Lecturer; Senior Director of Asset Liability Management and Investment Strategy, New York Life Insurance
Kamyar Moud has 20 years of experience in the financial services industry specializing in quantitative risk modeling and investment management. Currently, Kam is the Senior Director of Asset Liability Management and Investment Strategy at New York Life Insurance. Kam and his team are responsible for the Net Investment Income projection models for invested assets in general accounts across all lines of business within New York Life Insurance portfolios.
Prior to New York Life Insurance, Kam led the enterprise-wide Risk Analytics Solutions globally at AIG. In his role, he led the design and deployment of enterprise-wide investment risk models and enhanced the analytical capability of AIG’s Risk organization. Kam has led the deployment of various internal and vendor investment risk analytics systems and tools and successful digital transformation projects.
Before AIG, Kam was with State Street; in his capacity, he led the research and quantitative model development efforts focusing on stress testing models developed to assess the effects of severe economic scenarios on buy-side clients’ investment portfolios using advanced Bayesian methods. In parallel, he worked closely with the new product development team within State Street Global Exchange, which had the mandate of looking into external mergers, acquisitions, and strategic partnerships with new ventures.
Kam joined State Street from Moody’s Analytics (KMV) in San Francisco, where he was the Head of Portfolio Risk Advisory and Research Services for the Americas. Kam and his team were responsible for the development and implementation of quantitative risk models, which included Economic Capital models, Asset class specific Credit Risk models, Custom Credit Correlation and Credit Transition models, Macro-economic Credit Stress Test models for Tier 1 and 2 national and international banks, insurance companies and asset managers.
Prior to Moody’s, Kam was a Senior Quantitative Research Analyst with the Canadian Bank of Imperial Commerce (CIBC) in Toronto, where he developed credit risk models using machine learning algorithms and deployed new analytical functionalities to the bank’s Credit Risk Models Performance Monitoring system. Moud joined CIBC from Algorithmics Inc. as a Quantitative Research Analyst in the Quantitative Research group; his research focused on portfolio optimization and asset allocation using multistage stochastic models and online learning algorithms.
Kam holds three master of science degrees in Operation Research and Finance, Statistical Signal Processing and Information Theory, and a Bachelor of Science in Electrical Engineering. He has presented at international conferences and published in peer-reviewed scientific journals.
- M.S., Columbia University
- M.S., Queen's University, Smith School of Business, Canada
- M.S., Chalmers University of Technology
- B.S., Sharif University of Technology