IFoA CB2 study guide
IFoA CB2 · Work through your exam, one topic at a time.
CB2 is one of the subject codes in the Institute and Faculty of Actuaries (IFoA) examination system, part of the professional qualification route that leads to actuarial fellowship. The IFoA describes its qualification pathway as combining exams with Personal and Professional Development, where practical work experience is a key part of the qualification, and it publishes curriculum information, exam dates and essential resources through its Exams pages. Candidates for CB2 are typically student members working through the IFoA curriculum, usually alongside full-time actuarial employment, and they sit the subject as one step in a multi-exam progression rather than as a standalone certificate. The IFoA site does not enumerate individual subject syllabuses or state CB2-specific format, duration, fees or pass marks on the pages referenced here, so candidates should confirm the current syllabus, exam session dates and entry deadlines directly from the IFoA curriculum and exams pages and their member portal. The IFoA CB2 study guide has 4 sections and about 1,423 words.
01Data and Analysis
CB2 tests whether you can source, assess, prepare and summarise data before any model is fitted. Questions often ask you to choose an appropriate summary or chart, or to explain how poor data quality affects later conclusions.
365 words, about 2 min02Statistical Inference and Regression
CB2 tests fitting probability models to data, estimating parameters, testing hypotheses and using regression or time-series models in an actuarial context. You must interpret output, not merely compute it.
393 words, about 2 min03Building and Using Models
CB2 tests how to construct, parameterise, run and interpret actuarial models. It expects you to choose between deterministic and stochastic approaches, document assumptions and communicate output distributions rather than a single number.
335 words, about 2 min04Model Risk, Validation and Communication
CB2 tests how model risk arises, how models are validated and how results are communicated to decision-makers. It rewards specific controls and clear acknowledgement of limitations.
330 words, about 2 min