Actuarium

Exams

Study guides, original practice questions with worked solutions, and past-paper strategy for every CAS, SOA and CPCU exam — each linked to the Library so you study the concept, not just the syllabus.

43 exams & requirements361 practice questionsKaTeX-rendered solutions

Casualty Actuarial Society — ACAS and FCAS for property & casualty.

Preliminary

Exam 1 Probability (P)

Preliminary

Exam P/1 tests calculus-based probability: set theory, conditional probability and Bayes, discrete and continuous univariate distributions, transformations, moment generating functions, and joint/conditional/marginal distributions. It is shared with the SOA and is the usual first exam.

30 multiple-choice3 hours300 study hrs9 MC · 2 written

Exam 2 Financial Mathematics (FM)

Preliminary

Exam FM/2 covers interest theory: accumulation functions, nominal and effective rates, annuities, loan amortization and sinking funds, bond pricing and amortization, yield curves and spot/forward rates, duration, convexity, and immunization. Derivatives were removed from the FM syllabus in 2022; the emphasis is now firmly on cash-flow valuation.

30 multiple-choice2.5 hours250 study hrs9 MC · 2 written

MAS-I Modern Actuarial Statistics I

Preliminary

MAS-I covers Poisson processes and Markov chains, survival and reliability, parametric estimation and hypothesis testing, GLMs with an actuarial lens, and ARIMA time-series basics. It is the first exam with an explicit modeling mindset.

45 multiple-choice4 hours350 study hrs9 MC · 2 written

MAS-II Modern Actuarial Statistics II

Preliminary

MAS-II is the credibility and modern-modeling exam: classical and Bayesian credibility, conjugate priors and MCMC diagnostics, penalized regression, tree ensembles, and linear mixed models as a generalization of Bühlmann–Straub.

45 multiple-choice4 hours350 study hrs9 MC · 2 written

Associateship (ACAS)

Fellowship (FCAS)

Non-exam requirement

Study-plan builder

Choose your exam, dates and weekly time blocks. The builder weights weeks by syllabus topic, reserves the final 15% for review and mock exams, and tracks every session you complete.

Pick your study days; block lengths are scaled to hit your weekly target.

Mon1.5h
Wed1.5h
Sat5h

Suggested timeline: 30 weeks at 8 h/week (≈200 recommended hours incl. 15% review)

TopicWeightHoursResourcesPractice
Problem definition & data exploration
  • Translate a business problem into a well-defined predictive modeling question with clear target and success metrics.
  • Assess data quality, identify missing values, outliers and data leakage risks before modeling.
  • Perform exploratory data analysis, including univariate and bivariate summaries and visualizations, to inform feature choices.
  • Engineer and transform predictor variables (binning, interactions, encoding of categorical variables) appropriately for the chosen model.
25%43 1 MC · 2 written
Model building: GLMs, trees, regularization
  • Specify and fit a GLM with an appropriate distribution and link function for the target variable.
  • Build and tune decision-tree-based models (single trees, random forests, gradient boosting) with cross-validation.
  • Apply regularization techniques and variable-selection procedures to control overfitting.
  • Compare candidate models using appropriate metrics and select a final model justified by business and statistical criteria.
45%77 2 MC · 2 written
Validation & business communication
  • Validate a fitted model on hold-out or cross-validated data and assess stability of results.
  • Interpret and communicate model results (coefficients, relativities, variable importance) to a non-technical business audience.
  • Recommend business actions supported by the model output, articulating limitations, assumptions and risks.
  • Document the modeling process (data, decisions, diagnostics) in a clear written report.
30%51 2 MC · 1 written

12 weeks · 96 planned hours for SOA PA · recommended ≈200 hrs (104 short)

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