model-risk

Open-source model inventory & governance. Discovers every model, rule, and pipeline across all your platforms as one immutable, agent-queryable graph — git for models.

A hands-on lab showing how “improving” a single metric (AUC/accuracy/F1) can worsen real-world outcomes. Includes metric audits, slice checks, cost-sensitive evaluation, threshold tuning, and decision policies you can defend, so dashboards don’t quietly ship bad decisions.

Governance patterns for autonomous AI agents in regulated financial services — DEFCON state machine, Sovereign Veto, Audit Chain, EU AI Act mapping

Control-plane architecture for AI & agentic systems: governance as admission control, decision admissibility, and audit-grade evidence.

Calibrated probabilistic market forecasting—from point-in-time data to decision-readiness evidence.

Evidence-based evaluation methodology for coding-agent configurations: statistics, evidence contracts, and fail-closed reporting with synthetic worked examples. No real-model performance claims.

Universal Analytics Engine: a dataset-agnostic BI platform with an embedded model-risk governance layer (PII detection, Canada AIA impact scoring, proxy-bias flags, integrity scorecard) designed around OSFI E-23. Governance architecture mine; Python/Streamlit AI-assisted. Live demo in the About link.

Model governance for insurance pricing — PRA SS1/23 validation reports, model risk management, risk tier scoring

C-DAG: replayable causal audit traces for high-risk financial AI decisions.

A benchmark for how AI models fulfill legal duties under pressure

Independent validation framework for CCP-style initial margin models, including VaR, margin add-ons, backtesting, stress testing, sensitivity analysis, procyclicality monitoring, and model-risk governance.

React + TypeScript oversight hub for model criticality, release gating, evaluation drift, and executive AI risk visibility

Reproducible benchmark of classical, neural and hybrid mortality models with rolling-origin validation and actuarial liability impact.

The first public LLM benchmark for Canadian financial regulatory compliance. Covers OSFI E-23, FINTRAC, B-20, IFRS 9, Basel III, PIPEDA, and CASL.

Governed, evidence-first research tribunal for falsifiable and reproducible quantitative claims.

MSc thesis (Tilburg University): measuring and controlling SHAP explanation instability in high-stakes AML/fraud models — 590k real transactions, 30-seed stability study, out-of-time validation

Research and diagnostic data documenting how historical disinformation, when encoded into AI and financial algorithms, ceases to be a narrative and becomes a Systemic Risk Contagion. Using the cannabis industry as a high-fidelity case study for model recalibration in emerging and stigmatized markets.

Credit default-risk model with SHAP-based ECOA adverse-action reason codes - interpretability and model-risk framing for regulated lending

Regime-aware quant risk and market stability monitoring framework.

Model risk validation sandbox for market & credit risk (VaR, ES, EL, backtesting)