ASTAM Excel Question Trainer
One ASTAM question is graded from the uploaded Excel workbook, and the official past workbooks since Spring 2024 share one layout: a Candidate ID cell, parts with point values, labelled Answer cells, and a check figure. The trainer reproduces that layout with original data so candidates can drill the format, the functions, and the time budget without spending the small stock of official past questions.
SOA Exam ASTAM
Official syllabus, notation, formula sheet, introductory note, study notes, and released exams are mapped for topic planning.
What the official PDFs establish
- Format
- 3-hour exam with six questions and 60 total points.
- Excel component
- One question is answered in an Excel workbook; five questions are answered in written booklets.
- Assumed knowledge
- FM, P, FAM, and mathematical statistics VEE are assumed.
- Submission split
- The Excel workbook is uploaded for the Excel question, while answer booklets are submitted for the written questions.
- Tables and formula access
- Paper tables and the paper formula sheet are not supplied; candidates use the provided Excel workbook and official electronic resources.
Topic and domain coverage
| Topic | Weight | Source |
|---|---|---|
| Severity Models | 8-18% | Source: Exam ASTAM Syllabus, p. 2 |
| Aggregate Models | 12-22% | Source: Exam ASTAM Syllabus, p. 2 |
| Coverage Modifications | 8-18% | Source: Exam ASTAM Syllabus, p. 2 |
| Construction and Selection of Parametric Models | 14-24% | Source: Exam ASTAM Syllabus, p. 3 |
| Credibility | 12-20% | Source: Exam ASTAM Syllabus, p. 3 |
| Reserving and Pricing | 15-29% | Source: Exam ASTAM Syllabus, p. 4 |
Chapter and reading intelligence
- Loss Models, fifth edition
Selected sections from chapters 3, 5, 7-9, 11-13, 15, 17, and 18 are mapped in the syllabus.
- Introduction to Ratemaking and Loss Reserving
Selected sections from chapters 1, 4, and 5 are listed for ratemaking and loss reserving context.
- Outstanding Claims Reserves and QERM Chapter 5
Study notes support reserving and risk-measure topics; the guide summarizes concepts and links official materials.
Official files used by the map
- Official syllabussyllabus
Primary source for format, topic weights, and readings.
Source: Spring 2026 Exam ASTAM Syllabus - Notation guidenotation
Use for notation consistency in examples.
Source: ASTAM Notation for Spring 2026 - Formula sheetformula-sheet
Use to separate supplied formulas from skills that still need memory and practice.
- Introductory study notestudy-note
Use for exam logistics, Excel workbook submission, and software expectations.
- Released ASTAM exams and solutionsreleased-exam
Use for topic maps and answer-style analysis; do not republish questions or solutions.
Source: April 2026 ASTAM Exam
Quick Answer
The graded Excel question has covered reserving triangles, Pareto maximum likelihood with Goal Seek, chi-square goodness of fit for a Poisson frequency model, Bühlmann-Straub credibility premiums, and frequency-model fitting. The trainer supplies original questions on each of these plus Panjer recursion, in the same workbook format, with solution workbooks in which every Answer cell is a live formula.
Work the free sample below first. If the format is new to you, read the Excel tutorial and the refresher that ships with every question before timing yourself.
What Makes a Workbook Answer Score
Graders read the Answer cells and award method marks for legible side work. A live formula in the Answer cell earns credit for the method even when an upstream number is wrong; a typed value does not. Rows and columns inserted inside the provided tables can break the grader's references and are the most common self-inflicted loss.
Every trainer question carries a check figure of the form used on the official workbooks, so a mismatch is caught before the next part is built on top of it.
- Fill the Candidate ID cell first and never insert rows or columns inside the tables.
- Keep parameters in single labelled cells and anchor them with absolute references before filling formulas down.
- Use Goal Seek for one-dimensional maximum likelihood: the target cell is the derivative of the log-likelihood, set to zero.
- Budget three minutes per point and leave two minutes to confirm every Answer cell holds a formula.
How the Trainer Is Built
Data are simulated from stated models and the published answers are computed independently in Python; each solution workbook is then recalculated by a spreadsheet engine and every graded cell is checked against the answer key before release. No SOA question, data, or wording is reproduced; the official past workbooks remain the right final rehearsal and are linked from the past exams page.