Misaligned fraud strategy causing either excessive losses or blocked growth

$0.5M–$2M annually: app store suspension/delist risk; lost revenue during review period; payment method restrictions reduce conversion; reputational damage • $1.5M–$5M annually: overspending on high-fraud acquisition channels; false-positive blocks of good users reduce cohort quality; wasted budget on campaigns with high chargeback/fraud rates discovered too late • $1.5M–$6M annually: either fraud leakage (whale spenders' accounts compromised, bonus abuse drains margins) or false-positive blocks of genuine whales (higher LTV segments), killing AOV and repeat purchase rates

Analytics team builds separate models in R/Python; collaborates with Fraud team via email/Slack on feature engineering; no shared ground truth; rebuilds models quarterly without real-time feedback loop; uses Excel to track model drift • App Store Relations Manager must manually compile fraud prevention metrics (detection rate, false positives, chargebacks prevented) from multiple sources; creates quarterly report in PowerPoint; delays compliance response • App Store Relations Manager receives chargeback alerts from app store dashboard; manually reviews fraud tool logs to explain causation; writes email to Apple/Google support with manual summary; no automated linking of fraud decision to chargeback