Safety Margins for Systematic Biometric and Financial Risk in a Semi-Markov Life Insurance Framework
نویسنده
چکیده
Insurance companies use conservative first order valuation bases to calculate insurance premiums and reserves. These valuation bases have a significant impact on the insurer’s solvency and on the premiums of the insurance products. Safety margins for systematic biometric and financial risk are in practice typically chosen as time-constant percentages on top of the best estimate transition intensities. We develop a risk-oriented method for the allocation of a total safety margin to the single safety margins at each point in time and each state. In a case study, we demonstrate the suitability of the proposed method in different frameworks. The results show that the traditional method yields an unwanted variability of the safety level with respect to time, whereas the variability can be significantly reduced by the new method. Furthermore, the case study supports the German 60 percent rule for the technical interest rate.
منابع مشابه
Safety margins for unsystematic biometric risk in life and health insurance
In multistate life and health insurances, the pattern of states of the policyholder is random, thus exposing the insurer to an unsystematic biometric risk. For this reason safety margins are added on premiums and reserves. But in contrast to non-life insurance, traditionally the safety margins are not chosen explicitly but implicitly in form of a valuation basis of first order. If we define the...
متن کاملOn the decomposition of risk in life insurance
Assuming a product space model for biometric and financial events, there exists a rather natural principle for the decomposition of gains of life insurance contracts into a financial and a biometric part using orthogonal projections. In a discrete time framework, the paper shows the connection between this decomposition, locally variance-optimal hedging and the so-called pooling of biometric ri...
متن کاملSystemic Risk Evaluation of Banks and financial institutions applying Markov clustering method and centrality measures of risk
Systemic risk is the risk beared by an economic system because of a special organization. This means that a liquidity problem or a financial crisis in one company could trigger a chain of reactions that puts the whole market into trouble. This kind of risk was underestimated until 2008 financial crisis. Now federal regulations exist for controlling this risk of financial institutions. Among div...
متن کاملContinuous time semi-Markov inference of biometric laws associated with a Long-Term Care Insurance portfolio
Unlike the mortality risk on which actuaries have been working for more than a century, the long-term care (LTC) risk is young and as of today hardly mastered. Semi-Markov processes have been identified as an adequate tool to study this risk. Nevertheless, access to data is limited and the associated literature still scarce. Insurers mainly use discrete time methods directly inspired from the s...
متن کاملInterconnected Risk Contributions:A Heavy-Tail Approach to Analyze U.S. Financial Sectors
This paper investigates the dynamic evolution of tail risk interdependence among U.S. banks, financial services and insurance sectors. Life and non-life insurers have been considered separately to account for their different characteristics. The tail risk interdependence measurement framework relies on the multivariate Student-t Markov switching (MS) model and the multiple-conditional value-at-...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015