Measure and clear the exposure
created by autonomous economic agents
Entities assessed for autonomous systemic liability exposure across cyber, commercial, reinsurance, ILS, and specialty lines.
Autonomous Systemic
Liability Class
ASLC defines the liability class created by non-human economic actors operating continuously, without identity anchors, across interconnected systems. No existing actuarial, regulatory, or capital framework accounts for this class.
Autonomous Decision
Liability Gap
ADLG quantifies capital misalignment caused by ASLC exposure. Per entity. One number. The gap between declared capital and the capital actually required under autonomous agent exposure.
Example: Allianz SE — Declared capital $80.0B, ASLC-required $87.28B, ADLG $7.28B (Category C — Correlation)
ASL-ST01
Machine-Speed Autonomous Interaction Event (MSA-1)
Published 19 February 2026
Simultaneous autonomous decision failure across interconnected entities. All agents act on correlated signals at machine speed. No human checkpoint intervenes. Standard diversification assumptions collapse.
Sector-Adjusted
Distortion Indicators
Each ASLC category produces distinct capital distortion patterns. Benchmarks are calibrated per sector.
ASLC-AUIC Methodology v2.1
Capital data: FY2025 Annual Reports, Solvency II filings, Lloyd's Syndicate Returns, ILS fund disclosures
Exposure
Publication
Entity-level autonomous capital distortion. FY2025 declared capital. Updated continuously.
ASLC-AUIC-20260219
Independent analytical infrastructure for the measurement of autonomous systemic liability exposure.
Exposure scores and ADLG calculations are derived from publicly available capital data — annual reports, Solvency II filings, Lloyd's syndicate returns, and ILS fund disclosures. Entity-level assessments are published continuously.