Exam SRM Sample Questions, Free and Interactive
SRM is the data-science actuarial exam. Where P and FM test math and finance with actuarial framing, SRM puts you in front of the toolkit a modern actuary uses for predictive modeling: generalized linear models, decision trees, time series, principal component analysis, clustering. The style shifts too. More conceptual, less calculation-heavy, more "which method fits here" than "compute this integral."
The SOA's published SRM sample set is smaller than the older preliminaries: 66 items as of 2026, the entire publicly-released body of sample work. The exam is younger (introduced in its current form in 2018), so the SOA has accumulated fewer publicly-released items. At 66 items, the sample set works best as a final-stretch calibration tool, not as primary practice.
FreeFellow hosts all 66 in the practice surface with worked solutions alongside, plus an original SRM bank (1,000-plus questions) for the bulk of practice. Free, no signup to browse, no credit card.
Start practicing Exam SRM samples
What the 66 Sample Items Cover
The full topic distribution:
| Topic area | Approx. sample count | What you'll see |
|---|---|---|
| Generalized linear models | ~20 | Logistic regression, Poisson regression, link functions, deviance, log-likelihood interpretation |
| Decision trees | ~12 | CART, splitting criteria (Gini, entropy), pruning, ensemble methods, bagging/boosting |
| Time series | ~12 | Stationarity tests, AR, MA, ARMA, model identification, forecasting |
| Principal component analysis | ~8 | Variance explained, loadings, biplot interpretation, application to dimension reduction |
| Cluster analysis | ~6 | K-means, hierarchical clustering, dendrogram interpretation |
| Model selection and validation | ~8 | Cross-validation, AIC/BIC, bias-variance tradeoff, train/test splitting |
The patterns worth noticing: GLM questions favor scenario problems where you identify the right link function given the response data structure (binary, count, continuous-positive). Time-series questions favor stationarity diagnosis and model identification from autocorrelation patterns. Tree questions favor splitting-criterion comparisons and ensemble logic. The style is unmistakably data-analytic, not calculation-heavy.
Why the SRM Sample Set Is a Calibration Tool, Not a Primary Bank
Three concrete reasons specific to SRM:
The 66-item set is too small to drill on repeat without memorizing the answers. Once you've seen each item once, the calibration value drops fast.
The exam rewards conceptual understanding far more than pattern-matching. Reading ISLR (the canonical SRM textbook, free from its authors at statlearning.com) is a much better use of your hours than re-drilling 66 sample items.
SRM pacing is more forgiving than P/FM. You have time to think, which means raw practice volume matters less than it does on the calculator-heavy exams.
Save all 66 SRM samples for the final two weeks. Take them in a single 100-minute timed block (live exam pacing). Score 70 percent or higher and you're ready. Below 60, schedule another week of topic review before sitting.
Three Tactics for the 66 Items
Read ISLR first, work samples second. ISLR (An Introduction to Statistical Learning, James/Witten/Hastie/Tibshirani) is the conceptual foundation the SOA samples assume you already have. Read chapters 3 through 10 before you touch the sample set. Samples without the ISLR base produce frustration, not learning.
Write the model-selection reasoning before checking the solution. SRM rewards "which model fits" reasoning. When you work a sample item, write down (on scratch paper or in a note) why you chose the model you chose. Then check the worked solution. Self-grade on the reasoning, not just the letter you picked.
Focus on GLM link functions specifically. Of the 20 GLM items, roughly half hinge on identifying the right link function (logit for binary, log for Poisson, identity for continuous-positive with constant variance). Mastery here translates to live-exam points out of proportion to the study time.
What the Samples Don't Cover Well
Honest gaps for SRM:
- Recent syllabus additions (2024+). Model interpretability methods (SHAP values, partial dependence plots) and fairness/bias metrics are syllabus topics with sparse sample coverage. Supplement from the FreeFellow original SRM bank, which is calibrated against the current syllabus.
- Real-world data-cleaning scenarios. The samples assume tidy data. The live exam can include questions where the answer turns on recognizing a data-quality issue.
- Newer ensemble methods (gradient boosting, random forests). Sparse in older sample batches; better covered in the FreeFellow originals.
How SRM Practice Compares Across Free and Paid
| Source | SRM Sample Questions | Format | Cost |
|---|---|---|---|
| FreeFellow | All 66, interactive | Same surface as topic practice | $0 |
| ISLR (textbook) | None directly | Free PDF and printed book | $0 |
| ASM SRM Manual | All 66 in study manual | $130 to $200 | |
| Coaching Actuaries Learn + Adapt SRM | All 66 + originals + video lessons | Interactive within Adapt | $300 to $400 per exam |
| SOA only | All 66 | Static PDF on soa.org | $0 |
ISLR earns the explicit callout: it's the most important free SRM resource, written by the canonical authors of the underlying statistical-learning material. The SOA samples calibrate your readiness; ISLR builds the conceptual base.
Start Practicing
Practice all 66 Exam SRM samples alongside the FreeFellow original SRM bank. Both are free. Pair with ISLR for the conceptual foundation.
For the full picture on actuarial exam prep: Best Free Actuarial Exam Prep Resources (2026).