IFRS 17 & Solvency II Compliant Unified Claims Forecasting Hub
Eliminate fragmented claims data silos with AI forecasting for accurate volume, severity, and reserves under IFRS 17/Solvency II (up to 23-day assessment gains)[5].
System Architecture
The Problem
Insurance teams face significant challenges from fragmented claims data across P&C, life, and health systems, hindering timely volume, severity, and reserve forecasts essential for premium setting and solvency[1][2].
This fragmentation across legacy policy administration, claims platforms, and actuarial databases creates reconciliation burdens, exacerbated by regulatory requirements like IFRS 17’s insurance contract measurement (including contractual service margin tracking) and Solvency II’s solvency capital requirement (SCR) modeling, alongside NAIC risk-based capital guidelines, risking non-compliance and forecast inaccuracies[3][5].
Current solutions rely on manual aggregation or siloed predictive analytics, failing to unify disparate sources effectively or meet regulatory audit needs, despite AI advances in isolated claims processing that achieve gains like 23-day reductions in complex assessments but lack cross-system integration[1][5].
Our Approach
See implementation details below.
Implementation Roadmap
Foundation & Single Line Pilot
Multi-System Integration & Regulatory Modules
Parallel Run & Validation
Production Deployment & Optimization
Technology Stack
Interface Previews
Conceptual UI mockups illustrating the end-user experience.
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