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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteAI-assisted cash-flow underwriting can help a lender judge whether a business appears able to repay by examining money moving through its accounts: deposits, expenses, balances and, in some cases, individual transactions. A lender may combine those signals with conventional credit information, but the data reviewed and the way they affect a decision vary by lender. Cash flow alone does not guarantee approval.
What “AI cash-flow underwriting” means
Cash-flow underwriting uses information about a business’s inflows and outflows to help assess repayment capacity. The Federal Reserve describes both summary measures—such as monthly net cash flow, average deposits and account balances—and transaction-level information, such as sales and expenditures. Possible data sources include bank statements, deposit accounts and digital payment processors.
“AI lender” is not a precise category in the regulatory sources. They discuss alternative-data underwriting, complex algorithms and deposit-account activity, but do not identify a definitive list of current lenders using AI specifically to assess business cash flow. A lender may use automated analysis, conventional underwriting or a combination; the label alone does not establish what data it collects or how it makes decisions.
What business cash-flow information might be considered?
Depending on the lender and the data access granted, an assessment might use account-level summaries, individual transactions or both. The Federal Reserve’s examples include:
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- Monthly net cash flow and average account balances.
- Deposit amounts, frequency and regularity.
- Changes in average balances and account tenure.
- Overdraft history.
- Business sales and expenditures shown in transaction records.
These are examples of possible measures, not a universal checklist or proof that a particular lender uses a specific scorecard. The Federal Reserve compares some cash-flow measures with familiar credit dimensions such as payment history and amounts owed; that is an illustrative analogy, not evidence that every lender treats them identically.
How the information can feed into a loan decision
- Data are provided or accessed. A lender may ask for bank statements or permission to access account data. The Federal Reserve identifies bank statements and digital payment processors as potential sources, but does not establish a standard connection method or lookback period for all lenders.
- Account activity is turned into measures. The analysis may summarize deposits, expenses, balances or cash-flow patterns. If transaction-level data are used, sales and expenditures may also be considered. The specific inputs depend on the lender.
- Repayment capacity is assessed. Underwriting traditionally evaluates income and expenses to estimate whether repayment is manageable. Cash-flow information can add a view of money moving through accounts. Simple account measures may have an understandable relationship to repayment capacity; more complex models can process many data points.
- The lender makes a decision and sets any terms. Cash-flow information may be considered alongside credit-file information and other evidence. It can inform approval, denial or loan terms, but does not replace underwriting or the need for the business to repay.
The Federal Reserve’s October 2025 discussion describes cash-flow evaluation as a way to improve measurement of income and expenses, not as a guarantee of a particular outcome. The regulators’ materials do not establish a business-loan approval lift, default rate or pricing effect attributable to AI cash-flow analysis.
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How cash-flow analysis differs from a conventional credit file
| Question | Credit-file information | Cash-flow information |
|---|---|---|
| What it can show | Credit repayment history and other information in a credit file. | Account summaries or transactions reflecting deposits, expenses and balances. |
| What period it can illuminate | Credit history over time. | Account activity and operating cash movement during the period covered by the data provided or accessed. |
| How it may be used | As part of an assessment of creditworthiness. | As an additional view of income, expenses and repayment capacity, potentially alongside credit-file information. |
| What remains lender-specific | How a lender weighs credit-file details. | Which accounts and data are included, the analysis used and how much the results affect the decision. |
Neither method is established as universally more accurate or fair. The Federal Reserve and other regulators describe potential benefits from alternative data while also noting concerns about data quality, model performance and borrower understanding.
Will the lender see every business-account transaction?
That depends on the lender’s request and the information you provide or authorize it to access. A request for account summaries is not the same as access to transaction-level records. The sources do not establish a universal set of accounts, transaction categories or time period that every lender reviews.
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Before submitting an application, check the lender’s own permission and privacy terms. Find out which accounts are included, what information is accessed, how far back the review goes, and whether transaction-level activity is part of the assessment. Do not assume that the term “AI” answers those questions.
Potential advantages—and the limits behind them
What cash-flow data could add
Regulators say alternative data may improve the speed and accuracy of decisions and help evaluate applicants who might not obtain credit through mainstream systems. The Federal Reserve also discusses possible benefits such as identifying borrowers who are difficult to assess through traditional credit files and making parts of the process more convenient. These are potential outcomes, not quantified results for business-loan applicants or promises that a particular business will qualify.
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Why the analysis can be incomplete or difficult to interpret
- Data access and quality: Account access can be unreliable, and records may be inconsistent or poorly structured. Third-party data can also be costly.
- Uneven business conditions: The Federal Reserve notes that many alternative-data models have not been tested through a full business cycle. Their performance in a downturn may therefore be uncertain.
- Limited visibility for the applicant: A business may not know which accounts or transaction patterns mattered unless the lender explains its process or identifies the basis for a decision.
- More data do not remove risk: Cash-flow measures can supplement conventional information, but they do not eliminate underwriting, risk controls or repayment obligations.
What to do if a lender denies the application
Under CFPB guidance, creditors must provide specific reasons for adverse action that accurately reflect the actual basis for the decision, even when they use complex algorithms. The CFPB’s guidance does not create a special exemption for AI. It also does not mean that a borrower is entitled to source code or a complete explanation of the model.
Review the stated reasons and check whether the underlying business or account information is accurate. If you find a factual error, ask the creditor how to correct it and whether corrected information can be considered. A stated reason should describe the actual basis for the adverse action; a generic reference to an algorithm does not substitute for a specific reason under the CFPB guidance.
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What the regulatory sources do—and do not—establish
A 2019 joint statement by the Federal Reserve, CFPB, FDIC, OCC and NCUA defines alternative data broadly and includes cash-flow data derived from bank-account records. It discusses possible benefits when alternative data are used consistently with applicable consumer-protection law; it does not certify a particular lender or model.
Separate interagency principles for responsible small-dollar lending identify deposit-account activity as one possible way to assess creditworthiness, including in lending for small-business purposes. Those principles apply to supervised banks, savings associations and credit unions offering responsible small-dollar loans; they are not a general description of every business term loan or nonbank lender.
CFPB Regulation B § 1002.107 addresses specified data collection and reporting for covered small-business credit applications. It is reporting context, not a requirement that every lender collect transaction-level bank data. Applicability and effective requirements depend on the institution and current rules.
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Questions to ask before sharing account data
- Which business accounts and data will be reviewed, and are transactions included?
- What period does the information cover, and how can you correct inaccurate or incomplete data?
- How will the lender use the information alongside credit-file or other application details?
- If the application is denied, how will you receive the specific reasons for the decision?
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