P&C actuarial and insurance work
Junior’s actuarial development combines CAS training, insurance simulations, a detailed personal-auto pricing case study, and AI evaluation work grounded in probability, expected value, statistical inference, and model limitations.
Verified actuarial experience
Each experience adds a different layer: industry context through CAS, applied judgment through AIG simulations, and technical modeling through the pricing case study.
Casualty Actuarial Society · May–August 2025
Completed the CAS Student Central Summer Program, a remote actuarial learning experience focused on property and casualty insurance. Developed exposure to ratemaking, pricing analysis, insurance analytics, loss modeling, and actuarial career paths through case-based learning and professional programming. Earned the CAS Student Central Summer Program Participant credential.
AIG · October 2025
Completed actuarial and underwriting job simulations involving P&C risk assessment, data interpretation, underwriting judgment, actuarial analysis, and concise recommendation writing.
Independent case study
Built an end-to-end framework connecting exposure, claim frequency, claim severity, pure premium, expenses, profit, indicated rates, aggregate loss, and portfolio risk.
Flagship case study
This page documents the methodology and conclusions described on Junior’s public professional profile. The underlying code and dataset are not represented as publicly available.
Structured multi-year policy and claims data with exposure, territory, driver, vehicle, and loss factors.
Compared Poisson and Negative Binomial GLMs to model claim counts while accounting for exposure.
Compared Gamma and Lognormal approaches for positive claim costs using log-link specifications.
Used AIC, BIC, L1 regularization, monotonicity checks, fairness review, and practical interpretability.
Applied k-fold and out-of-time testing to examine stability, calibration, predictive performance, and reason codes.
Combined frequency and severity into pure-premium indications and aggregate-loss simulations with VaR, TVaR, reinsurance analysis, and combined-ratio stress tests.
Technical toolkit
The objective is not merely to fit a model. It is to understand why it behaves as it does, how it fails, and what the indication means for customers and the insurer.
Junior is preparing for actuarial Exams P and FM and is pursuing P&C pricing, reserving, predictive analytics, model validation, underwriting analytics, and enterprise risk opportunities.
