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Life Pricing Exam > Section C > Flashcards

Section C Flashcards

1
Q

Life and Annuity Assumptions

A

MILES APP (iPhone app that talks to your running shoes)

  1. Mortality
  2. Interest rates
  3. Lapse rates
  4. Expenses
  5. Sales distribution and volume
  6. Average Size
  7. Premium persistency and payment pattern
  8. Policyholder behavior (option election, annuitization, etc.)

Experience Assumptions for Ind Life and Ann (LP-107-07)
Various Other Texts

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2
Q

Steps to Establish Experience Assumptions

A
  1. Identify the assumption required
  2. Determine the structure and each assumption
  3. Analyze experience and trends
  4. Review and adjust assumptions and reasonableness, consistency, and appropriateness
  5. Document assumptions
  6. Monitor experience and updated assumptions

Experience Assumptions for Ind Life and Ann (LP-107-07)
Expected Mortality: Fully Underwritten

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3
Q

Key principles in deciding the complexity of the assumption structure

A
  1. Differences in experiences assumptions should reflect differences in experience
  2. The definition of a class should be easily understood
  3. The number of classes should be practical and cost effective

Experience Assumptions for Ind Life and Ann (LP-107-07)

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4
Q

Experience Classes

A

When calculating an assumption, experience should be divided into experience classes

Experience classes will consist of contracts that:

  1. Are of similar type
  2. Have similar structure
  3. Are issued over a continuous period of time
  4. Have similar marketing objectives

Experience Assumptions for Ind Life and Ann (LP-107-07)

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5
Q

Analyzing Experience and Trends

A

USEERRs

  1. Use actual or similar experience
  2. Sensitivity test the assumptions
  3. Evaluate credibility of data
  4. Evaluate quality of data
  5. Reflect trends in experience as appropriate
  6. Reflect internal and external factors

Experience Assumptions for Ind Life and Ann (LP-107-07)

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6
Q

Assumption Documentation

A
  1. What the assumption is
    a. Numerical values
    b. Experience classes
  2. Data underlying the assumption
  3. How the assumption was developed
    a. Credibility method used
    b. Any changes from prior study
  4. How to use the assumption

Experience Assumptions for Ind Life and Ann (LP-107-07)

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7
Q

Structure of Mortality Assumption

A
  1. Type of mortality table: Aggregate, fully select, or select and ultimate
  2. ANB vs. ALB
    a. LaTeX needed
    b. LaTeX needed
  3. Common experience
    a. Age/duration
    b. Gender
    c. Tobacco use
    d. Underwriting class (such as preferred, super preferred)
    e. Policy size
  4. Mortality Improvement

Experience Assumptions for Ind Life and Ann (LP-107-07)

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8
Q

Analyzing Mortality Experience

A

CRAM

  1. Credibility
  2. Risk covered
  3. Adjusting mortality for special situations
    a. Multiple life policies
    b. Substandard mortality
    c. Term conversions
    d. Anti-selection
    e. Blending mortality tables
    f. Adjusting similar experience
  4. Mortality studies

Experience Assumptions for Ind Life and Ann (LP-107-07)

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9
Q

Credibility of Mortality Assumption

A
  1. Credibility is measured through a confidence interval (CI)
  2. 95% CI = m +/- 1.96 * s
    a. m = n * q
    b. s^2 = n * p * q
  3. Enhancing credibility
    a. Use multiple years of exposures
    b. Group ages into 5 or 10 age groups
    c. Could do an actual to expected analysis using an industry study
  4. Expected value and variance for a group of policies – by counts

LaTeX needed

  1. Expected value and variance for a group of policies – by amounts

LaTeX needed

Experience Assumptions for Ind Life and Ann (LP-107-07)

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10
Q

Risks Covered in a Mortality Study

A

Only include standard risks in mortality study

Exclude the following:

  1. Policies not subject to normal underwriting
  2. Substandard policies
  3. Extended term or reduced paid up insurance
  4. Multiple life policies

Experience Assumptions for Ind Life and Ann (LP-107-07)

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11
Q

Mortality Studies

A
  1. Anniversary-to-anniversary or calendar year studies
  2. 5 years is the typical study period
  3. Amounts vs. Counts – use by amounts to reflect financial impact
  4. Mortality rate for a cell = Total Claims / Total Exposure
  5. Exact exposures

LaTeX needed

  1. Balducci assumption

LaTeX needed

  1. Common to make simplifying assumption that lives lapse at the end of the year and deaths occur in the middle of the year

Experience Assumptions for Ind Life and Ann (LP-107-07)

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12
Q

Term Conversion

A
  1. Term conversions usually result in higher mortality
  2. Ways to handle term conversions
    a. Include in regular mortality studies – all permanent policyholders share in the extra cost
    b. Include a charge in the term pricing
  3. Formula for the cost of extra mortality s years after conversion

LaTex needed

Experience Assumptions for Ind Life and Ann (LP-107-07)

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13
Q

Conservations of Deaths

A
  1. Reflect anti-selection or new risk class in mortality experience
  2. The weighted average mortality of two populations balances back to the standard assumption
  3. One-year formula

LaTeX needed

  1. Multi-year formula

LaTeX needed

Experience Assumptions for Ind Life and Ann (LP-107-07)

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14
Q

Adjust Similar Experience to Reflect:

A

MR CUD (is chewing)

  1. Market - lower mortality for affluent markets
  2. Reinsurance quotes
  3. Company’s underwriting standards
  4. Underwriting classes and requirements
  5. Distribution channels

Experience Assumptions for Ind Life and Ann (LP-107-07)

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15
Q

Structure of Lapse Assumptions

A
  1. Common experience classes
    a. Duration
    b. Issue age
    c. Frequency of premium
    d. Policy size
    e. Plan type (term vs. UL)
    f. Marketing method
    g. Target market
  2. Shock lapse - may be applicable at end of surrender charge period
  3. Dynamic lapse - may be applicable for investment products

Experience Assumptions for Ind Life and Ann (LP-107-07)

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16
Q

Analyzing Lapse Experience

A
  1. Credibility is less of a concern for lapse rates when compared to mortality rates
  2. Lapse study – Almost identical to performing a mortality study
  3. Include these lapses in the lapse study:
    a. Termination without value due to non-payment of premium
    b. Cash surrenders
    c. Transfers to extended term or reduced paid up
  4. The lapse study may or may not include the following:
    a. Term conversions
    b. Partial withdrawals
    c. Premium persistency
    d. Termination because policy loan exceeds cash value

Experience Assumptions for Ind Life and Ann (LP-107-07)

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17
Q

Structure of Interest Rate Assumptions

A
  1. Deterministic, multiple deterministic scenarios, or stochastic scenarios
  2. Portfolio rates or New money rates
  3. Net Rate = Gross Rate - Spread
  4. Investment returns may be based on book value or market value
  5. Policy loans can be treated as an asset cash flow or a liability

Experience Assumptions for Ind Life and Ann (LP-107-07)

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18
Q

Analyzing Investment Experience

A
  1. Book value basis: I = 2I / (A + B - I)
  2. Market value basis: r = (B - A - C) / (A + C/2)
  3. Mutual fund returns: r = (B - A) / A
  4. Tim weighted return = LaTeX needed
  5. Dollar weighted return (R)
    LaTeX needed

Experience Assumptions for Ind Life and Ann (LP-107-07)

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19
Q

Analyzing Expense Experience

A
  1. Expense assumption = Expenses / Units
  2. Units could be: Premium, policies, per 1000 of insurance, other
  3. Number of units in an expense study
    a. If expenses are charged at the beginning of the year

Units = (A + B + N) / 2

b. If expenses are charged at the middle of the year:

Units = (A + B) / 2

  1. Expense allocation - indirect expenses need to be allocated down to the product level

Experience Assumptions for Ind Life and Ann (LP-107-07)

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20
Q

Projecting Expenses

A
  1. Historical expense trends
  2. Expected inflation rates
  3. Expected volume of business (economies of scale)
  4. Impact of any expected changes in the company’s business
  5. Productivity Gains

Experience Assumptions for Ind Life and Ann (LP-107-07)

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21
Q

Source of Data for Mortality Assumption

A
  1. Company Experience
  2. Inter-company experience
  3. Government or private sector population studies
  4. Medical studies
  5. Medical studies
  6. Private organizations, reinsurers, or actuarial organizations

Expected Mortality: Fully Underwritten

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22
Q

Criteria for a Good Credibility Method

A
  1. The method is practical to apply
  2. There is no double counting or omission
  3. All of the relevant information is used
  4. Results are reasonable in extreme cases
  5. The sub-category A/E ratios are reasonable when compared to company and industry experience

Expected Mortality: Fully Underwritten

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23
Q

Limited Fluctuation Credibility (LFCT)

A
  1. LFCT provides a method for establishing full and partial credibility
  2. Formula and notation
    LaTeX needed
  3. Formula for Z
    LaTex needed

Expected Mortality: Fully Underwritten

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24
Q

Steps for the LFCT Normalized Method

A
  1. Calculate mortality ratios and credibility factors for the entire company and for each sub-category
  2. Calculate total company blended experience mortality ratio and expected claims using the credibility factor
  3. Calculate the sub-category blended experience mortality ratio and expected claims using sub-category credibility factors
  4. Normalize by multiplying each sub-category’s results by the ratio of the total expected claims in step 2 to the sum of expected claims in step 3.

Expected Mortality: Fully Underwritten

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25
Q

Advantages of the Normalized Method

A
  1. The sum of expected claims within sub-categories equals the total expected claims
  2. All of the information is used
  3. The results are reasonable in extreme cases
  4. The sub-category A/E ratios fall within the original range
  5. Correlations between subcategories may be captured
  6. It is practical to apply

Expected Mortality: Fully Underwritten

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26
Q

Adjust Mortality Experience for a New Underwriting Technique

A 
Qnew = LaTeX needed
QNew = the mortality rate adjusted for the new underwriting guideline
Qold = the mortality rate based on past experience

A = Impairment frequency, the rate at which an underwriting technique will detect medical impairments

B = Sentinel frequency, the rate in which people with impairments will avoid the company due to the underwriting change

C = Additional mortality, the average amount that mortality is increased by a presence of the impairment

Expected Mortality: Fully Underwritten

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27
Q

Adjust Mortality Experience for a New Preferred Risk Class

A
  1. Qpref = Qstd * (1-B)
  2. QResidual = QStd * (1-A+B*A) / (1-A)
  3. A = The amount of applicants that will qualify for the preferred risk class
  4. B = The mortality differential for the preferred risk class

When adding multiple preferred risk classes start with the most restrictive risk class

Expected Mortality: Fully Underwritten

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28
Q

Considerations when determining selective lapse rate assumption

A
  1. Size of premium rate increase
  2. Period between premium increases
  3. Duration of policy
  4. Policy size
  5. Distribution system
  6. Heaped renewal commissions
  7. External market
  8. Proportion of healthy lives remaining
  9. Conversion activity

Expected Mortality: Fully Underwritten

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29
Q

Multiple Life Policies – Equivalent Single Age

A
  1. Mortality is approximated by using the mortality of a single age
  2. Rough approximation since joint life and single life mortality have different slopes
  3. Mortality rates for last survivor will be overstated in the initial durations
  4. Mortality rates for first to die will be understated in the initial durations

Expected Mortality: Fully Underwritten

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30
Q

Multiple Life Policies – Joint Equal Age

A
  1. Joint mortality is approximated by using the joint mortality of the same number of lives with the same age and underwriting class
  2. The JEA approach is superior to ESA

Expected Mortality: Fully Underwritten

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31
Q

Reasons why a flat percentage of an industry table may not be an accurate mortality assumption

A

MINimum mortality will be profitable

  1. Mortality improvement that varies by age
  2. Issue ages over 70
  3. New underwriting classes

Mortality Table Slope – The Discussion Goes On

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32
Q

Methods Used to End Mortality Tables

A
  1. Forced method
    a. Set ultimate age mortality rate to 1.00
    b. This creates a discontinuity
  2. Blended method
    a. Set ultimate age mortality rate to 1.00
    b. Select an age less than the ultimate age and blend mortality rates gradually to 1.00 at the ultimate age
  3. Pattern method
    a. Let the pattern of mortality continue until the rate hits 1.00
    b. The age at which the rate hits 1.00 is the ultimate age
  4. Less-than-one-method
    a. Select an ultimate age and DO NOT set the ultimate mortality rate to 1.00

Ending the Mortality Table

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33
Q

Challenges When Developing Term Mortality Assumptions

A

No Nobody LAPSE

  1. No ultimate experience past 10 years for new risk classes
  2. Nobody really knows how preferred/residual ratios change over time
  3. Lack of credible data
  4. Anti-selection after the level premium period
  5. Past mortality improvement may or may not continue
  6. Slope of mortality over the select period is unknown
  7. Each company has different underwriting criteria

Term Mortality and Lapses

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34
Q

Approached to Setting Mortality After the Level Premium Period

A
  1. Best Guess
  2. Becker-Kitsos (BK)
    LaTeX needed
  3. Dukes-Macdonald (DM) – n% is the amount of excess lapses that select against the insurance company

Term Mortality and Lapses

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35
Q

Lapse Experience Under Lapse Supported Products

A
  1. Ultimate lapse rates for lapse supported products are between 0.5% and 2%
  2. Term-to-100 products have very low ultimate lapse rates (<1%)
  3. Ultimate lapse rate for level COI UL policies is between 1-2%

Lapse Experience Under Lapse Supported Policies
Lapse Experience Under UL Level Cost

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36
Q

Changes in the Term Life Industry

A
  1. Prior to 1970 - term premiums varied by gender and attained age
  2. Current premium structure - level for X years followed by ART scale
  3. Rate competition - aggressive rates and online sales
  4. Regulation - XXX increased reserves and companies sought external financing
  5. 2008 credit crisis - premiums stabilized/increased

Level Term Lapse Rates - Lessons Learned
Term Mortality and Lapses

37
Q

Term Life Lapse Rates Lessons Learned

A
  1. During times of decreasing term premiums, lapse rates increased
  2. Pattern of lapse - starts out high in the first year, and then levels off to an ultimate rate
  3. Lapses on new business should be lower than recent historical experience
  4. T100 in Canada lost money due to aggressive lapse assumptions

Level Term Lapse Rates - Lessons Learned

38
Q

Canadian 10-Year Term Lapse Study

A
  1. Gender - males have higher lapse rates than females
  2. Smoking status - smokers have higher lapse rates than non-smokers
  3. Risk class - the best preferred risk class have the lowest lapse rates
  4. Payment frequency - annual pay had higher lapse rates
  5. Mode of payment - pre-authorized payments had the lowest lapse rates
  6. Standalone versus Riders - no significant differences
  7. Lapse rates for substandard are higher than standard issue
  8. Face amount - higher face amounts had lower lapse rates (but lapses did tick up for 2M+)

Lapse Experience Study for 10-Year Term Insurance

39
Q

Opportunities in the life settlement market

A
  1. Traditional sale of in-force policies
    a. Focuses on terminally ill and impaired lives
    b. Well established market
    c. High growth of investors, slower growth of policies
    d. Competitive bids
  2. Premium financing
    a. Done if the insured can’t pay premium
    b. A third party will pay the premium for two years
    c. The premium paid is considered a “loan”
    d. At the end of two years the policyholder can repay the loan or enter into a settlement
  3. Other opportunities
    a. Charity owned life insurance
    b. Stranger owned life insurance

The Response of Life Insurance Pricing to Life Settlements

40
Q

Life Settlements Advantages to Insured and Investor

A

Advantages to the insured

  1. Liquidity - opportunity to cash-out prior to death
  2. Customized value - if a policyholder is in poor health, the value of the policy is higher
  3. Insurance policy may have low/no cash value
  4. Don’t have to continue making premium payments

Advantages to the investor

  1. Deals are priced to earn a return on investment
  2. Risk profile is unique (uncorrelated with other financial markets)

Testing for Adverse Selection in Life Settlements (LP-133-16)

41
Q

Drivers of Life Settlements

A
  1. Intrinsic value of policy is greater than the CSV
  2. Legacy, gift endowment
  3. Change in policyholder need
  4. Income shock (insured can’t pay premium or needs cash now)
  5. Change in health
  6. Other investment objectives

Testing for Adverse Selection in Life Settlements (LP-133-16)
The Response…to Life Settlements

42
Q

Risk and Profitability Drivers for Settlements

A
  1. Adverse selection - policyholders may know more about their health than the life settlement company
  2. Retained death benefit - policyholders seeking partial settlements may be looking for the best deal
  3. Convexity of premiums - settlement company would pay lower premiums upfront
  4. Diversification - life settlement company will aggregate experience
  5. Fixed costs for smaller policies
  6. Number of life expectancy estimates obtained

Testing for Adverse Selection in Life Settlements (LP-133-16)

43
Q

Types of Life Settlements

A

LS - Standard Life Settlement which comprises most of the market. Medical records are obtained.

SLS - Simplified life settlement. Face amount is less than 1M. Usually no medical records are obtained, just a medical questionnaire.

LS-RBD - Original policyholder retains a portion of the death benefit. Life settlement company still pays the full premium.

SLS-RBD - Simplified life settlement where original policyholder retains a portion of the death benefit.

Testing for Adverse Selection in Life Settlements (LP-133-16)

44
Q

Current Trends in Life Settlements

A
  1. Life expectancy of policyholders is increasing
  2. 88% are universal life policies
  3. 91% are LS type settlements
  4. Average age is 75
  5. Settlements with retained death benefit have an average retained death benefit of 25.3%

Testing for Adverse Selection in Life Settlements (LP-133-16)

45
Q

Valuation Formula for Life Settlements and Life Expectancy Formula

A

Need LaTeX

Testing for Adverse Selection in Life Settlements (LP-133-16)

46
Q

Regression model to test for adverse selection

A

Need LaTeX

Testing for Adverse Selection in Life Settlements (LP-133-16)

47
Q

Post Level Premium Term Plans

A

See card

Report on the Lapse and Mort Exp of Post-Level Premium

48
Q

Post-Level Premium Term Plans

A

See card

Report on the Lapse and Mort Exp of Post-Level Premium

49
Q

Premium Persistency Assumptions

A

See card

Report on Premium Persistency of Flexible Premium UL

50
Q

Factors that have led to increased attention on policyholder behavior

A

See card

Modeling of Policyholder Behavior for Life and Annuity

51
Q

Challenges of understanding policyholder behavior

A

See card

Modeling of Policyholder Behavior for Life and Annuity

52
Q

Policyholder Behavior Assumptions

A

See card

Modeling of Policyholder Behavior for Life and Annuity

53
Q

Challenges of Modeling Policyholder Behavior

A

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Modeling of Policyholder Behavior for Life and Annuity

54
Q

Ways to Model Policyholder Behavior

A

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Modeling of Policyholder Behavior for Life and Annuity

55
Q

Policyholder Behavior Assumptions

A

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Modeling of Policyholder Behavior for Life and Annuity

56
Q

Behavioral Economics Principals

A

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Modeling of Policyholder Behavior for Life and Annuity

57
Q

Behavioral Economics - Decisions Shortcuts

A

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Modeling of Policyholder Behavior for Life and Annuity

58
Q

Behavioral Economics - Value Assessments

A

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Modeling of Policyholder Behavior for Life and Annuity

59
Q

Behavioral Economics - Emotional Impacts

A

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Modeling of Policyholder Behavior for Life and Annuity

60
Q

Behavioral Economics - Social Impacts

A

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Modeling of Policyholder Behavior for Life and Annuity

61
Q

Behavioral Economics and Lapses

A

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Modeling of Policyholder Behavior for Life and Annuity

62
Q

Behavioral Economics and Premium Funding

A

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Modeling of Policyholder Behavior for Life and Annuity

63
Q

Behavioral Economics and Withdrawals

A

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Modeling of Policyholder Behavior for Life and Annuity

64
Q

Behavioral Economics and Investments

A

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Modeling of Policyholder Behavior for Life and Annuity

65
Q

Behavioral Economics and Annuitization

A

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Modeling of Policyholder Behavior for Life and Annuity

66
Q

Poor Data Quality Can Lead To:

A

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Experience Data Quality - How to Clean and Validate

67
Q

Common Causes of Data Errors

A

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Experience Data Quality - How to Clean and Validate

68
Q

Data Validity and Data Accuracy Errors

A

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Experience Data Quality - How to Clean and Validate

69
Q

Data Error Detection Techniques

A

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Experience Data Quality - How to Clean and Validate

70
Q

Solutions for Bad Data

A

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Experience Data Quality - How to Clean and Validate

71
Q

Data Validation

A

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Experience Data Quality - How to Clean and Validate

72
Q

ASOP 23: Data Quality Recommended Practices

A

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ASOP 23

73
Q

ASOP 23: Data Quality Considerations When Selecting Data

A

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ASOP 23

74
Q

ASOP 23: Data Quality Communication and Disclosure

A

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ASOP 23

75
Q

Impacts of Low Interest Rates on Insurers

A

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Is this Correction Good for Life Insurance?
Transition to High Interest Rate Env

76
Q

Factors Which Influence Economic Cycles

A

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Transition to a High Interest Rate Environment

77
Q

Potential Drawbacks of Stochastic Interest Rate Models

A

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Transition to a High Interest Rate Environment

78
Q

Impacts of a Spike in Interest Rates on Insurers

A

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Transition to a High Interest Rate Environment

79
Q

Interest Rate Testing and Impact on Products

A

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Transition to a High Interest Rate Environment

80
Q

Factors Which Could Lead to Rising Interest Rates

A

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Transition to a High Interest Rate Environment

81
Q

Steps for an Expense Study

A

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Best Estimate Assumptions for Expenses

82
Q

Sources of Expense Data

A

See card

Best Estimate Assumptions for Expenses

83
Q

Expenses and Common Units

A

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Best Estimate Assumptions for Expenses

84
Q

Expenses to Include in an Expense Study

A

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Best Estimate Assumptions for Expenses

85
Q

Expense Allocation Methods

A

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Best Estimate Assumptions for Expenses

86
Q

Assumptions ASOP General Considerations

A

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Draft ASOP: Assumption Setting

87
Q

Assumptions ASOP Reasonableness of Assumptions

A

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Draft ASOP: Assumption Setting

88
Q

Assumptions ASOP Guidance when actuarial report is not required

A

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Draft ASOP: Assumption Setting

Life Pricing Exam (6 decks)

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