David K.A. Mordecai
Education
Ph.D., economics and econometrics/statistics, The University of Chicago Booth School of Business; M.B.A., finance, NYU Stern School of Business
Summary of Experience
Dr. Mordecai is an expert on forensic financial and economic analysis, financial engineering, and the valuation of fixed-income securities and structured products, including over-the-counter derivatives – in particular, fixed-income and credit derivatives. He also has expertise in 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. In addition, Dr. Mordecai has direct experience with cryptocurrency and digital asset technology infrastructure, including the technical review and evaluation activities of distributed ledger technology. Dr. Mordecai has advised on, and provided technical oversight for, pattern and practice investigations, internal regulatory investigations, insurance investigations for state regulators, and stress testing for global financial institutions. He has testified extensively at deposition, trial, arbitration, and international arbitration; been admitted as an expert in federal, state, and county courts; and been cited favorably in court decisions. Dr. Mordecai has served as an advisor on systemic risk issues to the Federal Reserve, the International Monetary Fund (IMF), the US Department of the Treasury, and the Commodity Futures Trading Commission (CFTC), and as an advisor on hedge fund valuation issues to the International Organization of Securities Commissions. He has also been a member of the Investment Advisory Committee of the New York Mercantile Exchange (NYMEX). In addition to his role at The University of Chicago Booth School of Business, Dr. Mordecai is a visiting scholar at the NYU Courant Institute of Mathematical Sciences, where he co-advises research activities at the RiskEcon® Lab for Decision Metrics. Dr. Mordecai also co-teaches a course at NYU Law School on quantitative methods in litigation with a focus on machine testimony and machine behavior. His contributions to this course as co-instructor include extensive direct experience with technical review, evaluation, and testing of AI and machine learning applications across diverse institutional contexts, as well as industry and market settings.
AG Contacts