Pave recently crossed 100 million monthly credit risk evaluations across our platform.
That number isn’t interesting because it’s large; it’s interesting because it shows how credit risk is actually evaluated today. Not simply because more people are applying for credit, but because far more of the customer lifecycle now requires a risk decision.
Credit products have always created ongoing exposure across servicing, limit changes, and account activity - not just at application. What’s changed is that risk is no longer evaluated once; it’s measured and acted on continuously as exposure evolves. As products become more dynamic, risk decisions increasingly occur far beyond origination.
Lenders who do this well see clear benefits: more approvals for the right customers, better payment outcomes, fewer delinquencies, and more revenue per account. Continuous risk evaluation also makes it possible to safely expand relationships by offering additional products when a customer’s needs evolve.
The result is higher lifetime value (LTV) - not because lenders are taking more risk, but because they’re managing it more precisely as customer behavior changes.
Reaching this scale reflects a broader shift. Risk evaluation is moving from a one-time origination decision to continuous decisioning throughout the customer relationship.
The limits of origination-only risk assessment
Traditional credit scoring was built for one-time lending decisions, primarily at origination.
A borrower applied, the lender pulled a score and made its decision. This model worked well for its intended use case: pricing risk at the point of application.
But as credit products evolved and supporting technology improved, risk decisions emerged throughout the customer relationship. These decisions are no longer edge cases; they define how modern credit products operate. As products became more interactive and usage-based, underwriting shifted from one decision to many.
Point-in-time snapshots at origination were never designed to answer questions like:
- Should this customer’s credit limit go up, down, or stay the same?
- Is this a good moment to attempt this payment?
- Was this payment failure about timing or real distress?
- Does this customer qualify for a different credit product?
- Which account needs attention before problems show up?
These aren’t annual-review questions; they can happen weekly, daily, and sometimes per transaction. They require visibility into near-term exposure risk as it changes.
Operating without that visibility has a real opportunity cost: limits stay static, access stays constrained, and customers who could have grown safely are forced to look elsewhere. Over time, the cost isn’t only higher losses—it’s missed growth and lower LTV across the portfolio.
Historically, cost-per-pull pricing made frequent evaluation economically prohibitive. Teams were forced to ration checks to select moments (applications or scheduled reviews) instead of embedding risk evaluation into routine actions like payment attempts or limit changes. Many of these decisions simply couldn’t exist because checking risk too often wasn’t viable. Per-pull economics were built for occasional checks, but modern credit creates many decision moments by default.
Credit is no longer a one-time decision
Modern credit products are more valuable when they behave like continuous risk systems rather than one-off transactions.
Consumers and businesses now draw repeatedly from revolving lines, charge cards, BNPL, cash advances, earned wage access, and net terms. Embedded and non-bank lenders extend credit inside workflows—inventory purchases, payroll runs, supplier payments—creating ongoing exposure rather than isolated applications. As credit embeds into these workflows, the number of risk decisions scales with activity, not applications.
Continuous evaluation enables repeat usage that increases LTV and improves CAC efficiency. Products respond to evolving financial situations, driving growth within existing relationships-typically with lower incremental risk and acquisition cost than new-customer growth. More usage creates more decision points, expanding both access and control.
Risk lives between transactions, not just at origination. And as usage increases, what used to be “servicing” becomes a core part of underwriting.
Why cost-per-pull pricing no longer works
Once risk needs to be evaluated continuously, pricing per pull stops making sense.
When access to risk signals is constrained, teams are forced to ration decisions. Pave’s usage-based subscription model reflects how modern credit actually operates. As decision volume expands from a handful of checks to many checks across the lifecycle, the unit economics of a “pull” stop matching reality.
When access to risk signals isn’t rationed, teams stop asking “can we afford to check risk?” and start asking “which decisions should be automated?”
Our usage-based subscription model serves this new reality: teams can finally add decision points where risk actually shows up, rather than where budget allows.
New risk decisions that drive higher LTV
Clients didn’t reach 100 million monthly evaluations by checking the same moment more frequently. They reached it by evaluating new moments that were previously invisible or ignored. The volume is a byproduct of expanding the set of decisions, not just speeding up the old ones.
Real-time credit limit adjustments
Borrowers can be re-underwritten as exposure changes, expanding purchasing power for creditworthy customers in real-time while avoiding unnecessary limit decreases driven by temporary cashflow timing. Limits become dynamic, not static.
Intelligent payment routing and ACH risk management
Unsuccessful ACH attempts frustrate borrowers as much as lenders. Evaluating the likelihood of a successful ACH attempt in near real-time increases collection success while reducing fees and customer friction. When payments become a decision point, risk is evaluated at the pace of payments.
Dynamic account management
Continuous evaluation during servicing helps distinguish between customers who are temporarily low on funds and those facing genuine repayment difficulties. This informs whether to reschedule a payment or escalate to collections and builds long-term trust. Servicing stops being reactive and becomes another place to underwrite responsibly.
Chime illustrates how continuous risk evaluation can power scaled lending by turning live behavioral signals into real-time changes in advance eligibility and amounts. Through products like MyPay, Chime dynamically adjusts advance amounts using signals such as repayment behavior and account activity, giving users access that reflects their current financial reality.
This always-on underwriting has powered a large lending business; since launching in 2024, MyPay alone has a roughly $300M annual revenue run rate. That’s the pattern: as the number of decision moments increases, lenders can expand access safely inside an existing relationship.
These decisions didn’t exist in a point-in-time risk model. They only exist when risk can be evaluated continuously.
What 100 million monthly credit risk evaluations validates
We are in a fundamental shift in how lenders operate, and this creates a new market for risk decisions:
- Risk scores embedded into payment, servicing, and growth workflows
- Continuous evaluation replacing calendar-driven checks
- Automated decisions triggered by live financial behavior
Most exposure—and most opportunity—lives after origination: between payments, limit changes, and servicing actions.
As payments, cashflow, and credit blur, the bottleneck shifts from models to infrastructure: systems that can measure near-term exposure continuously and trigger action.
As credit becomes continuous, risk evaluation must be as well. Near-term exposure can’t be priced once and assumed away; it has to be measured as capital moves.
Pave is building the infrastructure that makes continuous risk evaluation, and continuous growth, possible. And as risk decisions expand beyond origination into everyday workflows, the opportunity expands with them.
