Topic starter
11/07/2026 8:24 pm
TL;DR: Manual review still has a role in ecommerce fraud detection, but Signifyd cites Merchant Risk Council data showing 35% of fraud teams want to reduce or eliminate it, and says merchants now screen twice as many orders digitally as manually. Human review remains useful for edge cases, but machine-led decisioning is becoming the operational default.
Editorial analysis by NHI Mgmt Group, based on content published by Signifyd: “Manual fraud review vs. AI: Best practices for merchants”.
By the numbers:
- 35% of fraud management teams cite reducing or eliminating manual fraud review as an area for improvement, according to Signifyd.
- A manual review costs $3.47 per transaction on average, according to Signifyd.
- A review-to-decline rate of less than 10% is a strong indicator to increase automation thresholds, according to Signifyd.
Key questions
Q: How should merchants reduce manual fraud review without increasing fraud risk?
A: Merchants should first segment transactions into stable, low-risk decisions and true exceptions.
Q: Why does manual fraud review become expensive at scale?
A: Manual fraud review becomes expensive because each case consumes analyst time, adds delay to order fulfilment, and increases the chance of inconsistent decisions.
Q: What are the signs that fraud review thresholds are too low?
A: A low review-then-decline rate is a strong sign that many cases sent to analysts could have been handled automatically.
Practitioner guidance
- Define review as an exception workflow Set explicit criteria for when a transaction leaves automated decisioning and enters human review, such as unusual value, mismatched identity signals, or high-risk geographies.
- Track review-to-decline performance Measure how many reviewed orders end in a decline and use that ratio to decide whether the automation threshold should move higher or lower.
- Use model managers, not manual clerks Recast fraud analysts as model managers who tune thresholds, monitor drift, and investigate the cases that automation cannot resolve with confidence.
Bottom line: Manual fraud review still has a valid role, but only as a bounded exception path when automated decisioning cannot confidently resolve a suspicious order.
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11/07/2026 8:54 pm
Manual review fatigue is a governance problem before it is a staffing problem. When fraud teams stay too dependent on human adjudication, the control stops scaling with transaction volume and becomes a bottleneck for both risk and revenue. The article’s central signal is that merchants are already moving toward digital screening because the exception workflow has outgrown the exception rate. Practitioner takeaway: design the operating model so humans handle edge cases, not the main line.
A few things that frame the scale:
- Nearly 60% of companies reported that fraud losses were still increasing in 2025.
A question worth separating out:
Q: When should human review still be part of fraud decisioning?
A: Human review still makes sense when transactions are unusual, high-value, or contain conflicting signals that require context a model may not capture well. It is best used as a bounded exception path, not as the main decision layer. The goal is to preserve expert judgment for edge cases, not routine approvals.
👉 Read our full editorial: Manual fraud review is giving way to machine-led decisioning