1

Baseline Measurement

Establish a baseline, such as percentage of users who encountered a fraudulent experience.
Example: FADE (Fraud Activity Detection Exposure)
Rate = 31% “Nearly 1 in 3 users were exposed to fraud signals during their session.”

2

Why It Matters

Exposure ≠ Impact: Seeing a scam doesn’t always mean churn—but it’s a signal.
Users with high FADE scores had 18% lower retention
Long-tenure users exposed to fraud were 2.3x more likely to disengage
Fraud exposure correlated with drop in conversion rate in the same session

3

Balancing Automation + Human Insight

Automation flags high-volume fraud patterns quickly.
Human analysts uncover nuanced abuse and evolving tactics.

“The cost of fraud isn’t just financial—it’s trust erosion. That’s why balance is a superpower.”

4

Executive Lens: Turning Exposure into Actionable Metrics

Retention Impact: Quantify churn rates among users with high FADE scores vs. baseline.
Revenue Risk: Estimate lost conversions or revenue per % increase in FADE.
Trust Index: Track brand trust or NPS scores in fraud-exposed cohorts.
Efficiency Gains: Show ROI of hybrid detection (automation + human review) in reducing false positives and fraud losses.