Browsing by Subject "Solvency II"

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  • Luoma, Arto; Puustelli, Anne; Koskinen, Lasse (2008)
    In this paper a Bayesian approach is utilized to analyze the role of the underlying asset and interest rate model in the market consistent valuation of life insurance policies. The focus is on a novel application of advanced theoretical and computational methods. A guaranteed participating contract embedding an American-style option is considered. This option is valued using the regression method. We exploit the flexibility inborn in Markov Chain Monte Carlo methods in order to deal with a fairly realistic valuation framework. The Bayesian approach enables us to address model and parameter error issues. Our empirical results support the use of elaborated instead of stylized models for asset dynamics in practical applications. Furthermore, it appears that the choice of model and initial values is essential for risk management.
  • Ronkainen, Vesa; Koskinen, Lasse; Koskela, Laura (2008)
    In the EU the supervision of the insurance industry is expected to step into the new Solvency II framework within some years. The new framework will mean a fundamental update for both valuation and solvency requirements. Instead of just offering a standard formula for calculating the solvency capital requirement, in Solvency II insurance companies will be encouraged to develop internal models that are expected to be able to assess numerous effects which would not be easily quantified using the “one fits all” standard approach. However, to develop an internal model that will satisfy the approval criteria is a major project, during which the model builders and implementers will be faced with serious challenges.
  • Koskela, Laura; Ronkainen, Vesa; Puustelli, Anne (2008)
    Vakuutusvalvonta. Reports 1
    Raportissa tutustumme eräisiin yleisiin stokastisiin osake- ja korkomalleihin päähuomion ollessa pitkäntähtäimen simulaatioissa, jotka ovat tyypillistä mm. henki- ja eläkevakuuttamiselle. Pohdimme käytännön mallintamisen eri vaiheita Solvenssi II -projektin sisäisten mallien näkökulmasta.
  • Kaliva, Kasimir; Koskinen, Lasse; Ronkainen, Vesa (2007)
    There is a major trend in the insurance sector towards arbitrage-free valuation of insurance liabilities and assets. The assumption of no-arbitrage is fundamental in financial modelling. This paper surveys assumptions of arbitragefree modelling and studies their consequences for the use of internal model in insurance. The model uncertainty arises as a particularly severe problem under the assumption that the conditions of arbitrage-free complete market theory do not hold and all participants in the market are not fully rational. We argue that the approximation errors of these idealistic assumptions are generally larger in insurance applications than elsewhere in the financial sector. Hence, the model uncertainty plays a particularly important role in the use of internal models. This should be taken into account in the development of the models and in risk management practice. Finally, we present some known Bayesian methods that might be useful for managing the model risk.
  • Pylkkönen, Pertti; Savolainen, Eero (2016)
    Bank of Finland. Bulletin 2/2016
    At the beginning of 2016, a new life and non-life insurance company solvency regulation was launched in EU, the so-called Solvency II regime. In the new regulation, both assets and liabilities of insurance companies are valued at market terms. The timing of the reform is awkward for the companies, as low interest rates and economic uncertainty burden company solvency.
  • Korhonen, Pekka; Koskinen, Lasse (2008)
    In this paper, we explore critical aspects related to the use and development of internal models in insurance companies’ risk and capital management. Our aim is to find out how crucial the various risk factors of internal models are for successful performance of essential management sub-tasks. The problem is approached hierarchically starting from relevant management sub-tasks, then analyzing the possible causes for the failure of the firm, and finally ending up with an analysis of the most important risk components which have to be taken into account when internal models are used and developed. As source information for causal and risk factors, we use a cause effect model of the European insurance supervisors and an international insurance survey. The problem is formulated as a multiple criteria decision making task with a hierarchical structure. We use the Analytical Hierarchy Process as a planning tool to analyze management criteria, causal and risk factors. The evaluation is carried out by a panel consisting of senior managers of Finnish insurance companies. As a result, we obtain a list and rank order of the key risk components for the use and development of internal models. The results also illustrate the potential usefulness of decision science tools when making subjective decisions in the context of internal models.