# False positives are a systems failure, not a risk win

**URL:** <https://community.rapyd.net/t/false-positives-are-a-systems-failure-not-a-risk-win/60055>\
**Category:** General\
**Tags:** open-discussion\
**Created:** [January 20, 2026, 5:58pm UTC](https://community.rapyd.net/t/false-positives-are-a-systems-failure-not-a-risk-win/60055 "2026-01-20T17:58:17Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![drew.harris](https://sea2.discourse-cdn.com/flex016/user_avatar/community.rapyd.net/drew.harris/32/1259_2.png) [@drew.harris](https://community.rapyd.net/u/drew.harris)\
**Post date:** [January 20, 2026, 5:58pm UTC](https://community.rapyd.net/t/false-positives-are-a-systems-failure-not-a-risk-win/60055/1 "2026-01-20T17:58:17Z")

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Your fraud system didn’t “protect revenue.”  
It interrupted a legitimate user flow.

From a developer perspective, false positives are unhandled edge cases showing up at scale.

**Takeaway:** If valid transactions are being blocked, the system is incomplete - no matter how strong the model looks on paper.

**Framework: FP as a First-Class Metric**  
If you treat fraud like infrastructure, you should be tracking:

- **FP rate** (legit tx blocked / legit tx total)
- **Resolution latency** (block → user success)
- **Retry fallout** (% users who never retry)
- **Support amplification** (tickets per block)

**Question for the community:**  
Which of these do you actively monitor today—and which do you wish you had better visibility into?