Introduction

Innovation in risk & value management — with people and trustworthy AI

I work at the intersection of business transformation and quantitative risk management — combining actuarial rigor with modern technology and data-driven thinking. The emphasis is not on individual tools or models, but on designing coherent decision frameworks that integrate analytics, performance, risk, and technology around purpose and collaboration. These frameworks quantify uncertainty and account for asymmetric outcomes, strengthening system integrity for practical impact. This allows decisions to compound into durable value through capital allocation trade-offs and risk-adjusted performance rather than fragment over time.

This site brings those themes together across insurance and pensions, decision frameworks, data science, and applied coding & AI — connected by a common decision structure: uncertainty, asymmetric outcomes, and portfolio effects through risk aggregation and dependency modeling over time. Projects like my sports simulation lab rigorously test real world frictions and portfolio resilience under asymmetric outcomes, providing first-hand evidence of how risk aggregation and uncertainty quantification shape long-term value. This approach mirrors professional work in insurance, pensions, and AI, where decision frameworks explicitly balance capital allocation, governance constraints, and model robustness.

If you’re driving transformation in risk management, rethinking pension design, or advancing analytics and AI in practice, you’ll find here a mix of shared ideas, quantitative perspectives, and first-hand findings from applied research and real projects, as well as my professional background.

To get in touch or learn more, visit the About me page.