Insurance loss coverage and social welfare

Restrictions on insurance risk classification may induce adverse selection, which is usually perceived as a bad outcome, both for insurers and for society. However, a social benefit of modest adverse selection is that it can lead to an increase in `loss coverage', defined as expected losses compensated by insurance for the whole population. We reconcile the concept of loss coverage to a utilitarian concept of social welfare commonly found in economic literature on risk classification. For iso-elastic insurance demand, ranking risk classification schemes by (observable) loss coverage always gives the same ordering as ranking by (unobservable) social welfare

Insurance loss coverage under restricted risk classification: The case of iso-elastic demand

This paper investigates equilibrium in an insurance market where risk classification is restricted. Insurance demand is characterised by an iso-elastic function with a single elasticity parameter. We characterise the equilibrium by three quantities: equilibrium premium; level of adverse selection (in the economist’s sense); and “loss coverage”, defined as the expected population losses compensated by insurance. We consider both equal elasticities for high and low risk-groups, and then different elasticities. In the equal elasticities case, adverse selection is always higher under pooling than under risk-differentiated premiums, while loss coverage first increases and then decreases with demand elasticity. We argue that loss coverage represents the efficacy of insurance for the whole population; and therefore that if demand elasticity is sufficiently low, adverse selection is not always a bad thing

A graphical model approach to simulating economic variables over long horizons

We present an application of statistical graphical models to simulate economic variables for the purpose of risk calculations over long time horizons. We show that this approach is relatively easy to implement, and argue that it is appealing because of the transparent yet flexible means of achieving dimension reduction when many variables must be modelled. Using United Kingdom data as an example, we demonstrate the development of an economic scenario generator that can be used by life insurance companies and pension funds. We compare different algorithms to select a graphical model, based on p-values, AIC, BIC, and deviance. We find them to yield reasonable results and relatively stable structures in our example, suggesting that it would be beneficial for actuaries to include these models in their toolkit

Impact of the Choice of Risk Assessment Time Horizons on Defined Benefit Pension Schemes

We examine the impact of asset allocation and contribution rates on the risk of defined benefit (DB) pension schemes, using both a run-off and a shorter 3-year time horizon. Using the 3-year horizon, which is typically preferred by regulators, a high bond allocation reduces the spread of the distribution of surplus. However, this result is reversed when examined on a run-off basis. Furthermore, under both the 3-year horizon and the run-off, the higher bond allocation reduces the median level of surplus. Pressure on the affordability of DB schemes has led to widespread implementation of so-called de-risking strategies, such as moving away from predominantly equity investments to greater bond investments. If the incentives produced by shorter term risk assessments are contributing to this shift, they might be harming the long term financial health of the schemes. Contribution rates have relatively lower impact on the risk

Histopathological study of soft tissue tumours in a tertiary health centre in southern part of Assam

Background: Soft tissue tumors are defined as mesenchymal proliferations which occur in the extraskeletal non-epithelial tissues of the body, excluding the viscera, coverings of brain and   lymphoreticular system. The objective of this study was to study the histopathological features of soft tissue tumors and to study the occurrence of soft tissue tumors in relation to age, sex and anatomical site.Methods: This study comprised of 89 cases studied over a period of two years. All soft tissue tumors, their gross features, microscopic findings were analysed in detail. Soft tissue tumors were divided into benign and malignant categories and further sub typing were done according to World Health Organization (WHO) classification. The distribution of soft tissue tumors according to the age, sex and site of occurrence was studied.Results: Out of 89 cases of soft tissue tumors, 76 cases were benign, 4 cases belonged to intermediate category and 9 cases were malignant. Adipocytic tumors formed the largest group constituting 39 cases. Vascular tumors were the second commonest (26 cases) followed by peripheral nerve sheath tumors (11 cases). The benign tumors were seen in younger age as compared to malignant tumors. Malignant soft tissue tumors was seen to be more common in male than female and pleomorphic sarcoma and liposarcoma was commonest (3 cases each).Conclusions: Benign tumors were more common than malignant. The most common benign tumors were lipoma followed by hemangioma and schwannoma. The most common malignant tumor was pleomorphic sarcoma. The benign tumors were seen in younger age as compared to malignant tumors

Modeling of WEDM Parameters while Machining Mg-SiC Metal Matrix Composite

In this paper an attempt has been made to study the effects of the process parameters of wire cut electrical discharge machining (WEDM) on Magnesium-Silicon Carbide MMC with 5% SiC in particulate form. For the analysis, six factors, namely pulse on time, pulse off time, spark gap voltage, peak current, dielectric flushing pressure and servo feed have been taken and a Taguchi L16 orthogonal array for two levels was used. Response surface methodology was also used to develop second-order models for material removal rate (MRR) and surface roughness (SR). From the analysis of variances, it has been observed that pulse on time and pulse off time were the most significant parameters among all those observed in predicting the MRR and SR, respectively

When is utilitarian welfare higher under insurance risk pooling?

This paper focuses on the effects of bans on insurance risk classification on utilitarian social welfare. We consider two regimes: full risk classification, where insurers charge the actuarially fair premium for each risk, and pooling, where risk classification is banned and for institutional or regulatory reasons, insurers do not attempt to separate risk classes, but charge a common premium for all risks. For the case of iso-elastic insurance demand, we derive sufficient conditions on higher and lower risks’ demand elasticities which ensure that utilitarian social welfare is higher under pooling than under full risk classification. Empirical evidence suggests that these conditions may be realistic for some insurance markets

When is utilitarian welfare higher under insurance risk pooling?

This paper considers the effect of bans on insurance risk classification on utilitarian social welfare. We consider two regimes: full risk classification, where insurers charge the actuarially fair premium for each risk, and pooling, where risk classification is banned and for institutional or regulatory reasons, insurers do not attempt to separate risk classes, but charge a common premium for all risks. For iso-elastic insurance demand, we derive sufficient conditions on higher and lower risks' demand elasticities which ensure that utilitarian social welfare is higher under pooling than under full risk classification. Using the concept of arc elasticity of demand, we extend the results to a form applicable to more general demand functions. Empirical evidence suggests that the required elasticity conditions for social welfare to be increased by a ban may be realistic for some insurance markets

Will genetic test results be monetized in life insurance?

If life insurers are not permitted to use genetic test results in underwriting, they may face adverse selection. It is sometimes claimed that applicants will choose abnormally high sums insured as a form of financial gamble, possibly financed by life settlement companies (LSCs). The latter possibility is given some credence by the recent experience of “stranger‐originated life insurance” (STOLI) in the United States. We examine these claims, and find them unconvincing for four reasons. First, apparently high mortality implies surprisingly high probabilities of surviving for decades, so the gamble faces long odds. Second, LSCs would have to adopt a different business model, involving much longer time horizons. Third, STOLI is being effectively dealt with by the U.S. courts. Fourth, the gamble would be predicated upon a deep understanding of the genetic epidemiology, which is evolving, subject to uncertain biases, and cannot predict the emergence of effective treatments

A tale of two pension plans: Measuring pension plan risk from an economic capital perspective

Years of high inflation, good investment returns and profits during the 1970s and 1980s created the illusion that defined benefit (DB) pension plans are easily affordable. Due to the creation of large surpluses during those years, pension risks have generally been excluded from an organisation's general risk management processes. Over the past decade or more however, increasing life expectancy and a steady fall in interest rates have meant that pension costs have increased. Consequently, many DB pension plans now have insufficient assets to cover all of their promised benefits. As a result, security of members' benefits may be compromised. This research, funded by the Society of Actuaries, builds on the works of Porteous et al. (2012), who performed a risk assessment of UK's Universities Superannuation Scheme (USS) based on the 2008 USS valuation report. In this research project, we update the analysis based on the most recently available valuation report. We then extend our analysis to carry out risk assessment of a stylised US plan, with the same membership profile as USS but with plan provisions modified to reflect a typical US DB plan design. We employ an economic capital approach to assess risks. Although the term economic capital has been widely used within the banking and insurance sectors, the concept is relatively new in the context of risk assessment of DB pension plans. In this research, we adapt the commonly used definitions of economic capital to appropriately capture the specific risk characteristics of DB pension plans. The analysis was carried out using stochastic economic scenario generators (ESG) calibrated to the UK and US economies. Specifically, we use a graphical model approach to ESG, proposed by Oberoi et al. (2019), alongside the well-known Wilkie model, to capture the sensitivity of the results to the choice of ESGs employed. The analysis also used a stochastic mortality model, similarly calibrated to the UK and the US. Results are shown for the full distribution of outcomes, but emphasis is given for certain percentile levels in line with the selected degree of confidence. We find that as a percentage of starting assets, the US stylised plan is more volatile than the USS plan. Moreover, the benefits of a larger allocation to long bonds are greater in the US stylised plan than the USS plan. In general, the effect on economic capital (for both plans) is much larger for changes in asset allocation than for changes to plan contributions. The full distribution of results provided should assist plan sponsors to understand the full range of uncertainties that they are assuming in the financing of their DB pension plans. An economic capital framework provides pensions regulators with another tool to consider their exposure to benefits guaranteed by the Pension Protection Fund and the Pension Benefit Guaranty Corporation. The analysis can also help the DB pension plan members to understand the uncertainties that the sponsor faces in the financing of DB pension plans