The security mortgage valuation in a stochastic perspective

The reverse mortgage market has been expanding rapidly in developed economies in recent years. Reverse mortgages provide an alternative source of funding for retirement income and health care costs. Increase in life expectancies and decrease in the real income at retirement continue to worry the those who are retired or close to retirement. Therefore, financial products that help to alleviate the “risk of living longer” continue to be attractive among the retirees. Reverse mortgage contracts involve a range of risks from the insurer’s perspective. When the outstanding balance exceeds the housing value before the loan is settled, the insurer suffers an exposure to crossover risk induced by three risk factors: interest rates, house prices and mortality rates. We analyse the combined impact of these risks on the pricing and the risk profile of reverse mortgage loans in a stochastic interest-mortality-house pricing model. Our results show shows  that pricing of reverse mortgages loans does not accurately assess the risks underwritten by reverse mortgages lenders and that failing to take into account mortality improvements substantially underestimates the longevity risk involved in reverse mortgage loans

Risk Profiles of Life Insurance Participating Policies: Measurement and Application Perspectives

The paper deals with the calculation of suitable risk indicators for Life Insurance policies in a Fair Value context. In particular, aim of this work is to determine the quantile reserve for Life insurance Participating Policies. This goal poses both methodological and numerical problems: for this reason the paper discusses both the choice of the mathematical models and the calculation tecnique. Numerical application illustrates the results

Pension funds risk analysis: stochastic solvency in a management perspective

The aim of the paper is to deal with the solvency requirements for Defined Contributions Pension funds. The probability of underfunding is investigated in a stochastic framework by means of the funding ratio, which is the ratio of the market value of the assets to the market value of the liabilities. Demographic and investment risks are modelled by means of diffusion processes. Their impact on the total riskiness of the fund is analyzed via a quantile approach

Cluster Analysis for Driver Aggressiveness Identification

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A “pay-how-you-drive” car insurance approach through cluster analysis

As discussed in the recent literature, several innovative car insurance concepts are proposed in order to gain advantages both for insurance companies and for drivers. In this context, the “pay-how-you-drive” paradigm is emerging, but it is not thoroughly discussed and much less implemented. In this paper, we propose an approach in order to identify the driver behavior exploring the usage of unsupervised machine learning techniques. A real-world case study is performed to evaluate the effectiveness of the proposed solution. Furthermore, we discuss how the proposed model can be adopted as risk indicator for car insurance companies