Book a Demo
Book a Demo
Post-payment recovery baseline replaced
1% improper-payment intercept opportunity
Pre-payment screening pressure addressed
A top-10 US health plan was operating a large national claims environment with $80B in annual claims volume and growing pressure to strengthen payment integrity performance.
The SIU had skilled investigators, but its operating model depended heavily on post-payment pursuit.
The problem was lack of systematic pre-payment risk scoring.
Claims moved toward payment without consistent fraud, waste, and abuse screening tied to claim value, provider risk profile, utilization patterns, and investigation logic.
High-risk claims could pass through, while investigators spent time sorting low-value or late-arriving leads.
The business impact showed up in poor recovery economics.
The plan recovered only $0.19 per $1 of confirmed fraud, and post-pay recovery became less effective as disputes, arbitration, provider consolidation, and legal involvement increased.
The executive trigger was a need to move from recovery activity to prevention control.
Leadership needed FWA Payor Analytics to score claims before payment, apply configurable thresholds, suspend or route high-risk claims, and let clean claims continue without unnecessary delay.
Novacis Digital deployed FWA Payor Analytics, a pre-payment fraud, waste, and abuse risk-screening solution built to score claims before payment release.
The solution combined Surveillance and Utilization Review dashboards, Fraud and Abuse Detection System logic, machine learning models, provider and member registries, and case management integration.
Claims were scored against configurable risk thresholds, then suspended, routed to SIU, escalated for medical necessity review, or cleared for payment based on flag type, claim value, and provider risk profile.
The technical differentiation was pre-payment decisioning, not retrospective reporting.
FWA Payor Analytics connected claim-level signals, provider behavior, utilization patterns, and investigation workflows in one governed layer before funds left the plan.
SIU and claims teams retained control over thresholds, case review, suspension decisions, and final claim disposition.
This shifted the operating model from pay-and-chase recovery to AI-guided pre-payment prevention with investigator-controlled decisions.
FWA Payor Analytics Capabilities
Pre-Payment Integrity Features
Novacis Digital implemented FWA Payor Analytics in two stages: a 6-week claims-risk pilot for pre-payment screening and SIU routing, followed by a 10–12 week enterprise expansion across the plan’s $80B annual claims pipeline.
The initial rollout focused on claims where provider behavior, utilization patterns, claim value, and historical investigation signals created the highest payment integrity exposure.
Early wins included claim-level FWA scoring, configurable suspension thresholds, SIU case routing, medical necessity escalation, and clean-claim pass-through.
This gave payment integrity and finance leadership proof that the plan could move from post-payment recovery activity to pre-payment prevention control while preserving investigator review and final claim disposition.
Addressed $800M in prevented improper-payment exposure under the plan’s 1% intercept scenario by scoring claims before payment release.
Shifted the control point from post-payment recovery to pre-payment action, giving investigators risk signals before funds left the plan.
Improved compliance readiness across 31-state pre-payment screening pressure, giving leadership stronger evidence of active payment integrity controls.
Screened the $80B annual claims pipeline using provider, member, utilization, claim-value, and investigation signals, proving execution at national health plan scale.
Reduced dependence on low-yield pay-and-chase operations, helping SIU teams focus earlier on high-risk claims and avoid late recovery disputes.
