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«Protecting the poor A microinsurance compendium Edited by Craig Churchill Protecting the poor A microinsurance compendium Protecting the poor A ...»

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Each component must be carefully calculated from the experience data and/or from other available information. As mentioned above, to the extent that specific data is unavailable, the actuary must make reasonable assumptions based on experience, industry studies and observations from similar programmes.

It is very important to note that in microinsurance product design, communication methods, management practices, and many other factors will impact the observed experience. In populations where insurance awareness is low, it may take much more time for claims rates to stabilize and to reach 246 Microinsurance operations predictable levels. For example, even though it was serving a similar insured population, Yeshasvini’s claims experience increased from Rs. 65 (US$1.43) per insured in Year 1 to Rs. 86 (US$1.89) in its second year of operation. The most likely reason for the higher claims cost in Year 2 is that there was a greater awareness of the insured benefits and claims procedures.

2.1 Life and savings products

The main components for pricing life and savings products are the following:

a) Rate of mortality Typically the actuary chooses an appropriate mortality table prepared by collaborating companies within the insurance industry and adapts this to the microinsurance group. In the absence of industry tables, population tables prepared by World Health Organization (WHO) or others may also be used and adapted to the particular group of microinsurance participants, although this is not the optimum approach.

The selection and adaptation of the mortality table is a critical step in the pricing process for life insurance. Ideally, the final table should be tested against the database of participants by calculating the expected claims and the number of deaths over a selected retrospective study period, and then comparing these results with actual experience in the same period. This comparison should be conducted over each risk subgroup if possible, such as those defined by a combination of age, gender and geographic location. This test will determine the appropriateness of the mortality model and is only possible if the scheme has accumulated reliable data, as described in the previous section. The actual-to-expected claims test can be performed iteratively until the selection of mortality table and required adjustments are completed. The final result is the mortality pricing model for the group.

Whenever possible, the actuary should use a demographic profile of the prospective insured group when calculating the expected aggregate mortality rate instead of simplifying the calculation by using an expected average age.

The latter approach is not very reliable (see Chapter 3.6).

The participation level is a very important consideration in preparing the mortality model. Mandatory participation of all eligible members of the target group is recommended. If participation is optional, then adverse selection will significantly increase the expected mortality rate.

Another important factor is the expected trend in mortality. In that regard, the actuary must take into account the influx of new participants in the next few months or years. For example, if the projected growth rate of the scheme is “high” and if new participants are a targeted segment of the Pricing microinsurance products 247 population such as younger women entrepreneurs, then the aggregate mortality rate will probably decrease or remain stable over time. Conversely, low growth rates are likely to result in an increased aggregate mortality rate as the group ages. For age-structured rates, this is less of a concern. However, for level premium rates, the future trends in expected mortality must be incorporated carefully.

For example, with VimoSEWA’s voluntary scheme, the rate of mortality changed dramatically in a few short years as a much larger proportion of younger women entered the programme, and due to wider participation compared to the earlier years (see Table 26).

Evolution of life mortality rate at VimoSEWA Table 26

–  –  –

HIV/AIDS is a major factor introducing long-term changes and trends into mortality rates. In regions with significant epidemics, the mortality rates can double or even triple, particularly in the income and age bands typically served by microfinance institutions and community-development NGOs.

Upon completion of the mortality model, the actuary will calculate the expected claims component of the premium rate, taking into account the product features and benefits payable contingent on death.

Other products like disability or health insurance will also require pricing tables, though based on contingency rather than mortality rates. Most of the above considerations will still apply.

–  –  –

It is important for the actuary to be able to prepare a schedule of dropout rates by age, gender and time since enrolment, and correspondingly, to understand what proportion of the lapses will reinstate their coverage within the allowable reinstatement period. This information can be derived from the premium history database described above.

Depending on the product, the drop-out rates and the pattern can either improve or decrease the profitability of the microinsurance programme. For all products, a high rate of drop-out will increase expenses. However, if the product has an equity or savings component of which a portion is forfeited through early surrender, then a high surrender rate can actually improve profitability. The actuary may choose to use some of the projected forfeited equity to fund other benefits and thus reduce the overall premium rates.





c) Risk loading Actuaries use risk mathematics to compute an appropriate risk premium, which is meant as a provision for adverse deviations (PAD) from expected claims over the short to medium term. Expected claims computed from experience and mortality tables will probably never be realized exactly4 and the risk loading is a provision to increase the probability that the actual claims will not exceed net premiums over a predefined time period.5 In general, experience with larger groups of homogeneous participants (in terms of age, gender, health, occupation, etc.) and with identical coverage is less likely to deviate significantly from the expected claims (i.e. smaller variance) than that of smaller groups, groups with diverse participants, or groups with several coverage options.

d) Uncertainty loading The actuary may include an amount to compensate for uncertainty. In general, the more assumptions that have to be made, and the less reliable and sparser the data, the greater is the uncertainty.

e) Profit or contribution to microinsurance surplus and equity To expand the scheme, some profits are needed. The desired profit may be expressed either as a loading or as a separate component of the net rate.

4 Technically, the expected claims computed from the data can be regarded as an estimate of the mean of the true underlying aggregate claims distribution.

5 The risk loading is computed based on a desired probability of having sufficient net premium to cover all claims over a defined period, typically 1 to 5 years. A loading that ensures adequate net premium with a probability of 95 per cent is higher than a loading that ensures same with probability of just 90 per cent, for example.

Pricing microinsurance products 249

f) Expenses The expected expenses incurred for marketing, underwriting, claims payment, premium collection and administration must be loaded into the final net rate. To do this correctly, a thorough analysis should be made to determine how the expenses of the entire scheme are incurred, and then the expenses should be projected and allocated to the various products on an incurred basis. Arbitrary expense allocation will result in cross-subsidization of products (although this may be desired in some cases).

Recently Grameen Kalyan’s health insurance programme was analysed to compare premium by health centre to the cost of operating the centre. The analysis showed that some centres were producing a surplus after taking account of only their local costs, but before factoring in the head office cost allocation and the depreciation of their equipment. Future pricing reviews of its products must include the costs of running the entire programme.

g) Expected investment earnings Expected investment earnings are used in combination with expected mortality rates to prepare the net rates for life insurance before expense loading.6 For example, Yeshasvini invested the initial annual premium and earned interest of Rs. 2 (US$0.04) per insured person, which helped cover some of the administrative expenses. The actuary, therefore, needs to consider how excess premiums will be invested before they are used to fund the scheme’s expenses and incurred claims. Moreover, the timing and frequency of the premium payments (see below) affect the investment earnings as do the quality, liquidity and rates of return of the selected investments.

As discussed in Chapter 3.6, the main risk in pricing long-term insurance products is the accuracy of assumed investment earnings. Long-term fixed rate guarantees are especially dangerous if the asset used to invest premiums (such as 20 to 30-year bonds) is not identified and purchased at the time the guarantee is given. Interest rates can drop relatively quickly, so it may be impossible to invest in assets that provide the returns needed to fund the rate guarantees. A shortfall of just a few basis points may well lead to eventual bankruptcy due to the effect of compound interest. One solution is to link rate guarantees to investment instruments such as government-issued bonds or five-year average term deposits in commercial banks.

–  –  –

h) Product design Product design features affect all the pricing components. For example, one common product is level-term life insurance. If the coverage is linked to loans from an MFI, the risks covered are predominantly women’s lives (where women are the target clientele of the MFI). By also providing coverage for the clients’ spouses and children, the risk pool is significantly altered, especially since most male spouses are often older than their wives and because males usually have higher mortality rates. Product features such as waiting periods and pre-existing illness exclusions are also important pricing considerations (see Chapter 3.1).

i) Timing and frequency of premium payments These have to be factored into the premium rates. For example, if the annual premium payable at the beginning of the coverage year is P, the equivalent monthly premium is higher than P/12 for three reasons: 1) the additional collection expenses (twelve transactions rather than just one), 2) lost interest earnings and 3) the fact that those dying will not complete the monthly premium payments.

j) The size of the microinsurance group This affects the expense levels due to economies of scale, and it will greatly influence the required risk loading discussed above.

k) Participation rates These affect the mortality rates, morbidity rates and the expenses. A community with 100 per cent participation will have lower per-capita claims expenses than a community with only 10 per cent participation. In the latter case, adverse selection comes into play because the families who believe that they will receive a benefit are more likely to enrol in the insurance programme.

l) Growth of the microinsurance scheme This, together with inflow of new participants, is a critical factor in mortality trends. The addition of older or younger insured populations can dramatically change the expected aggregate mortality of the group.

–  –  –

n) The livelihoods, occupations and activities of the participants These greatly affect the health, mortality and morbidity rates and thus the expected claims.

o) Inflation rates These will affect expenses and perhaps benefits depending on the product design. Inflation rates will usually have an effect on investment earnings as well.

p) Reinsurance This can be used to manage some pricing risks. Theoretically, and all things being equal, reinsurance can result in lower net rates due to the reduced riskloading requirements, but this depends on the design of the reinsurance programme and on the reinsurer. However, in many cases the reinsurance programme adds an additional cost.



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