SOA Exam SRM Guide
SRM is the SOA statistics bridge: regression, risk modeling, statistical learning ideas, and the conceptual base for PA.
- Role
- Exam Guide
- Level
- Core
- Time
- Reference
- Freshness
- Stable
What Exam SRM Entails
- Statistics for risk modeling, including regression, time series, and simulation ideas.
- Preparation for predictive analytics work and PA-style model communication.
- Core practice: choosing models, interpreting assumptions, and connecting statistical output to risk decisions.
SOA Exam SRM
Official syllabus readings and topic weights are mapped; sample questions are topic-tagging inputs only.
What the official PDFs establish
- Format
- 3.5-hour, 35-question multiple-choice CBT exam.
- Relationship to PA
- SRM is a prerequisite for PA and assumes calculus, probability, and mathematical statistics background.
- R note
- Candidates are not required to learn R, but R output may appear on the exam.
Topic and domain coverage
| Topic | Weight | Source |
|---|---|---|
| Basics of Statistical Learning | 5-10% | Source: Exam SRM syllabus, p. 2 |
| Linear Models | 40-50% | Source: Exam SRM syllabus, p. 2 |
| Time Series Models | 10-15% | Source: Exam SRM syllabus, p. 3 |
| Decision Trees | 20-25% | Source: Exam SRM syllabus, p. 3 |
| Unsupervised Learning Techniques | 10-15% | Source: Exam SRM syllabus, p. 3 |
Chapter and reading intelligence
- Frees Regression Modeling
Chapters 1-3, 5-9, and 11-13 are mapped in the syllabus with section-level exclusions.
- ISLR, second edition
Syllabus readings cover statistical learning, linear regression, resampling, model selection, trees, and unsupervised learning sections.
Official files used by the map
- Official syllabussyllabus
Primary source for format, topic weights, and readings.
- Sample questionssample-questions
Use for topic tagging and practice design; do not republish question text.
Source: Exam SRM Sample Questions
Quick Answer
SRM is pre-fellowship, not an FSA exam. It belongs in the ASA-side statistics and predictive analytics sequence with PA and ATPA.
Official Format And What The Exam Covers
The September 2026 syllabus maps SRM as a 3.5-hour, 35-question multiple-choice CBT exam. The official overview frames it around regression, time series, principal components analysis, decision trees, cluster analysis, and model selection or validation.
The syllabus also makes three practical points candidates should remember: SRM is a prerequisite for PA, calculus and Probability (P) background are assumed, and candidates are not required to learn R even though R output may appear on the exam.
Where The Weight Really Sits
Linear models dominate the syllabus. If a candidate treats SRM as a generic machine-learning survey, they will usually underprepare for the regression-heavy center of the exam.
The rest of the syllabus matters because it rounds out actuarial modeling judgment: time series for temporal structure, decision trees for nonlinear segmentation, and unsupervised learning for dimension reduction or clustering ideas.
- Basics of statistical learning: 5-10%.
- Linear models: 40-50%.
- Time series models: 10-15%.
- Decision trees: 20-25%.
- Unsupervised learning techniques: 10-15%.
What It Connects To
SRM connects Exam P probability to regression, model selection, likelihood-based thinking, and practical risk modeling. It is also the cleanest conceptual preparation for PA because it teaches what a model is doing before PA asks you to explain and defend that model in a business context.
For ActuaryPath, SRM is also one of the best bridges into broader statistics and ML language: generalized linear models, AIC or BIC, principal components, and decision trees are all recognizable outside the actuarial exam world.
SOA vs CAS Context
SRM is not the same as CAS MAS-I or MAS-II, but there is conceptual overlap around probability, statistics, regression, and model interpretation. The useful comparison is not which exam is "harder" in the abstract, but how the downstream signal differs between the ASA predictive-analytics sequence and the CAS modern-statistics sequence.
Common Candidate Mistakes
A common SRM mistake is overfitting your study plan to vocabulary and underweighting interpretation. The exam rewards being able to choose a model, read assumptions, interpret diagnostics, and explain why a procedure is or is not appropriate in context.
Another common mistake is treating SRM as if coding fluency is the tested skill. The exam is about statistical reasoning first. Software output is useful only if you can interpret what it means.