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Preface P-1 Contents Preface P-7 Syllabus Reference P-10 Flow Chart P-13 Chapter 0 Chapter 1 Some Factual Information C0-1 0.1 0.2 0.3 0.4 0.5 C0-1 C0-3 C0-3 C0-4 C0-6 Traditional Life Insurance Contracts Modern Life Insurance Contracts Underwriting Life Annuities Pensions Survival Distributions 1.1 1.2 1.3 1.4 1.5 Age-at-death Random Variables Future Lifetime Random Variable Actuarial Notation Curtate Future Lifetime Random Variable Force of Mortality Exercise 1 Solutions to Exercise 1 Chapter 2 Life Tables 2.1 2.2 2.3 2.4 2.5 Life Table Functions Fractional Age Assumptions Select-and-Ultimate Tables Moments of Future Lifetime Random Variables Useful Shortcuts Life Insurances 3.1 3.2 3.3 3.4 3.5 3.6 3.7 C1-21 C1-27 C2-1 C2-6 C2-18 C2-29 C2-39 C2-43 C2-52 C3-1 Continuous Life Insurances Discrete Life Insurances mthly Life Insurances Relating Different Policies Recursions Relating Continuous, Discrete and mthly Insurance Useful Shortcuts Exercise 3 Solutions to Exercise 3 Actex Learning C1-1 C1-4 C1-6 C1-10 C1-12 C2-1 Exercise 2 Solutions to Exercise 2 Chapter 3 C1-1 | Johnny Li and Andrew Ng | SoA Exam MLC C3-2 C3-17 C3-26 C3-29 C3-36 C3-43 C3-46 C3-48 C3-61 Preface P-2 Chapter 4 Life Annuities 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 Chapter 5 Continuous Life Annuities Discrete Life Annuities (Due) Discrete Life Annuities (Immediate) mthly Life Annuities Relating Different Policies Recursions Relating Continuous, Discrete and mthly Life Annuities Useful Shortcuts C4-47 C4-61 Premium Calculation C5-1 Traditional Insurance Policies Net Premium and Equivalence Principle Net Premiums for Special Policies The Loss-at-issue Random Variable Percentile Premium and Profit C5-1 C5-3 C5-12 C5-18 C5-27 Exercise 5 Solutions to Exercise 5 C5-38 C5-55 Net Premium Reserves C6-1 6.1 6.2 6.3 6.4 The The The The Prospective Approach Recursive Approach: Basic Idea Recursive Approach: Further Applications Retrospective Approach Exercise 6 Solutions to Exercise 6 Chapter 7 C4-1 C4-18 C4-25 C4-29 C4-31 C4-35 C4-38 C4-44 Exercise 4 Solutions to Exercise 4 5.1 5.2 5.3 5.4 5.5 Chapter 6 C4-1 Insurance Models Including Expenses 7.1 7.2 7.3 7.4 Gross Premium Gross Premium Reserve Expense Reserve and Modified Reserve Basis, Asset Share and Profit Exercise 7 Solutions to Exercise 7 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC C6-2 C6-15 C6-24 C6-33 C6-41 C6-65 C7-1 C7-1 C7-5 C7-13 C7-23 C7-39 C7-57 Preface Chapter 8 P-3 Multiple Decrement Models: Theory 8.1 8.2 8.3 8.4 Multiple Decrement Table Forces of Decrement Associated Single Decrement Discrete Jumps Exercise 8 Solutions to Exercise 8 Chapter 9 Multiple Decrement Models: Applications 9.1 9.2 9.3 9.4 Calculating Actuarial Present Values of Cash Flows Calculating Reserve and Profit Cash Values Calculating Asset Shares under Multiple Decrement C8-1 C8-1 C8-5 C8-10 C8-23 C8-29 C8-40 C9-1 C9-1 C9-4 C9-17 C9-23 Exercise 9 Solutions to Exercise 9 C9-28 C9-40 Chapter 10 Multiple State Models C10-1 10.1 10.2 10.3 10.4 10.5 Discrete-time Markov Chain Continuous-time Markov Chain Kolmogorov’s Forward Equations Calculating Actuarial Present Value of Cash Flows Calculating Reserves Exercise 10 Solutions to Exercise 10 Chapter 11 Multiple Life Functions 11.1 11.2 11.3 Multiple Life Statuses Insurances and Annuities Dependent Life Models Exercise 11 Solutions to Exercise 11 Chapter 12 Interest Rate Risk 12.1 12.2 12.3 Yield Curves Interest Rate Scenario Models Diversifiable and Non-Diversifiable Risks Exercise 12 Solutions to Exercise 12 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC C10-4 C10-13 C10-19 C10-32 C10-39 C10-44 C10-63 C11-1 C11-2 C11-17 C11-31 C11-43 C11-63 C12-1 C12-1 C12-13 C12-17 C12-26 C12-37 Preface P-4 Chapter 13 Profit Testing 13.1 13.2 13.3 C13-1 Profit Vector and Profit Signature Profit Measures Using Profit Test to Compute Premiums and Reserves Exercise 13 Solutions to Exercise 13 Chapter 14 Universal Life Insurance 14.1 14.2 14.3 14.4 14.5 14.6 Basic Policy Design Cost of Insurance and Surrender Value Other Policy Features Projecting Account Values Profit Testing Asset Shares for Universal Life Policies Exercise 14 Solutions to Exercise 14 Chapter 15 Participating Insurance 15.1 15.2 C13-1 C13-12 C13-16 C13-24 C13-32 C14-1 C14-2 C14-5 C14-17 C14-21 C14-30 C14-40 C14-43 C14-53 C15-1 Dividends Bonuses C15-2 C15-10 Exercise 15 Solutions to Exercise 15 C15-24 C15-28 Chapter 16 Pension Mathematics 16.1 16.2 16.3 16.4 16.5 The Salary Scale Function Pension Plans Setting the DC Contribution Rate DB Plans and Service Table Funding of DB Plans Exercise 16 Solutions to Exercise 16 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC C16-1 C16-1 C16-12 C16-14 C16-19 C16-39 C16-45 C16-60 Preface P-5 Appendix 1 Numerical Techniques 1.1 1.2 1.3 Numerical Integration Euler’s Method Solving Systems of ODEs with Euler’s Method Appendix 2 Review of Probability 2.1 2.2 2.3 2.4 2.5 2.6 Probability Laws Random Variables and Expectations Special Univariate Probability Distributions Joint Distribution Conditional and Double Expectation The Central Limit Theorem A1-1 A1-1 A1-7 A1-12 A2-1 A2-1 A2-2 A2-6 A2-9 A2-10 A2-12 Exam MLC: General Information T0-1 Mock Test 1 T1-1 Solution T1-29 Mock Test 2 T2-1 Solution T2-28 Mock Test 3 T3-1 Solution T3-29 Mock Test 4 T4-1 Solution T4-29 Mock Test 5 T5-1 Solution T5-29 Mock Test 6 T6-1 Solution T6-29 Mock Test 7 T7-1 Solution T7-29 Mock Test 8 T8-1 Solution Actex Learning T8-28 | Johnny Li and Andrew Ng | SoA Exam MLC Preface P-6 Suggested Solutions to MLC May 2012 S-1 Suggested Solutions to MLC Nov 2012 S-17 Suggested Solutions to MLC May 2013 S-29 Suggested Solutions to MLC Nov 2013 S-45 Suggested Solutions to MLC April 2014 S-55 Suggested Solutions to MLC Oct 2014 S-69 Suggested Solutions to MLC April 2015 S-81 Suggested Solutions to MLC Oct 2015 S-97 Suggested Solutions to MLC May 2016 S-109 Suggested Solutions to MLC Oct 2016 S-123 Suggested Solutions to Sample Structural Questions S-133 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 1: Survival Distributions C1-1 Chapter 1 Survival Distributions OBJECTIVES 1. To define future lifetime random variables 2. To specify survival functions for future lifetime random variables 3. To define actuarial symbols for death and survival probabilities and develop relationships between them 4. To define the force of mortality In Exam FM, you valued cash flows that are paid at some known future times. In Exam MLC, by contrast, you are going to value cash flows that are paid at some unknown future times. Specifically, the timings of the cash flows are dependent on the future lifetime of the underlying individual. These cash flows are called life contingent cash flows, and the study of these cash flows is called life contingencies. It is obvious that an important part of life contingencies is the modeling of future lifetimes. In this chapter, we are going to study how we can model future lifetimes as random variables. A few simple probability concepts you learnt in Exam P will be used. 1. 1 Age-at-death Random Variable Let us begin with the age-at-death random variable, which is denoted by T0. The definition of T0 can be easily seen from the diagram below. Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 1: Survival Distributions C1-2 Death occurs Age T0 0 The age-at-death random variable can take any value within [0, ∞). Sometimes, we assume that no individual can live beyond a certain very high age. We call that age the limiting age, and denote it by ω. If a limiting age is assumed, then T0 can only take a value within [0, ω]. We regard T0 as a continuous random variable, because it can, in principle, take any value on the interval [0, ∞) if there is no limiting age or [0, ω] if a limiting age is assumed. Of course, to model T0, we need a probability distribution. The following notation is used throughout this study guide (and in the examination). − F0(t) = Pr(T0 ≤ t) is the (cumulative) distribution function of T0. − f0(t) = d F0 (t ) is the probability density function of T0. For a small interval Δt, the product dt f0(t)Δt is the (approximate) probability that the age at death is in between t and t + Δt. In life contingencies, we often need to calculate the probability that an individual will survive to a certain age. This motivates us to define the survival function: S0(t) = Pr(T0 > t) = 1 – F0(t). Note that the subscript “0” indicates that these functions are specified for the age-at-death random variable (or equivalently, the future lifetime of a person age 0 now). Not all functions can be regarded as survival functions. A survival function must satisfy the following requirements: 1. S0(0) = 1. This means every individual can live at least 0 years. 2. S0(ω ) = 0 or lim S 0 (t ) = 0. This means that every individual must die eventually. t →∞ 3. S0(t) is monotonically decreasing. This means that, for example, the probability of surviving to age 80 cannot be greater than that of surviving to age 70. Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 1: Survival Distributions C1-3 Summing up, f0(t), F0(t) and S0(t) are related to one another as follows. F O R M U L A Relations between f0(t), F0(t) and S0(t) f 0 (t ) = d d F0 (t ) = − S0 (t ) , dt dt ∞ t t 0 S 0 (t ) = ∫ f 0 (u )du = 1 − ∫ f 0 (u )du = 1 − F0 (t ) , Pr(a < T0 ≤ b) = ∫ b f 0 (u )du = F0 (b) − F0 (a ) = S 0 (a ) − S 0 (b) . a (1.1) (1.2) (1.3) Note that because T0 is a continuous random variable, Pr(T0 = c) = 0 for any constant c. Now, let us consider the following example. Example 1.1 [Structural Question] You are given that S0(t) = 1 – t/100 for 0 ≤ t ≤ 100. (a) Verify that S0(t) is a valid survival function. (b) Find expressions for F0(t) and f0(t). (c) Calculate the probability that T0 is greater than 30 and smaller than 60. Solution (a) First, we have S0(0) = 1 – 0/100 = 1. Second, we have S0(100) = 1 – 100/100 = 0. Third, the first derivative of S0(t) is −1/100, indicating that S0(t) is non-increasing. Hence, S0(t) is a valid survival function. (b) We have F0(t) = 1 – S0(t) = t/100, for 0 ≤ t ≤ 100. Also, we have and f0(t) = d F0(t) = 1/100, for 0 ≤ t ≤ 100. dt (c) Pr(30 < T0 < 60) = S0(30) – S0(60) = (1 – 30/100) – (1 – 60/100) = 0.3. [ END ] Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 1: Survival Distributions C1-4 1. 2 Future Lifetime Random Variable Consider an individual who is age x now. Throughout this text, we use (x) to represent such an individual. Instead of the entire lifetime of (x), we are often more interested in the future lifetime of (x). We use Tx to denote the future lifetime random variable for (x). The definition of Tx can be easily seen from the diagram below. 0 x x + Tx Now Death occurs 0 Tx Age Time from now [Note: For brevity, we may only display the portion starting from age x (i.e., time 0) in future illustrations.] If there is no limiting age, Tx can take any value within [0, ∞). If a limiting age is assumed, then Tx can only take a value within [0, ω − x]. We have to subtract x because the individual has attained age x at time 0 already. We let Sx(t) be the survival function for the future lifetime random variable. The subscript “x” here indicates that the survival function is defined for a life who is age x now. It is important to understand that when modeling the future lifetime of (x), we always know that the individual is alive at age x. Thus, we may evaluate Sx(t) as a conditional probability: S x (t ) = Pr(Tx > t ) = Pr(T0 > x + t | T0 > x) = Pr(T0 > x + t ∩ T0 > x) Pr(T0 > x + t ) S0 ( x + t ) . = = Pr(T0 > x) Pr(T0 > x) S0 ( x) The third step above follows from the equation Pr( A | B) = Exam P. Actex Learning Pr( A ∩ B) , which you learnt in Pr( B) | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 1: Survival Distributions C1-5 F O R M U L A Survival Function for the Future Lifetime Random Variable S x (t ) = S0 ( x + t ) S0 ( x) (1.4) With Sx(t), we can obtain Fx(t) and fx(t) by using Fx(t) = 1 – Sx(t) and fx(t) = d Fx (t ) , dt respectively. Example 1.2 [Structural Question] You are given that S0(t) = 1 – t/100 for 0 ≤ t ≤ 100. (a) Find expressions for S10(t), F10(t) and f10(t). (b) Calculate the probability that an individual age 10 now can survive to age 25. (c) Calculate the probability that an individual age 10 now will die within 15 years. Solution (a) In this part, we are asked to calculate functions for an individual age 10 now (i.e., x = 10). Here, ω = 100 and therefore these functions are defined for 0 ≤ t ≤ 90 only. First, we have S10 (t ) = S0 (10 + t ) 1 − (10 + t ) /100 t = = 1 − , for 0 ≤ t ≤ 90. S0 (10) 1 − 10 /100 90 Second, we have F10(t) = 1 – S10(t) = t/90, for 0 ≤ t ≤ 90. Finally, we have f10 (t ) = d 1 F10 (t ) = . dt 90 (b) The probability that an individual age 10 now can survive to age 25 is given by Pr(T10 > 15) = S10(15) = 1 − 15 5 = . 90 6 (c) The probability that an individual age 10 now will die within 15 years is given by Pr(T10 ≤ 15) = F10(15) = 1 − S10(15) = 1 . 6 [ END ] Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 1: Survival Distributions C1-6 1. 3 Actuarial Notation For convenience, we have designated actuarial notation for various types of death and survival probabilities. Notation 1: t px We use t px to denote the probability that a life age x now survives to t years from now. By definition, we have t px = Pr(Tx > t) = Sx(t). When t = 1, we can omit the subscript on the left-hand-side; that is, we write 1px as px. Notation 2: t qx We use t qx to denote the probability that a life age x now dies before attaining age x + t. By definition, we have t qx = Pr(Tx ≤ t) = Fx(t). When t = 1, we can omit the subscript on the left-hand-side; that is, we write 1qx as qx. Notation 3: t|u qx We use t |u qx to denote the probability that a life age x now dies between ages x + t and x + t + u. By definition, we have t|u qx = Pr(t < Tx ≤ t + u) = Fx(t + u) − Fx(t) = Sx(t) − Sx(t + u). When u = 1, we can omit the subscript u; that is, we write t |1 qx as t | qx. Note that when we describe survival distributions, “p” always means a survival probability, while “q” always means a death probability. The “|” between t and u means that the death probability is deferred by t years. We read “t | u” as “t deferred u”. It is important to remember the meanings of these three actuarial symbols. Let us study the following example. Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 7: Insurance Models Including Expenses Chapter 7 C7-1 Insurance Models Including Expenses OBJECTIVES 1. To calculate gross premium and gross premium reserve 2. To calculate expense reserve and FPT and other modified reserves 3. To calculate asset share, annual profit and gain This is an important chapter and serves as a first check point of the basics of life contingencies. In this chapter we discuss how expenses are incorporated into the calculation of premiums and reserves. We are going to assume that the expenses are incurred with certainty. 7. 1 Gross Premium Four Types of Expenses Recall that net premiums are calculated under a basis that does not allow for expenses. The net premium is used to pay for the cost of insurance. However, when a policy is sold, various expenses are incurred by the insurer. It is important to understand the characteristics of these expenses because they have a significant effect on premiums and reserves. Initial / acquisition expenses Initial expenses are expenses incurred when the policy is issued. This typically includes the cost of underwriting and other costs of acquisition, including clerical expenses (setting up records on computer systems), medical check-up fees, commissions and advertising expenses. Some of these costs are fixed, while some of them vary with the amount of insurance or size of the premium. Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 7: Insurance Models Including Expenses C7-2 Maintenance / renewal expenses After the policy is issued, there are continuing administrative expenses and commission. For example, there is money spent on collecting premium payments and keeping track of all the accounting records. Such expenses are normally incurred each time a premium is payable. Under the US commission system, usually the rate of commission is higher in the first year, and thus the maintenance expenses are typically smaller than initial expenses. You will see that this would create a serious problem in later sections. Settlement / termination expenses Upon the termination of the policy, there are some paperwork and costs to finalize and disburse benefit payments. Occasionally, a claim investigation is required and incurs a cost. Usually, settlement expenses are insignificant when compared to acquisition and renewal expenses. Other miscellaneous expenses There are some other expenses that may or may not be directly related to the policies but are loaded to the policies for pricing. One such example is investment expense, which is reflected in pricing by a reduction in the assumed interest rate. Another example includes general expenses spent on research, legal services, taxes, licenses and other fees. Typically, we can summarize and aggregate all expenses in the following form: Year 1st year 2nd year M Per policy 40 6 M Per 1000 insurance 5 0.5 M Percentage of premium 50% 15% M The expenses above are payable at the beginning of each policy year Settlement expense: 20 per policy plus 0.4 per 1000 insurance For example, for a policy with a death benefit of 5000, and an annual level premium of 800: 1st year expense (payable at issuance) is 40 + 5 × 5 + 0.5 × 800 = 465 2nd year expense (payable 1 year after issuance) is 6 + 0.5 × 5 + 0.15 × 800 = 128.5 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 7: Insurance Models Including Expenses C7-3 Upon death, the settlement expense is 20 + 0.4 × 5 = 22. In what follows, we need to compute the APV of expenses. The APV of settlement expenses is obviously in the form of a term or endowment insurance. The APV of initial and renewal expense are in the form of a life annuity. For example, for an n-year level annual premium policy, with premium G, if we have the following expenses: Year 1st year Renewal years e0 + c0 G Per policy e0 e1 e1 + c1G e1 + c1G Percentage of premium c0 c1 ... e1 + c1 G time 0 1 2 ... n−1 n then the APV of the all renewal expenses is (e1 + c1G )a x:n −1| . The APV of initial and renewal expenses is (e0 + c 0 G ) + (e1 + c1G )a x:n −1| = (e0 + c0 G ) + (e1 + c1G )(a&&x:n| − 1) = (e0 − e1 ) + (c0 − c1 )G + (e1 + c1G )a&&x:n| Expense Augmented Model We can formulate the gross future loss random variable at issue that incorporates expense payments by defining g 0L = PV of benefit outgo + PV of expenses − PV of gross premium income. The superscript g denotes “gross.” Under the equivalence principle, the gross premium (or expense-loaded premium) is the premium such that the mean of 0Lg is 0 under a specific set of mortality, interest and expenses assumptions that form a premium basis. (We shall elaborate on basis later in section 4.) That is, APV of benefits + APV of expenses = APV of gross premium income. Other premium principles (e.g. percentile premium, premium calculated based on a profit margin) can also be used and they would be discussed in Chapters 12 and 13. In what follows we usually use a level gross premium, though in the discussion on the general theory we permit Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 7: Insurance Models Including Expenses C7-4 other premium payment patterns. The gross premium at time t is Gt, while the net premium at time t is πt. As in the previous chapters, usually one needs not write down the precise mathematical formulation of 0Lg when the equivalence principle is applied. However, the form of 0Lg would be needed if one computes the percentile or the variance of 0Lg, or invoke any other premium principles. The good news is that such questions are rarely examined in Exam MLC. Example 7.1 [Structural Question] Consider a 4-year annual level premium special endowment insurance on (40). The death benefit is 1000, payable at the end of the year of death if death occurs within 4 years. If the life survives 4 years, 1200 is payable 4 years after the issuance of the policy. Calculate the net level annual premium and level gross premium under the following basis: (i) Mortality: q40 = 0.08, q41 = 0.09, q42 = 0.10, q43 = 0.11. (ii) Expenses: Initial expenses and renewal expenses (payable at the beginning of each policy year) Year 1st year Renewal years Per policy 10 2 Percentage of premium 25% 5% Settlement expense is 5, payable at the end of the year for the first 3 years. There is no settlement expense in the fourth year. (iii) Interest: 6% annual effective. Solution We first calculate the required insurance and annuity functions: a&&40:4| = 1 + 0.92 0.92 × 0.91 0.92 × 0.91 × 0.90 + + = 3.2456659, 1.06 1.06 2 1.06 3 4E40 = 0.92 × 0.91 × 0.90 × 0.89 = 0.53117579, 1.06 4 1 A40 = A40:4| − 4 E 40 = 1 − :4| 0.06 × 3.2456659 − 0.53117579 = 0.28510727, 1.06 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 7: Insurance Models Including Expenses 1 A40 = :3| C7-5 0.08 0.92 × 0.09 0.92 × 0.91 × 0.1 + + = 0.21945633 . 1.06 1.06 2 1.06 3 Calculation of net level premium: Let π be the net level premium. 1 πa&&40:4| = 1000 A40 + 1200 4 E 40 :4| π= 1 1000 A40 + 1200 4 E 40 :4| a&&40:4| = 284.2308 Calculation of gross premium: Let G be the level gross premium. The initial and renewal expenses add up to 10 + 0.25G + (2 + 0.05G )a 40:3| = 8 + 0.2G + (2 + 0.05G )a&&40:4| . 1 The APV of the settlement expense is 5A40 . :3| 1 1 Ga&&40:4| = 1000 A40 + 1200 4 E 40 + 5 A40 + 8 + 0.2G + (2 + 0.05G )a&&40:4| :4| :3| G= 1 1 1000 A40 + 1200 4 E 40 + 5 A40 + 8 + 2a&&40:4| :3| :4| 0.95a&&40:4| − 0.2 = 325.3494 [ END ] The insurance company may charge a premium that is greater than the gross premium because the insurer can only break even but not make a profit if the insured is charged a gross premium. 7. 2 Gross Premium Reserve Consider an n-year term insurance policy which is still in force t years after issue. Define the present value of gross future loss random variable by g tL = Present value, at time t, of future benefits and expenses − Present value at time t, of future gross premiums. Death benefit: bt − 1 Settlement expense: Et − 1 Renewal / Initial expense: Rt − 1 bt Et Rt bt + 1 Et + 1 Rt + 1 bn − 1 En − 1 Rn − 1 bn En time 0 Gross premiums: … t−1 t t+1 Gt − 1 Gt Gt + 1 Actex Learning … n−1 n Gn − 1 | Johnny Li and Andrew Ng | SoA Exam MLC Chapter 7: Insurance Models Including Expenses C7-6 The present value, at time t, of expenses includes the renewal expense at time t because they are associated with the premium then due at time t. The settlement expense at time t is not included in the calculation of tLg because tLg is defined condition on Tx > t. The gross premium reserve (or expense-augmented reserve) at time t is the conditional mean g tV = E( tLg | Tx > t ), where the expectation is calculated under a specific basis. As a result, gross premium reserve can be calculated prospectively by g tV = APV at time t of future benefits and expenses − APV at time t of future gross premiums. This definition holds no matter if the policy is discrete, continuous or semi-continuous. The gross premium above is the actual premium charged for the policy. The gross premium may be, or may not be determined from the equivalence principle. If it is determined from the equivalence principle, then 0Vg = 0. (Note, however, that when one compute the net premium reserve, net premium is always used, so that 0V must be 0.) Example 7.2 Consider the set up in Example 7.1. Calculate the gross premium reserve at the end of year 2 and year 3. Solution Death benefit: 1000 Survival benefit: 5 Settlement expense: Renewal expenses: 2 + 0.05G Initial expense: 10 + 0.25G 1000 5 2 + 0.05G 1000 5 2 + 0.05G 1000 1200 time Gross premiums: For 2Vg, 0 1 2 3 G G G G 4 g 2V Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-1 Exam MLC Mock Test 4 SECTION A − Multiple Choice Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-2 **BEGINNING OF EXAMINATION** 1. For a fully discrete whole life annuity immediate of 10 per year issued to (37), you are given: (i) Mortality follows the Illustrative Life Table. (ii) i = 0.06 (iii) Y is the present value random variable for the annuity immediate. Calculate the standard deviation of Y. (A) 21 (B) 22 (C) 23 (D) 24 (E) 25 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 2. T4-3 The present value random variable for an insurance policy on (x) is expressed as: ⎧ 0 ⎪2v K x +1 ⎪ Z = ⎨ K x +1 ⎪v ⎪⎩2v K x +1 if K x < 5 if 5 ≤ K x < 10 if 10 ≤ K x < 15 thereafter Which of the following is a correct expression for E(Z)? (A) 25|Ax − 10|Ax (B) 25|Ax − 10|Ax + 215|Ax (C) 25ExAx − 10ExAx+10 + 15ExAx+15 (D) 25ExAx+5 − 10ExAx+10 + 15ExAx+15 (E) 5Ex(2Ax+5 − 5Ex+5Ax+10 + 15Ex+5Ax+15) Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-4 3. For a special fully continuous whole life insurance on (44), you are given: (i) Premiums and benefits: Premium Rate Benefit (ii) μx = First 20 years 3P 100,000 Thereafter P 300,000 1 for x ≤ 84. 84 − x (iii) δ = 0.06 Calculate P using the equivalence principle. (A) 1,900 (B) 1,915 (C) 1,930 (D) 1,945 (E) 1,960 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 4. T4-5 You are given: (i) i = 0.05 (ii) A60 = 0.560 (iii) A40 = 0.176 (iv) 20p40 = 0.75 ( 3) using the two-term Woolhouse approximation. Calculate a 40 :20| (A) 13.7 (B) 14.2 (C) 14.5 (D) 14.9 (E) 15.1 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-6 5. For a multiple decrement model on (60), you are given: (i) μ 60(1)+t follows the Illustrative Life Table for t ≥ 0. (ii) μ 60(τ +) t = 2.5μ 60(1)+t for t ≥ 0. Calculate the probability that failure of (60) occurs during the 10th year due to cause 1. (A) 0.25 (B) 0.27 (C) 0.29 (D) 0.31 (E) 0.33 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 19. T4-21 For a defined benefit pension plan, you are given: (i) The retirement benefit is 15 per month of service. (ii) Retirement is allowed beginning at age 63. (iii) There is one employee who is currently exact age 45 and was hired at exact age 40. (iv) i = 0.07 (v) The following data x 63 64 65 q ′x( r ) 0.2 0.3 1.0 a&&x(12) 10 9 8.5 Assume: (i) Employees retire only on their birthdays. (ii) There are no pre-retirement decrements. Calculate the actuarial present value of the projected retirement benefit for this employee. (A) 10,600 (B) 11,400 (C) 12,600 (D) 13,900 (E) 15,300 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-22 20. Consider a universal life insurance sold to (40). The death benefit is $120,000 plus the account value at the end of the year of death. You are given: (i) The following basis is used to calculate cost of insurance: − Mortality follows the Illustrative Life Table. − Interest rate is 5% per annum effective. (ii) For each premium paid, the expense charge is $50 plus 3% of the premium. (iii) There is no corridor requirement. (iv) The death benefit is payable at the end of the year of death. (v) The surrender penalties are as follows: Year of surrender Penalty 1 $3100 2 $2700 3 $2500 ≥4 $900 Project the cash value at the end of the third year using the following assumptions: − The policy remains in force for three years. − Interest is credited to the policyholder’s account at 1% per annum. − The policyholder pays a premium of $2000 at the beginning of each year. (A) 0 (B) 770 (C) 1340 (D) 1770 (E) 2240 Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-23 Exam MLC Mock Test 4 SECTION B − Written Answer Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-24 1. (7 points) For this question, you are not required to show your steps. (a) (4 points) Identify the actuarial functions with the following integral or sum representations. Verbally explain the meaning behind each of the actuarial functions you use. n (i) ∫v (ii) 1 2 3 ⎞ 1 ⎛⎜ n m m m ⎟ p v p v p v ... p v + + + + x n x 1 2 3 x x ⎟ m ⎜⎝ m m m ⎠ (iii) t 0 ∞ ∑v k = n +1 (iv) (b) ∫ ∞ 0 p x dt t k k px at| t p x μ x +t dt (3 points) For each of the following actuarial functions, write down its integral or summation form and explain verbally what it means. (i) n| (ii) a&&x:n| Ax (iii) ex Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 2. T4-25 (13 points) (a) (4 points) Explain in words the difference between Type A and Type B universal life insurance policies. (b) (5 points) For a Type A universal life insurance policy with a face amount of $60,000, you are given: • The account value on December 31, 2013 was $30,000. • On January 1, 2014, a premium of $2,500 was made. No other premiums were made in 2014. • The total expense charge and the cost of insurance deducted on January 1, 2014 were $170 and $250, respectively. • The credited interest rate in 2014 was 8% per annum effective. • The corridor factor requirement is 2.5. • Death occurred in 2014 and a death benefit was payable at the end of 2014. Compute the amount of the death benefit. (c) (4 points) Suppose that the universal life insurance policy in (b) is a Type B policy with an additional death benefit of $60,000 instead. Recalculate the amount of the death benefit. Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-26 3. (14 points) (a) (9 points) For each of the following risks, determine if the risk is diversifiable. Explain your answers verbally. (i) The uncertainty associated with future lifetimes of policyholders, provided that the underlying mortality rates are fixed and known and that policyholders' lifetimes are independent (ii) The uncertainty associated with death probabilities (iii) The uncertainty associated with interest rates (b) (5 points) For pricing a 3-year life annuity-due of 1 on (x) to be issued on January 1, 2015, you are given: = 0.95 − 0.03k, k = 1, 2 • kpx • δ(k) is the force of interest for year k, k = 2014, 2015, 2016. • δ(2014) = 0.03 • δ(k + 1) − δ(k) equals 0.01 with probability 70% and equals −0.01 with probability 30%, for k = 2014, 2015. • Y is the expected present value of this annuity on January 1, 2015. Calculate Y. Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 4. T4-27 (15 points) You are given: • i = 0.05 • 10|A40 • 2 • a&&50 = 14.63606 = 0.178809, A40 = 0.20799, 10E40 = 0.590041 A40 = 0.06741, 2A50 = 0.12446 Let Y be the present value random variable for a 10-year deferred life annuity-due to (40) of 1 per year. Let Z1 be the present value random variable for a whole life insurance of 1 on (40) with benefits at the end of the year of death. Let Z2 be the present value random variable for a 10-year endowment insurance of 1 on (40) with benefits at the end of the year of death. (a) (3 points) Express Y, Z1 and Z2 in terms of K40, v and d. (b) (2 points) Using your results in (a), show that Y = 21(Z2 – Z1). (c) (5 points) (i) Show that Z1Z 2 = Z 32 + v10 Z 4 for some present value random variables Z3 and Z4. Identify Z3 and Z4. (ii) Hence, calculate E(Z1Z2). (d) (5 points) Calculate the variance of Y. Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC Mock Test 4 T4-28 5. (7 points) Let x, y and m be positive integers. The lifetimes of (x) and (y) are independent and follow the uniform distribution of death (UDD) fractional age assumption. (a) (4 points) It is known that Ax( m ) = assumption. (i) i i (m) Ax under the specified fractional age Using the given fact, or otherwise, show that under the specified fractional age assumption, a&&x( m ) = α (m)a&&x − β (m) , id i − i (m) where α (m) = ( m ) ( m ) and β (m) = ( m ) ( m ) . i d i d (ii) By considering the result from (a)(i), derive a formula for calculating a&&x( m:n)| under the specified fractional age assumption. Express your answer in terms of α(m), β(m), nEx and a&&x:n| . (b) (3 points) It is known that under the specified fractional age assumption, a&&xy( m ) = α (m)a&&xy − β (m) − 1 2 2 ⎞ ∞ k +1 i ⎛ + ⎟∑ v k pxy qx + k q y + k ⎜1 + − i( m)d ( m) ⎝ m d (m) i ⎠ k =0 ≈ α (m)a&&xy − β (m). (i) Explain why ∞ ∑v k =0 (ii) k +1 k p xy q x + k q y + k is typically small. Rather than using the UDD assumption and the approximation above, one may approximate a&&xy( m ) by using the Woolhouse formula. Write down the Woolhouse formula for approximating a&&xy( m ) . Express your answer in terms of a&&xy , m, δ and μxy. **END OF EXAMINATION** Actex Learning | Johnny Li and Andrew Ng | SoA Exam MLC