suggests. The result: higher approvals, better conversion, lower losses.

Operational Wins for Risk Teams

Cashflow scores reduce manual reviews by surfacing key signals—like income volatility, recurring shortfalls, or stacking risk—upfront. Out-of-the-box attributes and purpose-built models allow teams to plug in quickly and customize as needed, accelerating time to value. Real-time signals help risk teams proactively detect issues like loan stacking or early delinquency.

Use Cases Across the Lending Stack

Earned Wage Access and Pay Advances

For EWA providers and instant pay platforms, repayment timing is everything. Cashflow scores detect income deposits and help align repayment schedules with real paydays. They also surface signals like additional unconnected accounts or advance stacking that increase risk. This helps providers approve more users while maintaining high repayment success

Small Dollar and Personal Loans

In short-term credit, the ability to repay the first few payments is often the best indicator of long-term performance. Cashflow scores let lenders model the likelihood of repaying payments 1 through 4. Lenders can swap out low-quality approvals while unlocking new segments previously declined under FICO cutoffs. This improves approval efficiency without compromising risk.

Credit Builder and Charge Cards

For secured or starter cards, cashflow scoring supports more dynamic underwriting. Providers can set credit limits that adjust to a user’s real-time financial capacity. These models can also monitor ongoing usage patterns and payment behavior to guide future limit increases or decreases. It’s a more adaptive, data-driven way to help users build credit responsibly.

SMB and Self-Employed Risk Scoring

Traditional documents like tax returns or profit/loss statements take time to collect and review, and often contain manual errors. Cashflow data offers a more accurate and automated path. Lenders can verify income, measure cash reserves, and understand how a business manages working capital all from connected accounts. This unlocks financing opportunities for small businesses and freelancers often overlooked by legacy models.

Getting Started with Cashflow Scores

Easy Integration into Existing Models

Cashflow scores are accessible via API and can be tested alongside existing rules or models. Providers like Pave offer pre-built integrations with platforms like Taktile, Alloy, Oscilar, and LendAPI, plus support for Snowflake delivery. Real-time webhooks and custom endpoints give teams flexibility to plug into any underwriting flow. It’s easy to test in parallel before a full rollout.

From A/B Tests to Full Rollouts

Most teams start with an A/B test: compare performance between current models and cashflow scores. Once uplift is proven, scores can be operationalized into production. This can mean replacing FICO at an earlier part of the funnel, or simply layering cashflow-based rules on top. Either way, the result is faster decisions, higher accuracy, and better portfolio outcomes.

Final Take: Rethink What Makes Someone Creditworthy

A borrower’s true potential is visible in how they manage money day to day. Cashflow scores make that data usable. They offer lenders the precision and speed needed to approve more customers without increasing risk, and help underserved segments get access to the financial products they need.

By aligning underwriting to how people actually earn and spend, cashflow scores unlock smarter decisions and stronger relationships.

👉 Book a demo to see how your team can make faster, more inclusive decisions, driven by real behavior, not assumptions.

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