Payment Disputes and Fraud Agents: What Banking Teams Need to Govern

Key takeaways

• AI agents can investigate payment disputes by retrieving transaction records, account history and supporting documentation, then flagging cases for human review.
• Fraud detection agents can analyze transaction patterns and flag suspicious activity, but the final fraud determination should remain with a human reviewer.
• Regulation E requires that banks provide timely investigation and written explanation for disputed transactions. Agent-assisted workflows must still meet those timelines.
• A governed agent workflow should log which agent investigated each case, what data it used, what it found, and what recommendation it made.
• The agent should have scoped access to account data—only the transactions and fields needed for the investigation—and should not be able to close disputes or block accounts without human approval.

Payment disputes and fraud investigation are resource-intensive processes. AI agents can reduce the manual work by retrieving records, analyzing patterns and flagging cases for human review. But the workflow must be governed to survive regulatory review and customer complaints.

What the payment dispute workflow looks like

A customer disputes a transaction—either as unauthorized (fraud) or as an error (wrong amount, wrong merchant, duplicate charge). The bank must investigate the dispute, gather evidence, and provide a written explanation within the timeframe required by Regulation E (generally 10 business days to investigate, or up to 45 days if the account is provisionally credited).

An AI agent can assist with that investigation. It can retrieve the transaction record, check the account history for similar transactions, retrieve merchant information, and assemble supporting documentation. It can flag cases that clearly meet one outcome (e.g., a duplicate charge that the merchant reversed) and cases that need human review (e.g., a pattern of disputed transactions that requires deeper investigation).

The agent’s job is investigation and recommendation, not final determination. The bank should retain authority to close disputes, issue credits or chargebacks, and block accounts if fraud is confirmed.

Fraud detection agents: pattern analysis, not final judgment

Fraud detection agents can analyze transaction patterns in real time or in batch—looking for unusual locations, unusual amounts, rapid sequences of transactions, or other signals that differ from the customer’s typical behavior.

These agents can flag suspicious transactions for human review. But the final fraud determination should remain with a human reviewer who can consider context that the agent may not have—customer calls, known fraud patterns, merchant relationships, or other factors.

A governed fraud detection workflow should log which agent flagged each transaction, what pattern it detected, what evidence it gathered, and what recommendation it made. The human reviewer’s decision should be recorded separately, with the rationale for accepting or rejecting the agent’s recommendation.

Regulation E and dispute timelines

Regulation E requires that banks investigate disputed transactions promptly and provide a written explanation to the customer. In general the bank has 10 business days to investigate; it can take up to 45 days (90 in some cases, such as new accounts, point-of-sale or foreign transactions) if it provisionally credits the account within those 10 business days.

An agent-assisted investigation workflow must still meet those timelines. The agent can speed up the investigation by retrieving records and assembling evidence faster, but the bank remains responsible for ensuring that the customer receives a timely response and a clear explanation.

If the agent recommends a particular outcome, the bank should still review that recommendation and ensure that the written explanation to the customer is accurate and complete. The agent does not relieve the bank of its regulatory obligations.

Per-case checklist

For each payment dispute or fraud case investigated by an AI agent, the bank should be able to show:

• Which agent and version investigated it
• What data it used (transaction records, account history, merchant information)
• What it found (evidence gathered, patterns detected)
• What recommendation it made (fraud confirmed, not fraud, needs more review)
• The human reviewer’s decision and the rationale
• The final outcome (credit issued, chargeback filed, account blocked, case closed)
• The written explanation provided to the customer
• Whether the investigation met the Regulation E timeline

This checklist is not a Regulation E requirement. It is a practical starting point for building dispute and fraud records that can survive regulatory review and customer complaints.

Governance controls for dispute and fraud agents

Dispute and fraud agents should operate within defined controls:

• Scoped access: The agent should receive only the transaction and account data it needs for the investigation. Access to full account history or customer data should be limited to what the investigation requires.
• No final authority: The agent should investigate and recommend, not determine final outcomes. The bank should retain authority to close disputes, issue credits, chargeback transactions, or block accounts.
• Evidence preservation: The agent should log all evidence it retrieves and all patterns it detects. This evidence should be preserved for the human reviewer and for regulatory review.
• Audit trail: Every investigation should be logged with the agent version, input data, findings, recommendation and reviewer decision.
• Regulatory timelines: The workflow should track investigation dates and ensure that Regulation E timelines are met. The agent can help by retrieving records faster, but the bank must monitor the timeline.
• Exception handling: If the agent cannot make a recommendation (missing data, ambiguous patterns, insufficient evidence), it should flag the case for human review.

These controls help the bank demonstrate that the agent operates within defined boundaries and that human reviewers retain decision authority.

Questions to bring to the governance review

The following is a suggested discussion checklist for dispute and fraud agents. It is not a list of requirements imposed by Regulation E or other regulations, and your compliance, legal and risk teams should determine which questions apply to your specific workflow.

• What data does the agent receive? Identify the exact transaction and account fields the agent uses for investigation.
• Is the access scoped to the investigation? Justify why each field is required for the specific case.
• What patterns does the agent detect? Document the fraud signals or dispute patterns the agent looks for.
• What happens when the agent cannot reach a conclusion? Identify the manual review process for ambiguous cases.
• Who owns the agent’s recommendations? Identify the risk, compliance or fraud team responsible for reviewing and approving agent outputs.
• How is the agent tested? Describe the test cases for fraud patterns, edge cases and false positives.
• What does the audit trail show? Confirm that it records agent version, input data, findings, recommendation and reviewer decision.
• How do you ensure Regulation E timelines? Describe the process for tracking investigation dates and customer notifications.

The right answer differs by bank. The key is to have answers before a regulator or customer asks.

From investigation to determination

The dispute or fraud agent is one component of a larger investigation workflow. The human reviewer who receives the agent’s recommendation still makes the final determination—whether to issue a credit, file a chargeback, block an account, or close the case.

If the agent operates within scoped access, documented patterns and a clear audit trail, it can reduce investigation time without adding regulatory risk. The final decision remains with a human reviewer, and the investigation record is transparent and reviewable. For a deep dive into building governed AI agents, see the Moring AI Governance hub.

See it worked through one case: the payment dispute walkthrough follows a single illustrative case step by step, showing what the agent prepares, what it is refused, who decides and what the record keeps.

Frequently asked questions

Can an AI agent close a payment dispute?

A governed dispute workflow should keep final authority with human reviewers. The agent can investigate the dispute, retrieve evidence and recommend an outcome, but it should not close the case or issue a credit without human approval. The bank remains responsible for the final determination and the written explanation to the customer.

Can an AI agent block an account for fraud?

A governed fraud workflow should keep account blocking authority with human reviewers. The agent can flag suspicious transactions and recommend blocking, but it should not block accounts without human approval. The human reviewer should consider context that the agent may not have.

Does Regulation E apply to agent-assisted investigations?

Yes. Regulation E’s requirements for timely investigation and written explanation apply regardless of whether the investigation is assisted by an AI agent. The bank remains responsible for ensuring that the customer receives a timely response and a clear explanation.

What should a customer be able to see about their dispute investigation?

If a customer asks about their dispute investigation, the bank should be able to show what evidence was gathered, what patterns were detected, what recommendation the agent made, and what the human reviewer decided. This helps the bank respond to customer complaints and demonstrate transparency.

How should a bank document fraud detection patterns?

Fraud detection patterns should be documented with their version, their risk or fraud basis, and the team responsible for approving changes. Changes to patterns should trigger a review, and the agent should use versioned patterns so that past decisions can be traced to the patterns in effect at the time.

What happens if the agent cannot reach a conclusion?

If the agent encounters missing data, ambiguous patterns or insufficient evidence, it should flag the case for human review. The workflow should not fail silently or make a determination on incomplete information.

Sources

• Regulation E: Electronic Fund Transfers
• CFPB: Managing Your Money: Disputing a Charge

Frequently asked questions

About the author

Arya SharanProduct Marketing & GTM, Moring AIChennai

Owns product marketing and go-to-market at Moring AI across positioning, demand and enablement. Works with regulated buyers on how governed AI agents are scoped, evaluated and bought. Writes about the operating questions that decide whether an agent reaches production.

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