About me
Is your Predictive Modeling algorithm inadvertently discriminatory, leaving behind revenues and attracting unwanted regulatory attention? Do you trust the Data Analytic team not to create an AI model that will become a costly White Elephant? Do you really need a Large Language Model or should you deploy a Small Language Model?
My Story
I am a consultant with 25 years of actuarial experience, brining the actuarial lens to innovation and technology for the insurance industry. I advise clients on how to implement AI use cases while mitigating unwanted regulatory attention.
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With a solid technical education from the prestigious Ecole Nationale de la Statistique et de l'Administration Economique master's degree in actuarial science, I continue to lead and support the industry by chairing the Artificial Intelligence subcommittee of the American Academy of Actuaries, and being the president of the Chicago Actuarial Association. I also volunteer on Behavioral Economics and Data Science and Analytics Committee committees, as well as on the project oversight group of the Society of Actuaries Quantitative Fairness Metrics project. These activities keep me on the leading edge of how the family of Predictive Modeling techniques impacts the industry, from the old GLM-GAM to AI, ML and newer GenAI, LLM/SLM techniques.
I publish and present on innovation, technology, bias, behavioral economics, life underwriting, stochastic on stochastic, and risk management. I am passionate about exploring the opportunities and challenges of applying innovation and technology to the actuarial profession and the insurance industry.
Contact
I'm always looking for new and exciting opportunities. Let's connect.
312-758-5398