Columbia University’s M.S. in Actuarial Science prepares students to design risk management models and pricing strategies for insurance, pensions, and financial institutions. These capstone ideas involve stochastic modeling, predictive analysis, valuation, and regulatory risk assessment.
Mortality Forecasting Using Lee-Carter Model and Stochastic Simulation
Pricing of Term Life Insurance Using Predictive Analytics
Modeling Lapse Rates in Life Insurance Using Survival Analysis
Catastrophic Risk Modeling for Natural Disasters Using Copulas
Loss Development Triangles for Claim Reserving in General Insurance
Machine Learning Models for Health Insurance Fraud Detection
Valuation of Variable Annuities Under Stochastic Interest Rates
Asset-Liability Management Strategy for Pension Funds
Capital Allocation Using Tail Value at Risk (TVaR) Models
Experience Rating Systems for Auto Insurance Pricing
Dynamic Longevity Risk Hedging Using Derivative Instruments
Retirement Planning Tool Using Monte Carlo Simulation
Predictive Models for Reinsurance Underwriting Profitability
Markov Chain Modeling of Disability Insurance Transitions
Stress Testing Pension Funds Using Macroeconomic Scenarios
Bayesian Models for Estimating Rare Insurance Events
Deterministic vs. Stochastic Models in Premium Forecasting
Optimal Portfolio Strategy Under Regulatory Capital Constraints
Impact of Climate Change on Catastrophe Insurance Pricing
Loss Ratio Trend Forecasting Using Time Series Methods
Collexa supports actuarial students with risk modeling in Excel/R/Python, pension simulations, regulatory report structuring, and premium valuation workflows.
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