# Reinsurance of health insurance for the informal sector David M. Dror 1

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3 It seems self-evident that high probability of risk exposes insurers to a high expected claims cost; what is less self-evident is that when the probability drops, small groups benefit less from the drop than large groups, because the statistical possibility of a higher than average claim load occurring is sensitive to group size. Fig. 2 illustrates this phenomenon, juxtaposing a group of 100 and one of 1000 members, and employing the normal distribution approximation to the binomial law. As can be seen, when the probability is 2%, both groups are exposed to the chance that the claim load will be above the expected mean; but whereas this risk (for claims to be 60% or higher than the mean) is in the order of 1% for the large group, it is a significant 16% for the small group. Underestimated probability of risk. Fig. 1 and Fig. 2 have shown that the level of fluctuations depends on the probability of risk. Thus, an erroneous estimate of P will unavoidably lead to an erroneous estimate of the expected statistical fluctuations. The financial corollary of this error is higher likelihood of insolvency. This relation is more significant for small groups, as Fig. 3 shows. The graph (calculated with the same assumptions as Fig. 2) demonstrates that when the required income is fixed on an assumed P = 10% and allowing a level of insolvency of 5%, an observed value of P of 15% causes the risk of insolvency to jump from 5% to 50%; and an observed P-value of 20% instead of the estimated 10%, will escalate the risk of insolvency to 90% instead of 5%. Fluctuations in unit cost of benefits. Variance in the unit cost of benefits is an additional potential source of financial instability. Provider payment systems such as capitation or flat rates have become common remedies for unit-cost fluctuations. Reaching such a favourable negotiated deal requires a strong bargaining position, which single MIUs may not always have. When unit-cost variation cannot be averaged out or transferred to the provider, the cost of single episodes of care is likely to vary significantly (for instance, a prescription for a simple pain killer will be cheaper than an antibiotic; or the costs of one incident involving hospitalization can vary depending on the length of stay). Fig. 4 provides an example from ORT Health Plus Scheme (La Union, Philippines): 80% of all medico-technical procedures cost up to 200 Phippine pesos, but the remaining 20% cost up to 6timesmore. Catastrophes. A catastrophic event is random, of low probability, and too costly for most individuals to absorb even for a single occurrence. MIUs might be exposed to two categories of health catastrophes: predictable catastrophes, which include idiosyncratic events with low probability and high cost. Data from Kisiizi, Uganda, showed that a single case of surgery could bankrupt an entire MIU for a full financial exercise. This example would suggest that the smaller the MIU, and the smaller the financial volume, the more such events resemble catastrophic situations. Insuring this risk could be one of the attraction-poles of MIUs. The second type, unpredictable catastrophes, involves covariant events that result from natural disasters such as flooding, contamination of water sources, epidemics and the like. These can cause an unpredicted large increase in the number of claims. Clearly, a risk that affects an entire village cannot be insured solely within the village; it requires pooling with areas not exposed to that risk (9, p.136). 674 Bulletin of the World Health Organization, 2001, 79 (7)

4 Reinsurance of health insurance How can the financing of MIUs be stabilized? Experience with single MIUs, and lessons from micro-finance schemes would suggest that riskpooling mechanisms launched by CBOs are quite rudimentary, while complex arrangements often enjoy outside technical and financial assistance. Furthermore, there is evidence that MIUs seeking and relying on outside resources (13) tend to operate in isolation from other MIUs in order to improve their competitive edge for external funding. Those who fail to secure external subsidies risk folding. The approach espoused here, to guarantee financial viability of MIUs from inception through risk management tools, represents a paradigm shift compared to the school of thought that views the creation of subsidy-based MIUs as the main challenge. The fundamental concept advanced here is that just as MIUs pool risks that are too large for individual exposure, reinsurance can pool risks that a single MIU may find difficult to bear. Simply defined, reinsurance is the transfer of liability from a primary insurer (the MIU) to another insurance company (the reinsurer). The transfer of risks to a reinsurer is called cession. Reinsurance activity covers four domains, which are financing, capacity, stabilization, and catastrophe protection; sometimes a fifth domain is added, which would certainly be necessary for MIUs: underwriting and managerial assistance (14). Financing relates to calculating and accumulating the reserves (surplus) that an insurer must retain to guarantee its insurance risk. The traditional view is that substantial own funds are the mark of a healthy financial position. For newly established MIUs in particular, contingency reserves are unavailable, and it is even doubtful if the use of own funds to cover peaks in risk is more effective than financial reinsurance that can be designed to cover both costs and the formation of actuarial provisions. Maintaining reserves also raises the possibility that MIUs could be exposed to members pressure to spend accumulated sums on benefit enhancements, whereas reinsurance avoids such demands. Capacity refers to the size of a single type of risk the MIU can accumulate. Stabilizing describes the ability to reduce the year-to-year fluctuations in risk (or loss) exposure. Catastrophe protection simply means insuring the MIU against a loss that may endanger its very existence. Lastly, underwriting and managerial assistance offered by the reinsurance allows for sharing information, statistical expertise, and managerial experience that would normally be unaffordable by MIUs, and which can improve performance. Sharing risks between insurance carriers is common practice in the insurance industry, regardless of the size of insurers. True, where social health insurance can operate within pay-as-you-go financing (as in most OECD countries), reinsurance is rare. However, MIUs cannot operate on a pay-asyou-go basis; nor do they enjoy unlimited deficit financing from external sources. Hence, MIUs need to be assisted to provide insurance. The political imperative for this is that MIUs provide insurance to low income and low health status populations in the informal sector, and thus meet a need that otherwise goes unmet. A concern is sometimes raised that reinsurance is operated only by the private (for profit) sector, and thus MIUs may be exposed to excessive costs for reinsurance protection. In fact, MIUs cannot at present attract profit-oriented reinsurers. This valid concern has motivated a search for a structure that would operate reinsurance tools in support of MIUs, in affordable conditions. The project to conceptualize, model, and pilot this kind of reinsurance has been launched by a team composed of experts from International Labour Organization (ILO), the World Bank, and the University of Lyon (Claude Bernard), led by the author, financed by an award from the World Bank s Development Marketplace and the ILO, and called Social Re (15). What can be reinsured? In the previous section, several causes of instability were described. In this section it will be shown that most of these can be reinsured. Data from Kisiizi, Uganda, on the incidence of hospitalization (during a period of about one year, among 30 MIUs, covering between 15 and 57 households) was analysed to show the severity of random statistical fluctuations in claims numbers. The field data were compared to simulated data, obtained by using a random-number generator and assuming the binomial distribution of claims, to predict the number of incidents. The two data sets are shown in Fig. 5. With an average of 0.4 incidents per insured household for the period, the actual incidence shows a threefold to fourfold difference between MIUs. Seeing that the insured medical care costs (that are borne by the MIU) do not cover ancillary costs such Bulletin of the World Health Organization, 2001, 79 (7) 675

5 as food, which the families bring to hospital, one can reasonably assume no moral hazard and low demand elasticity. The simulated data were produced to verify that such extreme fluctuations were not a distortion of inadequate field observations. The similarity between the two series is striking, and allows the impact of reinsuring this risk (for which no field data are of course available) to be explored through more simulations. The question explored was how long MIUs with a uniform size (100 members) and the same risk profile (P = 10%) could remain solvent without reinsurance, when contribution rates were calculated to cover the expected average cost of the package ( original rate ). For the purpose of this simulation, the number of MIUs was increased to 90. The results are shown in Fig. 6. Most MIUs ran aground, even though surpluses were carried forward across years. The original contribution rate was thus increased at intervals of 10% (from 110% to 150%). With contributions at 110%, only 50% of the MIUs survived a 10-year period. As expected, survival rates increased with increasing contribution rates, but only those MIUs that could secure an income of 150% of the original rate for the entire 10-year period were almost safe from insolvency. This cost was compared to reinsurance. With a premium assumed to be 15% of the original rate, reinsurance secured a higher survival rate than all alternatives, and cheaper than all but the 110% alternative. It should be noted that this calculation of reinsurance assumed that the reinsurer paid all costs above the average. The conclusion seems to be compelling: from the point of view of the MIUs, reinsurance was preferable to financing of deficits from contingency reserves, and its cost was more affordable at inception than the alternative option of factoring a reserve into the contribution rates. The same data were also used to explore how long the reinsurer could survive with this business profile, with a reduction of the number of MIUs to 10, to accommodate a small test population. This is shown in Fig. 7. As can be seen, during the first five years, the reinsurer can encounter episodes of deficit, although these are not very likely. After five years, all nine runs of the simulation showed positive results for the reinsurer. This simulation strongly suggests that reinsurance can operate on a cost-neutral basis in the long term, but that it needs the financial resources to cover possible deficits during the first few years of operations. A second simulation (not shown here), with fewer MIUs, produced less favourable results. This would suggest that, as can be expected, a larger pool of MIUs improves the results of the reinsurer and reduces the period needed for cost neutrality. Fluctuations in income could also be reinsured under finite risk reinsurance, which is a form of coverage that combines the transfer of a risk with a profit-sharing relationship between the reinsurer and the ceding MIU. This multi-year contract allows the reinsurer to compensate limited amounts of losses in one year, against payment by the MIU through premiums and investment income in other years when surpluses are generated. This form of financial reinsurance operates a trade-off between the underwriting income of today and investment income of 676 Bulletin of the World Health Organization, 2001, 79 (7)

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