Topic starter
12/07/2026 12:18 pm
TL;DR: Fraud cost U.S. companies an average of 3.3% of annual revenue in 2025, while 84% of those losses hit revenue directly or indirectly, according to Sift. The practical lesson is that fraud prevention now has to be treated as a revenue-control and identity-risk problem, not just a detection function.
Editorial analysis by NHI Mgmt Group, based on content published by Sift: “Get the Fraud Out: How Sift Helps Businesses Stop Fraud Before It Hits Revenue”.
By the numbers:
- U.S. companies lost an average of 3.3% of annual revenue to fraud in 2025.
- 84% of those losses affected revenue directly or indirectly.
Key questions
Q: What breaks when fraud controls are too rigid?
A: Rigid fraud controls block legitimate customers, raise abandonment, and increase manual review even when they reduce some fraud.
Q: Why do fraud and customer experience need to be governed together?
A: Because fraud decisions affect trust, conversion, and customer retention at the same time.
Q: How should payments teams measure whether fraud prevention is actually working?
A: Payments teams should measure fraud prevention with a small set of KPIs tied to both risk reduction and business impact.
Practitioner guidance
- Separate fraud loss from friction loss Track blocked legitimate conversions, abandoned sessions, manual review rates, and chargebacks in one business view so the programme can see total revenue impact.
- Score risk across the full journey Apply signup, login, transaction, and post-transaction signals in a single policy model so an attacker cannot move from one weak point to the next unchecked.
- Tune thresholds with business input Review policy thresholds with fraud, payments, customer experience, and identity teams so the response matches current attack patterns and acceptable customer friction.
Bottom line: Fraud prevention is no longer just about stopping bad actors because the control itself can now damage revenue when it creates avoidable friction.
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12/07/2026 12:32 pm
Fraud prevention has become a trust-governance problem, not only a loss-detection problem. Once fraud decisions affect approval rates, friction, and review load, they become part of the identity and access control plane. That means fraud, IAM, and customer experience teams are now managing the same trust boundary from different angles. Practitioners should treat policy governance as a revenue control discipline.
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 organisations prioritise automated fraud decisioning over manual review?
A: Organisations should prioritise automation when transaction volume is rising faster than review capacity, or when manual queues are causing inconsistent decisions and delayed fulfillment. Manual review still has value for edge cases, but it does not scale well in high-growth channels like travel and mobile commerce. Automation should absorb the routine cases so analysts focus on the highest-risk exceptions.
👉 Read our full editorial: Fraud prevention is becoming a revenue control problem