use cases

Add cash flow underwriting without replacing your existing systems

Turn customer-permissioned transaction data into practical risk signals that fit alongside your existing bureau data, scorecards, policies, and decision engine.

The problem

Many lenders can access bank transaction data but do not have a practical way to turn it into a reliable credit risk signal. Raw transaction feeds can contain thousands of records, inconsistent descriptions, incomplete account coverage, and patterns that are hard to interpret through simple rules. The problem is not gaining access to more data; it is converting that data into stable, explainable, decision-ready risk information, without assuming the project requires replacing your decision engine or rebuilding your entire scorecard.

How Carrington Labs can help

Start with a standardized cash flow score
Cashflow Score gives a 1-100 transaction-based risk measure with explainable behavioral drivers you can use alongside bureau scores and existing models.
Or build a lender-specific model
For lenders with sufficient outcome data, transaction signals can be incorporated into a Credit Risk Model trained on your product and performance.
Focus on one workflow first
Begin with thin-file underwriting, borderline applications, manual-review queues, or a specific product, and validate before changing decisions.

How this fits in your workflow

Magnifying glass on an ID.
Customer connects accounts
The customer connects eligible bank accounts with permission.
A Computer.
Data becomes risk signals
Transaction data is prepared and converted into a score, model output, drivers, or financial metrics.
A Person giving a pitch infront of a graph.
Apply in your existing process
Outputs are delivered into your current decision engine, origination system, or analyst workflow; performance is measured before you expand.

Who is this for

Carrington Labs supports lenders aiming to responsibly expand access.
  • Digital lenders
  • Issuers
  • Fintechs
  • Financial Institutions

What Carrington Labs provides

Inputs it can use
Customer-permissioned (open banking) bank-transaction data, delivered with consent, alongside your bureau data and existing models.
Outputs it returns
A 1-100 Cashflow Score with risk segment and behavioral drivers, or a lender-specific model output, via API or batch.
You keep control
Carrington Labs delivers risk signals into your existing systems. You keep your decision engine, policy, and final decisions.

FAQs

Does cash flow underwriting replace a bureau score?
Not necessarily. Cash flow information answers different questions about current income, expenses, liquidity, obligations, and behavior. Many lenders use it alongside bureau data and internal risk models.
Do we need to replace our decision engine?
No. Carrington Labs can deliver risk signals into your existing decision engine, origination system, analyst workflow, or data environment.
What is the difference between Cashflow Score and a custom Credit Risk Model?
Cashflow Score is a standardized transaction-based risk score. A custom Credit Risk Model is developed for your product, data, population, and outcomes and can combine transaction data with other sources.
Can we start with one customer segment?
Yes. A focused pilot may begin with thin-file applicants, referred applications, manual reviews, or one product.
Does transaction data automatically improve underwriting?
No. Additional data is valuable only when it can be converted into stable, predictive, explainable signals and validated against relevant outcomes.

Related resources

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How to Lend to Thin-File Customers Using Cash Flow Data

Thin-file customers may lack traditional credit history, but they are not low-information. Learn how lenders can use transaction data, tailored credit risk models, financial health metrics, and offer sizing to make smarter credit decisions.

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Can You Underwrite Without a Credit Bureau? A Practical Guide for Modern Lenders

Can lenders underwrite without a credit bureau? Learn when bureau-free underwriting works, where it falls short, and how AI, machine learning, and cash flow analytics can improve credit risk decisions.

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Why Second-Look Underwriting Is a Practical Starting Point for Cash Flow Underwriting

Second-look underwriting is a contained way to test cash flow data on borderline applications before rebuilding your entire origination stack.

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The Real Opportunity in Cash Flow Underwriting Is Precision

Cash flow underwriting isn't just about inclusion. It's about precision, and how behavioral signal sharpens approval, pricing, and servicing decisions.

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Explore solutions

Cashflow
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Summary