ACH fraud monitoring and settlement lag: what merchants need to change

TL;DR: ACH internet payments reached 11.41 billion transactions totaling $6.98 trillion in 2025, while Nacha’s new rules now require fraud monitoring across the ACH ecosystem for originators and service providers, according to Riskified and Nacha. Settlement lag, return-code tracking, and differentiated fulfillment are becoming the practical controls that determine whether merchants can absorb fraud without damaging customer experience.

NHIMG editorial — based on content published by Riskified: ACH fraud monitoring, settlement lag, and the new Nacha rules

By the numbers:

• The FTC tracked $12.5 billion in reported fraud losses in 2024 and $15.9 billion in 2025.
• Lack of credential rotation is cited as the top cause of NHI-related attacks by 45% of organisations, followed by inadequate monitoring and logging (37%) and over-privileged accounts (37%).

Questions worth separating out

Q: How can merchants reduce fraud without blocking good customers?

A: Use layered controls that reserve strict checks for combinations of risk, not single signals.

Q: Why does ACH settlement lag create more fraud risk than card payments?

A: Because value can be released before final settlement, which gives fraudsters time to exploit the gap between verification and return.

Q: How do you know if ACH fraud monitoring is working?

A: Look for measurable reduction in losses, fewer false approvals in high-risk segments, and consistent analysis of return-code patterns across all entry types.

Practitioner guidance

• Separate verification from release decisions Do not treat account validation as permission to fulfill.
• Monitor return codes across all ACH entry types Build a single fraud telemetry view for R01, R07, R10, and R29 events so your team can see whether fraud is shifting across payment categories rather than only in WEB debits.
• Add transaction-level decisioning to identity checks Combine account ownership validation with velocity, amount, device, and historical behaviour signals before approving fulfillment.

What's in the full article

Riskified's full article covers the operational detail this post intentionally leaves for the source:

• How Riskified applies approve or decline decisions to ACH transactions in practice.
• How the instant versus delayed fulfillment recommendation is used to reduce exposure.
• How financial guarantee coverage works when an approved ACH payment is later returned.
• How the article maps return codes and fraud signals to specific decisioning outcomes.

👉 Read Riskified's analysis of ACH fraud monitoring and fulfillment timing →

ACH fraud monitoring and settlement lag: what merchants need to change?

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