Quantify GenAI Risk in Euros
The first Monte Carlo VaR/ES engine purpose-built for banks and insurers quantifying GenAI deployment risk under SR 26-2 and OCC 2026-13.
The GenAI Risk Quantification Gap
90+ Governance Vendors
All offer qualitative dashboards and policy templates. None quantify GenAI risk in monetary terms.
Regulatory Mandate
SR 26-2 and OCC 2026-13 require banks to measure and hold capital against GenAI model risk. Qualitative is no longer sufficient.
Deterministic Quantification
ModelQuant runs 10,000+ Monte Carlo draws on correlated failure-mode trees to produce VaR and Expected Shortfall in euros.
GenAI Failure Modes We Quantify
Hallucination
Fabricated outputs causing incorrect financial decisions or regulatory filings.
Jailbreak
Adversarial prompts bypassing safety guardrails to produce prohibited content.
Data Leak
Exposure of sensitive training data or customer PII through model outputs.
Bias / Drift
Systematic bias or distributional drift causing discriminatory or unfair outcomes.
Prompt Injection
Indirect prompt injection via third-party data sources compromising model behavior.
Adversarial Output
Manipulated outputs causing financial loss or reputational damage.
Run Demo Assessment
See ModelQuant in action. Click below to run a full Monte Carlo VaR/ES simulation on pre-seeded GenAI failure modes.
Click "Run Demo" to generate real VaR/ES quantification data.
Get Early Access
Join banks and insurers already quantifying their GenAI deployment risk with ModelQuant.