Assumptions and Monitoring Flashcards

1
Q

Mortality assumption

A

Final Mortality Rate (% of base table) = Base Table Rate × Selection Factor × Underwriting Class Factor × Size Factor × Socioeconomic Factor × Trend Factor × (1 + Prudential Margin)

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2
Q

Claim incidence rates

A

State transition monitoring uses internal transition experience supplemented by industry studies.
The process analyses movements between different health states, considering duration in each state, age effects, and recovery patterns.
Base rates are adjusted for medical advances and treatment effectiveness.
Key trends include improvements in medical care and changes in care protocols.
The final rates incorporate duration effects, age factors, treatment impacts, and recovery patterns, plus prudential margins.

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3
Q

Claims investigations

A

Claims investigations could refer to death benefits, or disabiltiy benefits.

The mortality assumption is important in these instances:
- early death in term assurance benefit (not enough premium collected yet0
- in claim state (for LTC and pensions)
- during survival period of CI as determines how many people survive to claim

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4
Q

Morbidity monitoring

A

The monitoring process focuses on calculating both crude inception rates (becoming disabled) and recovery rates (ceasing to be disabled). These are compared against expected rates for each risk category. Analysis is performed by cause of disability to identify any changing patterns. The average claim duration is tracked, and trends in medical treatments that might affect recovery rates are monitored. Special attention is paid to changes in workplace conditions or disability definitions that might impact experience.

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5
Q

Persistency assumption

A

Persistency assumptions typically start with the company’s target lapse rates based on pricing. These are adjusted for expected market competition effects and economic factors. Duration-based adjustments are crucial as lapse rates often vary significantly by policy duration. The rates might also vary by distribution channel and premium payment method, requiring specific factors for each combination

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6
Q

Persistency monitoring

A

Persistency monitoring calculates actual lapse rates by policy duration and analyzes them against expected rates. The analysis considers premium size and type, with particular attention to any selective lapse patterns. Market condition impacts are closely monitored, especially competitor actions and economic changes. Premium increase impacts are tracked carefully, and any signs of anti-selection in lapses are investigated.

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7
Q

State transition rates monitoring

A

State transition monitoring calculates actual transition rates between different health states and compares these to expected rates. The average time spent in each state is tracked, and recovery rates are monitored by cause of claim. Entry age patterns are analyzed, and claim termination rates are reviewed regularly. Changes in care practices or medical treatments that might affect transition rates are closely monitored.

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8
Q

Claim amount assumption

A

Claim amount monitoring focuses on actual claims history and provider fee schedules. The process analyzes trends in treatment costs, provider contracts, and medical inflation. Base amounts are determined from recent experience, then adjusted for changes in treatment protocols and provider arrangements. The analysis must consider both frequency and severity trends separately. Final claim amounts include severity factors, treatment effects, provider impacts, and inflation adjustments.

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9
Q

Expenses assumption

A

Expense assumptions begin with analyzing recent company cost data, carefully separating fixed and variable components. The process involves determining an appropriate basis for spreading fixed costs across policies and calculating percentage-based loadings for variable costs. Expected inflation is incorporated, and volume assumptions are crucial for unit cost projections. Different expense types (acquisition, maintenance, investment, claims) each need their own assumption basis and allocation method.

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10
Q

Expenses monitoring

A

Expense monitoring involves tracking actual versus budgeted expenses across all categories. Unit costs per policy are calculated and compared to assumptions, with separate analysis for acquisition and maintenance costs. Expense ratios are regularly reviewed, and allocation bases are validated to ensure they remain appropriate. Any significant deviations are investigated to understand whether they represent temporary fluctuations or permanent changes requiring assumption updates.

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11
Q

Inflation assumption

A

Inflation assumptions begin with general economic forecasts for consumer price inflation. A medical inflation premium is added based on historical patterns and expected healthcare cost trends. Wage inflation effects are incorporated where relevant, particularly for income protection products. Regional factors are applied where significant geographic variations exist in inflation patterns.

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12
Q

Inflation monitoring

A

Inflation monitoring tracks actual versus expected inflation rates across different categories. Medical cost trends are analyzed separately from general inflation. Wage increase patterns are monitored, particularly in key occupation groups. Treatment cost changes are tracked by type of treatment. Regional variations are analyzed, and provider fee changes are monitored. Any structural changes in healthcare delivery that might affect future inflation patterns are identified and assessed.

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13
Q

Investment return assumption

A

Investment return assumptions start with risk-free rates derived from government securities. Risk premiums are added based on the intended asset mix, with different premiums for each asset class. The assumption incorporates expected investment expenses and makes allowance for default risk. The final rate reflects the company’s investment strategy and any asset-liability matching requirements.The overall estimate investment assumption will reflect the balance between the expected return from assets currently held and expected return from assets that we intend to buy in the future.

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14
Q

Investment performance monitoring

A

Investment monitoring tracks actual versus expected returns across all asset classes. Reinvestment rates for new money are closely watched, particularly in comparison to assumptions. Asset-liability matching effectiveness is reviewed regularly. Investment expenses are tracked against assumptions, and credit experience is monitored. Market changes that might affect future return expectations are analyzed and fed back into assumption setting.

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15
Q

Profit requirements assumption

A
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16
Q

When is the mortality assumption significant?

A
  • When LTC claims are in payment, as the later the PH dies, the longer claims are paid for
  • In DB funds, the longer a pensioner lives, the longer the pension fund is required to make payments.
  • During the survival period of a CI policy, if PH dies in survival period the CI will not be paid.
  • When there is a death benefit payable
17
Q

When is the lapse assumption significant?

A
  • Early on in the policy as it may cause financial loss, where insufficient premiums have been received to recover the initial strain (commission and initial expenses) i.e. asset share is negative.
  • Insurer makes profit if asset share is positive and no surrender value offered
  • Selective lapses - healthier low claiming PMI holders are more likely to lapse, leaving worsening book
18
Q

Reason for monitoring

A
  • Monitor actual vs expected experience
    > to take corrective action
    > to update assumptions to be more accurate
    > make more informed decisions about pricing and reserves adequacy
  • Develop earned asset shares
  • Monitor any trends in experience
  • Provide management information
19
Q

Commission

A

Commission assumptions start with regulatory maximums and market practice as a base. Initial commission rates are set higher than renewal rates, typically differentiated by distribution channel. Clawback assumptions incorporate expected lapse rates and historical recovery experience. The final assumption includes an element of prudence for non-recovery of clawback amounts and considers any special distribution arrangements. Channel mix assumptions are crucial as different channels may have varying commission structures and clawback patterns.

20
Q

Tax

A

Tax assumptions begin with current tax rates and incorporate any known future changes. Different types of tax (profit tax, investment income tax, premium tax) are considered separately. For profit tax, assumptions consider the timing of taxable profits and available deductions. Premium tax assumptions are typically straightforward additions to the premium. Investment income tax assumptions need to consider the mix of taxable and tax-exempt investment income.

21
Q

New business volume assumption

A

New business volume assumptions start with recent company experience and incorporate market growth expectations. These are broken down by product type, distribution channel, and policyholder characteristics. Average policy size assumptions consider recent trends and economic factors. Mix assumptions include product type, distribution channel, territory, gender, occupation, and health status variations. Renewal assumptions typically project lower volumes than new business.

22
Q

Discount rate

A

Discount rate assumptions start with the risk-free rate as a base. Risk premiums are added using CAPM or statistical approaches depending on the application. Product-specific adjustments are made based on guarantee levels, option complexity, and risk profile. Market consistency approaches use term-dependent risk-free rates, typically based on swap rates or government bond yields. Additional margins reflect parameter uncertainty and market risk compensation.

23
Q

Benefit amount

A

For long-term contracts, benefit amounts are typically fixed at outset with simple rate-based calculations (e.g., R30 per R1000 benefit). Larger policies might have different assumptions due to higher underwriting expenses, though they often show better experience due to socioeconomic factors and stricter underwriting. For short-term contracts (PMI), assumptions are more complex, requiring both claim frequency and size predictions. These are based on provider contracts which might include industry-fee-for-service, modified fee-for-service, per-diem, per-case, capitation, or salary arrangements. Each arrangement transfers different levels of risk to providers.

24
Q

Benefit amount monitoring

A

Benefit amount monitoring varies by contract type. For long-term contracts, monitoring focuses on whether the fixed rates remain appropriate for different policy sizes and whether the expected better experience for larger policies is materialising. For short-term contracts, monitoring is more intensive, tracking actual versus expected costs under different provider arrangements. This includes analyzing hospital stay lengths, treatment intensities, readmission rates, and the effectiveness of preferred provider networks.

25
Q

Benefit inflation assumption

A

Inflation assumptions vary by product purpose. For long-term contracts (CI/LTCI), different inflation rates apply based on benefit purpose: medical treatment costs for care benefits, no inflation for fixed debts, earnings inflation for income replacement, and price inflation for ongoing costs. For short-term contracts (PMI), the assumption incorporates medical inflation plus adjustments for changing treatment protocols, technological innovation, and shifting demographics. LTCI typically uses specific indices linked to nursing and residential home costs.

26
Q

Monitoring benefit inflation

A

Inflation monitoring tracks actual versus expected increases across different cost categories. For medical costs, this includes tracking treatment protocol changes, technology impacts, and provider fee increases. For LTCI, nursing and residential home cost indices are monitored. Marketing risks are assessed - too low inflation might leave policyholders underinsured, while too high inflation might drive lapses through excessive premiums. Different inflation components (medical costs, wages, general prices) are monitored separately to ensure assumptions remain appropriate for each benefit type.

27
Q

Reason for EV monitoring

A

Validate calculations, data, and assumptions.
Reconcile values for successive years.
Provide management information and data for executive remuneration.
Provide information to be included in the company’s accounts.

28
Q

Aims of AOS

A
  1. Assess actual versus expected experience (and financial impact)
  2. Assess the financial effect of writing new business for health and care providers.
  3. Provide a check on the valuation.
  4. Provide information on trends in experience.
  5. Analysis of embedded value (EV) for long-term insurers.
  6. Identify non-recurring elements of surplus
  7. Comply with regulations
29
Q

What might cause surplus for ST product (PMI) vs. pension?

A

Medical
Claims experience deviations
Morbidity/inception rate variations
Recovery rate differences
Premium adequacy
Expense overruns/savings
Short-term investment returns

DB fund
Pension increases (equivalent to a claim)
Mortality experience
Salary increases
Long-term inflation
Investment returns

DC fund
Expense overruns/savings
Investment portfolio mismatching
Data processing variations
Member choice impacts

30
Q

AOS differences health vs. pension

A
  1. Frequency of calculation
  2. Time horizon: 1-2 years vs. decades
  3. Main risk sources: monthly vs. annual
    Health/Care: Claims, morbidity, medical inflation
    Pensions: Investment returns, longevity, inflation
  4. Management Actions
    Health/Care: Premium adjustments, provider contract changes (change expenses), benefit design modifications, short-term investment strategy
    Pensions: Contribution rate changes, investment strategy shifts, benefit restructuring, long-term funding plans
31
Q

Data criteria

A

There should be sufficient data to reduce sampling error
There should be recent enough data to ensure relevance
The data should be accurate and reliable.
Data should be available in the first place in the right format and at the right price.

32
Q

Why is it so important to use dependent decrements in investigations?

A

Dependent decrements is when the relationship between the decrements is acknowledged. For example, if someone dies they are unable to withdraw or retire. It is important to use dependent decrements in crude calculations to get more accurate actual vs. expected values.

33
Q

What are the reasons for monitoring experience?

A

Reasons for monitoring experience:
* Update assumptions as future experience emerges
* Monitor any trends in experience
* Monitor actual vs expected in experience as to take corrective action
* Provide management information and make more informed decisions

In context of underwriting and reinsurance, monitoring helps
* Check underwriting procedures are effective.
* Identify anti-selection.
* Assess need for reinsurance.
Calculate profit share values under existing treaties.

34
Q

How do different basis affect the analysis of surplus?

A

Prudent basis:
- surpluses can be expected (big deviation between actual and expected)
- deficit here is a huge red flag
- focus on the size of the margins

Realistic basis:
- both gains and losses should be investigated
- actions should be based on size and pattern of deviations
- focus on accuracy of the assumptions

35
Q

When is renewal rate investigation important?

A
  • important to to amortise the initial expense costs when pricing the product. can take up to 2/3 years to recover these initial claim costs. if insufficient renewal, cannot recover expenses which lowers profit levels.
  • essential assumption for the financial planning of the business, e.g. for the forecasting of future profitability.
  • analysis will also enable the company to identify groups, e.g. particular agents, channels, or regions, that may have very different renewal experience. company can then take appropriate remedial action, e.g. change its sales distribution and/or marketing strategies.
  • renewal rates, split according to previous claims history, will be essential in modelling future experience for the purposes of deriving appropriate NCD scales, where applicable.