The Fraud KPI Most SIU Teams Should Track: Your Decline Overturn Rate
SIUs measure fraud caught and savings booked, but not how many declines get reversed. Why your decline overturn rate is the KPI that matters most.
SIUs measure fraud caught and savings booked, but not how many declines get reversed. Why your decline overturn rate is the KPI that matters most.
Still tracking fraud cases in spreadsheets? Here’s what it actually costs an SIU team in time, errors and lost audit trail.
SIU case management bottlenecks rarely come from a lack of technology or headcount. They come from four repeatable failure points: triage queues, lost handoffs, invisible workload, and scattered case data.
Most SIU case management tracks cases, not the people working them. Here’s why that blind spot concentrates backlog and burnout on a few investigators, and what workload visibility actually fixes.
Detection fills the queue; fraud referral conversion decides how much you actually save. Where counter-fraud savings leak between referral and outcome, and how to close the gap.
How long should a fraud investigation take? Realistic SLA ranges by case type, what delay costs under Consumer Duty, and how to hit deadlines without cutting corners.
A unified fraud investigation workbench brings the whole case onto one surface. What that changes for case visibility, consistency and investigator capacity.
Detection keeps filling the queue; the fraud alert backlog is where savings leak. Why more fraud alerts don’t mean more savings — and how to clear it.
Human-in-the-loop AI in fraud investigation means AI handles retrieval and drafting while a named investigator makes every material decision. What regulators and investigators both need, and why full autonomy stays rare.
FraudOps complements your detection stack: scores and alerts in, outcomes and enriched data back, live in weeks — not quarters.