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Biography

Chicago Booth Adjunct Professor, David K.A. Mordecai is President of New York based advisory firm and Co-Managing Member of聽, a data analytics, technology development and commercialization firm.

With nearly forty years of direct industry experience across a range of commercial sectors and capital markets as a former senior executive at global banks, diversified financial institutions and a large multi-strategy hedge fund management firm, Dr. Mordecai actively conducts applied research at the intersection of risk engineering and industrial economics, which has included forensic financial and economic analysis, financial engineering, the valuation of fixed income securities and structured products, including over-the-counter derivatives, complex insurance and reinsurance liabilities, M&A and successor liability analysis, operational risk, reliability and warranty-indemnity analysis, environmental liability, trade credit and political risk, as well as asset-liability and risk management models and practices.

Since 2013, David K.A. Mordecai has served as the first聽Scientist-in-Residence听补迟听, an accelerator platform for early and growth stage technology firms, organized by聽聽in conjunction with Accenture and a consortium of venture capital firms and global financial institutions.

During his thirty-year tenure in the financial services industry, he has served as a Managing Director at聽, where he led Relative-Value Market Strategies, a quantitative economics and financial engineering function with the global mandate to develop firm-wide and industry standards, benchmarks and frameworks for the valuation and trading of exposures underlying long-dated life, health, medical and pension liabilities as well as geopolitical risk. Prior to this, he served as Senior Advisor to the Head of Swiss Re Financial Services. Previously, at a multi-strategy hedge fund with $10 Billion of assets under management, he was Managing Director of Structured Products, responsible for $5 billion of CDO assets. Prior to his role as a hedge fund manager, he was Vice President of Financial Engineering/Principal Finance at聽, and a Director at the rating agency聽. During the first decade of his career, he specialized in credit analysis and the origination, structuring, and trading of leveraged loans for non-recourse project finance and highly leveraged transactions involving corporations and financial institutions.

Dr. Mordecai has served as an advisor on systemic risk issues to the Federal Reserve, the聽, the聽, and the Commodities and Futures Trading Commission (CFTC), and as an advisor on hedge fund valuation issues to the聽. He coauthored the second working paper published by the Treasury Department鈥檚 Office of Financial Research, entitled聽. He has also been a member of the Investment Advisory Committee of the聽. He is the founding Co-Chair of the聽聽Liquidity Risk Committee, and has actively served on the Steering Committee of the IAFE鈥檚 Investor Risk Working Group on hedge fund and CTA disclosure issues, as well as the Advisory Board.

Dr. Mordecai earned a Ph.D. with concentrations in Econometrics/Mathematical Statistics and Economics/ Industrial Organization from the聽 Booth School of Business (2004), and an M.B.A. in Finance from聽 (1987).

As Visiting Scholar at Courant Institute, Dr. Mordecai advises research activities at聽聽NYU, established in 2011 in order to apply a range of computational and analytical methods to commercial, consumer and population-related societal trends. In this senior advisory capacity for the lab, he leads technical oversight for research activities exploring applications of agent-based computing and statistical inference, in conjunction with machine learning systems and methods, to a broad range of commercial and institutional contexts. In 2010, he was invited to become a Fellow, as well as a member of the Advisory Board of the Mathematical Finance Program at Courant, having served as a guest lecturer for the program since 2006.

He has served as an adjunct instructor of applied mathematics at Courant, as well as an Adjunct Professor and an active member of the working group for the聽(NYUCDS) at its inception. In 2014, he was appointed Course Director to lead the NYUCDS Capstone graduate applied research program in its inaugural year. Dr. Mordecai also serves on the Advisory Committee of the Institute for Analytics and Data Science (IADS) at Durham University, England. In addition, he has been a guest lecturer at聽, at the Graduate Business School, the Engineering/Operations Research Division, as well as the School for International and Public Affairs, as well as at NYU Law School.

Dr. Mordecai serves as Chair of the Nanotechnology Committee, Co-Chair of the Space Law Committee and Vice-Chair of the Artificial Intelligence and Robotics for the. As the founding Editor-in-Chief of the聽(JRF ca.1999), a quarterly peer-reviewed research periodical, which addresses topics in financial risk intermediation, he remains a senior member of JRF鈥檚 Advisory Board. He has published numerous articles on topics including hedge fund strategies, structured credit, and weather and insurance derivatives.聽He has also served on the advisory committee for聽聽(CAIA) Association, and on the editorial board of the聽.

He is a member of the founded in 1817, a member of the leadership council and carbon sequestration science committee of the 4,000 acre biological field station Black Rock Forest Consortium, comprised of twenty-three research institutions, and was previously a member of the board of directors of Scenic Hudson and Hudson Highlands Land Trust.

Research Interests

Statistical learning, decision and process control applications at the intersection of industrial economics and engineering: density estimation, regression, classification and clustering; outlier analysis, anomaly detection, system identification; kernels, filters, mixture methods; sieve estimation; signal processing and compressive sensing; factor and principal components analysis; data smoothing, sifting, sorting methodologies. Empirical Industrial Organization: statistical risk analysis and econometrics of natural resource and energy market economics; environmental and geo-political risks; political economy, law and economics of markets, market externalities, geopolitical and systemic risks; forensic economic and statistical analysis; economic analysis of data and algorithmic bias; operational risk and reliability engineering; statistical and forensic analysis of scientific evidence; validation testing and verifiability analysis of artificial intelligence (AI) and machine learning (ML) algorithms.

Academic Areas

• Econometrics and Statistics