Aubrey Clayton
Aubrey Clayton is a part of the Moody’s Analytics Insurance Research group. His recent work has focused on applications of economic scenario generators and Least Squares Monte Carlo (LSMC) proxy techniques to multi-period problems, particularly the projection of dynamic hedge programs and economic capital. Aubrey has a PhD in Mathematics from The University of California, Berkeley with a specialty in stochastic modeling and dynamical systems.
Economic Scenarios: Moody's Analytics provides internally and globally consistent economic, regulatory, and custom scenarios.
Economic Capital : Moody’s Analytics insurance economic capital solution provides critical insights that help evaluate solvency positions and risk-based decision making.
Insurance Asset and Liability Management : Moody's Analytics insurance asset and liability management (ALM) solution provide scenario-based asset and liability modeling for insurers.
Scenario Generation: Mathematical model simulating possible paths of economic and financial market variables.
Liability Valuation: Process of valuing a company's liabilities for financial reporting purposes.
Capital Measurement & Projection: Approach for the projection of assets and liabilities for a business block to future time.
Developed techniques to calibrate proxy functions for Conditional Tail Expectation metrics, improving efficiency for reserve/capital projections
Used LSMC and neural network methods to forecast Greeks for complex Variable Annuity portfolios, enabling fast projection of dynamic hedges