Tool 06 · TOOL 06
Quantify the logical concentration of your AI insurance portfolio by foundation model. Identify silent exposures from cross-model dependencies.
Accumulation Index
Significant accumulation, action recommended
Model × Lines of Business Heatmap
| P&C | Cyber | |
Model PML by foundation model (M€)
EU AI Act Flags
Top 3 insights
Critical concentration: 100% of the AI book sits with OpenAI / Microsoft Azure. An unplanned outage triggers a correlated loss across the full perimeter.
HHI of 10000: high concentration by OECD thresholds. Systemic accumulation risk is non-diversifiable under the current configuration.
1 model(s) classified EU AI Act "high risk" (GPT-4o) with no compliance check. Exposure to Article 6 and DORA sanctions before August 2026.
HHI Concentration
OECD thresholds: < 1,500 diversified, 1,500-2,500 moderate, > 2,500 high.
Correlated outage scenario
If OpenAI / Microsoft Azure is unavailable 24h
Estimate based on declared integration depth (24h outage hypothesis).
Accumulation formula: score = min(100, sum(% book x usage coeff) + concentration and compliance penalties). Coefficients: Underwriting 1.5 / Claims 1.4 / Compliance 1.3 / Risk 1.2 / Service 1.0.
Model PML: PML = (% book / 100) x premium volume x usage severity factor. Factors: Underwriting 0.8 / Claims 0.7 / Compliance 0.5 / Risk 0.6 / Service 0.3.
EU AI Act:Indicative risk levels based on model capabilities and declared use. Not a substitute for legal analysis.
HHI : Herfindahl-Hirschman Index computed on provider exposure shares. OECD thresholds: < 1,500 diversified, 1,500-2,500 moderate, > 2,500 concentrated.
Integration depth: Scale 1-5 representing model substitutability: 1 = stateless API (replacement in hours), 5 = internalized proprietary model (migration > 30 days). Score impact: +4 pts per level.
Results depend on entered parameters and do not constitute a certified accumulation risk assessment.
Illustrative research tool, not certified. AlgoPolis, 2026.