Free Study Materials for the Casualty Actuarial Society (CAS) Exam 5B
(Old Exam 6)
Concepts Involved in the Chain Ladder Method: Practice Questions and Solutions
July 21, 2010 - Republished July 11, 2014
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This section is part of Mr. Stolyarov's Free Study Materials for the CAS Exam 5B.
This section of the study guide is intended to provide practice problems and solutions to accompany the pages of Estimating Unpaid Claims Using Basic Techniques, cited below. Students are encouraged to read these pages before attempting the problems. This study guide is entirely an independent effort by Mr. Stolyarov and is not affiliated with any organization(s) to whose textbooks it refers, nor does it represent such organization(s).
Some of the questions here ask for short written answers based on the reading. This is meant to give the student practice in answering questions of the format that will appear on Exam 5B (Old Exam 6). Students are encouraged to type their own answers first and then to compare these answers with the solutions given here. Please note that the solutions provided here are not necessarily the only possible ones.
Friedland, Jacqueline F. Estimating Unpaid Claims Using Basic Techniques. Casualty Actuarial Society. July 2009. Chapter 7, pp. 84-90.
Original Problems and Solutions from The Actuary's Free Study Guide
Problem S6-17-1. List the seven steps of the development method, i.e., the chain ladder method. (See Friedland, p. 85.)
Solution S6-17-1. The following are the seven steps of the chain ladder method (Friedland, p. 85):
1. "Compile data in a development triangle."
2. "Calculate age-to-age factors."
3. "Calculate averages of the age-to-age factors."
4. "Select claim development factors."
5. "Select tail factor."
6. "Calculate cumulative claim development factors."
7. "Project ultimate claims."
Problem S6-17-2. For 36 to 48 months, the age-to-age factors calculated from various accident years (AYs) of data are as follows:
AY 2113: 1.125
AY 2115: 1.269
AY 2116: 1.120
AY 2117: 1.006
Calculate the following statistics:
(a) Simple average for the latest six years
(b) Simple average for the latest five years
(c) Simple average for the latest three years
(d) Medial average for the latest six years (excluding the high and low value)
(e) Geometric average for the latest six years
(f) Volume-weighted average for the latest six years, given that exposures in each subsequent year are 5% higher than in the previous year
Solution S6-17-2. (a) Simple average for the latest six years:
(1.315 + 1.125 + 1.128 + 1.269 + 1.120 + 1.006)/6 = 1.1605.
(b) Simple average for the latest five years:
(1.125 + 1.128 + 1.269 + 1.120 + 1.006)/5 = 1.1296.
(c) Simple average for the latest three years:
(1.269 + 1.120 + 1.006)/3 = 1.131666667.
(d) Medial average for the latest six years:
(1.125 + 1.128 + 1.269 + 1.120)/4 = 1.1605.
(e) Geometric average for the latest six years:
(1.315*1.125*1.128*1.269*1.120*1.006)^(1/6) = 1.155963621.
(f) Volume-weighted average for the latest six years, given that exposures in each subsequent year are 5% higher than in the previous year:
Assume, for convenience, that there is 1 exposure unit in AY 2112. Then, each year, the number of exposure units increases by a factor of 1.05. The volume-weighted average is thus
(1*1.315 + 1.05*1.125 + (1.05^2)*1.128 + (1.05^3)*1.269 + (1.05^4)*1.120 + (1.05^5)*1.006)/(1 + 1.05 + 1.05^2 + 1.05^3 + 1.05^4 + 1.05^5) = 1.154704947.
Note that I have used MS Excel notation here to facilitate ease of computerized computation. Problems of this sort are not, in most real-world applications, done by hand. On the exam, the volume of computations required will, I expect, be lower per problem than it is here.
Problem S6-17-3. Friedland, p. 88, discusses five characteristics that actuaries examine when reviewing claim development factors and the experience on the basis of which they are derived. State the name of each characteristic and state one possible question related to it.
Solution S6-17-3. The following are five characteristics that actuaries examine when reviewing claim development factors and the experience on the basis of which they are derived:
1. Smooth progression of individual age-to-age factors and average factors across development periods: Do the age-to-age factors steadily decrease toward 1 as later time periods from the accident date are considered?
2. Stability of age-to-age factors for the same development period: What is the variance in the age-to-age factors for a particular time period (X months to Y months from the accident date) among the accident years considered?
3. Credibility of the experience: What is the volume of the underlying experience, and is it sufficiently large for the experience to be used on a stand-alone basis, or must external data be considered?
4. Changes in patterns: Do any systematic differences from one time period to the next suggest a different external or internal operating environment?
5. Applicability of the historical experience: Is it appropriate to assume that claims will develop in the future much as they have developed in the past, or must one take account of new circumstances that have not yet impacted historical claim data?
Problem S6-17-4. Briefly describe three approaches commonly used by actuaries to estimate tail development factors. (See Friedland, p. 90.)
Solution S6-17-4. The following are three approaches commonly used by actuaries to estimate tail development factors:
1. Use industry benchmark factors.
2. Extrapolate tail factors by fitting a curve - often an exponential curve - to known development factors.
3. Assume that reported development is already at ultimate and use the ratio of reported claims to paid claims as the estimate of the tail factor.
Problem S6-17-5. You know the following age-to-age factors for accident year 2033:
12-24 months: 1.134
24-36 months: 1.130
36-48 months: 1.102
48-60 months: 1.055
12 months to ultimate: 1.500
What is the tail (60-months-to-ultimate) development factor?
Solution S6-17-5. The 12-months-to-ultimate factor is the product of the given age-to-age factors and the tail factor. Thus, the tail factor is 1.500/(1.134*1.130*1.102*1.055) = 1.006852162.
Gennady Stolyarov II (G. Stolyarov II) is an actuary, science-fiction novelist, independent philosophical essayist, poet, amateur mathematician, composer, and Editor-in-Chief of The Rational Argumentator, a magazine championing the principles of reason, rights, and progress.
In December 2013, Mr. Stolyarov published Death is Wrong, an ambitious children’s book on life extension illustrated by his wife Wendy. Death is Wrong can be found on Amazon in paperback and Kindle formats.
Mr. Stolyarov has contributed articles to the Institute for Ethics and Emerging Technologies (IEET), The Wave Chronicle, Le Quebecois Libre, Brighter Brains Institute, Immortal Life, Enter Stage Right, Rebirth of Reason, The Liberal Institute, and the Ludwig von Mises Institute. Mr. Stolyarov also published his articles on Associated Content (subsequently the Yahoo! Contributor Network) from 2007 until its closure in 2014, in an effort to assist the spread of rational ideas. He held the highest Clout Level (10) possible on the Yahoo! Contributor Network and was one of its Page View Millionaires, with over 3.1 million views.
Mr. Stolyarov holds the professional insurance designations of Associate of the Society of Actuaries (ASA), Associate of the Casualty Actuarial Society (ACAS), Member of the American Academy of Actuaries (MAAA), Chartered Property Casualty Underwriter (CPCU), Associate in Reinsurance (ARe), Associate in Regulation and Compliance (ARC), Associate in Personal Insurance (API), Associate in Insurance Services (AIS), Accredited Insurance Examiner (AIE), and Associate in Insurance Accounting and Finance (AIAF).
Mr. Stolyarov has written a science fiction novel, Eden against the Colossus, a philosophical treatise, A Rational Cosmology, a play, Implied Consent, and a free self-help treatise, The Best Self-Help is Free. You can watch his YouTube Videos. Mr. Stolyarov can be contacted at email@example.com.
Learn about Mr. Stolyarov's novel, Eden against the Colossus, here.