Skip navigation Jump to main navigation

Kamyar Moud

Lecturer; Director of Asset Liability Management and Investment Strategy, New York Life Insurance

Kamyar Moud has over 18 years of experience in financial services industry specializing in quantitative risk modeling and investment management.  Kam currently is Director of Asset Liability Management and Investment Strategy at New York Life Insurance. Kam and his team are responsible for the Net Interest Income projection models for invested assets.

Until recently, Kam was leading the enterprise-wide Risk Analytics Solutions globally at AIG. In his role, he was responsible for led the design and deployment of enterprise-wide investment risk models and enhancing the analytical capability of the AIG’s Risk organization. Kam has led the deployment of various internal and vendor investment risk analytics systems, tools as well as the successful digital transformation projects.

 Prior to AIG, Kam was with State Street, in his capacity he was leading the research and quantitative model development efforts focusing on quantitative stress testing model development to assess the effects of severe economic scenarios on buy side clients’ investment portfolios using advanced Bayesian methods. In parallel he worked closely with new product development team within State Street Global Exchange that 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 Portfolio Risk Advisory and Research Services for Americas. Kam and his team were responsible for 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 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. where he was 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 in 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