CAS Exam 8Advanced Ratemaking

Fellowship (FCAS)

4 hours·25 written-answer items·≈450 study hours

Syllabus learning objectives

Paraphrased from the CAS syllabus so the study-plan builder and practice sets track the topics you will actually be examined on. Weights are the official topic ranges.

Classification ratemaking & GLMs

30%

Build a GLM to estimate frequency, severity, or pure premium relativities by rating variable.
Assess multicollinearity, interactions and offsets when specifying a classification model.
Translate GLM output into indicated rating relativities and territory/class plans.
Validate a classification model using lift charts, double-lift charts and hold-out testing.

Individual risk rating (experience, schedule, retrospective)

30%

Compute experience rating modification factors incorporating credibility for primary and excess losses.
Apply schedule rating debit/credit criteria to adjust manual premium.
Determine retrospective premium under basic and incurred-loss retro rating plans with loss limits and maximum/minimum premiums.
Assess the incentive and cash-flow effects of individual risk rating plans.

Excess, deductible & increased-limits pricing

25%

Compute increased limit factors from a fitted severity distribution and adjust for trend and development.
Price deductible credits and self-insured retentions using limited expected value functions.
Assess the effect of ALAE treatment (pro rata vs. first-dollar) on excess layer pricing.
Evaluate the sensitivity of layer pricing to assumptions about the severity distribution's tail.

Catastrophe & reinsurance pricing

15%

Apply exposure rating and experience rating (burning cost) techniques to price reinsurance treaties.
Use catastrophe model output (exceedance probability curves) to price catastrophe covers.
Price proportional and non-proportional reinsurance structures, including reinstatement provisions.
Assess model and parameter uncertainty in catastrophe and reinsurance pricing.

Lecture videos for this exam

Open the full video library →

Insurance Risk Pricing with GLM, GAM and XGBoost

Matthew Evans · Pricing & GLMs

Pricing Insurance Risk: Theory and Practice

Stephen Mildenhall · Pricing & GLMs

Steve Mildenhall Python for Pricing Insurance Part 1

David Wright · Pricing & GLMs

Introduction to Excess of Loss Reinsurance | Excess of Loss Reinsurance Course for Beginners

Underwrite University · Reinsurance

Introduction to Catastrophe Excess of Loss (XoL) Reinsurance | Introductory Course for Beginners

Underwrite University · Reinsurance

Overview

Exam 8 is the fellowship pricing exam: GLM classification (CAS monograph), individual risk rating (NCCI experience rating, retrospective rating, Table M/L), increased limits and deductibles (ILFs, layer pricing, Fisher), and reinsurance/catastrophe pricing (Clark, Mata).

Duration: 4 hours
Questions: 25 written-answer items
Style: Computer-based written answer
Credit: Required for FCAS

Syllabus map

Classification ratemaking & GLMs

30%

GLMs and Predictive Modeling in Pricing

Individual risk rating (experience, schedule, retrospective)

30%

Workers' Compensation Ratemaking Credibility Theory: Limited Fluctuation, Bühlmann, and Bayes

Excess, deductible & increased-limits pricing

25%

GL, Auto & Umbrella Pricing: Increased Limits and Excess Ratemaking Reinsurance Structures and Pricing

Catastrophe & reinsurance pricing

15%

Extreme Value Theory and Heavy Tails Reinsurance Structures and Pricing

Key formulas

Experience modification $\;M=1+Z\left(\dfrac{A}{E}-1\right)$ , NCCI split-plan form $\;M=\dfrac{A_p+wA_e+(1-w)E_e+B}{E+B}$

Increased limits factor $\;ILF(L)=\dfrac{E[X\wedge L]+\text{ALAE}+\text{risk load}}{E[X\wedge B]+\cdots}$ ; layer cost $\;=E[X\wedge L_2]-E[X\wedge L_1]$

Loss elimination ratio $\;LER(d)=\dfrac{E[X\wedge d]}{E[X]}$

Retrospective premium $\;R=\left[B+cL\right]T$ bounded by $H$ and $G$ ; $\;B=e-(c-1)E+cI$ where $I$ is the net insurance charge

Table M insurance charge $\;\phi(r)=\int_r^\infty(1-F(s))ds$ , savings $\;\psi(r)=\phi(r)+r-1$

Exposure vs experience rating for reinsurance: exposure curve $G(d)$ gives the share of loss below a fraction $d$ of insured value.

Study strategy

Master the mechanics of the NCCI split plan and retrospective rating formula; compute a full retro premium with Table M several times.
For ILFs, practice consistency tests (marginal ILFs must decrease) and the effect of trend on layers (leveraged effect).
For GLMs, focus on model-building decisions: offsets, weights, interactions, and validation (lift charts, double-lift, Gini).
Draw the exposure/Table M pictures — many written questions ask you to reason from the graph.

Common traps

Forgetting the tax multiplier or applying it before the min/max in retrospective rating.
Using ILFs multiplicatively with class relativities where the reading says they interact (limit × class).
Confusing loss cost of a layer with its share of premium when expense loads differ by layer.
Treating credibility $Z$ in experience rating as $n/(n+k)$ without the split between primary and excess.

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