Bring consistency to ORSA, ALM and monitoring applications with the Option Interpolation Model (OIM). Insurance products are often characterized by embedded options and guarantees contractually promised to the policy holder. The value of these options and guarantees depends heavily on the prevailing economic conditions. Examples are the interest rate in case of profit-sharing options, or the return on investments in case of Unit-Linked products with a return guarantee. The value of embedded options and guarantees is an integral part of the market value of insurance liabilities. A correct and consistent valuation is therefore essential. Not only from the perspective of good risk management, but also for internal and supervisory reporting. While determining the current value of embedded options and guarantees is usually not a problem, obtaining their future market value as needed in forward-looking applications like ORSA and ALM is much more complicated. The main problem is that one needs to assess the option value for each year in each scenario, resulting in extremely lengthy calculation times. Ortec Finance offers a solution to this problem through our Option Interpolation Model (OIM).

The importance of an accurate and consistent valuation of embedded options and guarantees is strongly emphasized by the regulatory agencies. National supervisory authorities and the European Insurance Occupational Pensions Authority (EIOPA) pay specific attention to this topic and stress that it must occur separate from the technical provisions. Solvency II, officially taken effect per 1 January 2016, underlines the importance of a consistent and correct valuation as well as the necessity to include it in the Own Risk and Solvency Assessment (ORSA).

Besides using a consistent valuation of embedded options and guarantees for various Solvency II goals, it is also important to include it in other applications of the insurer. Think, for example, of Asset Liability Management (ALM), monitoring, the pricing of new products and other (internal) reports. Ideally, the same valuation method is used across all these applications, in order to maintain consistency and transparency and to make the interpretation of the various parts easier.

The standard method for valuing embedded options and guarantees is risk-neutral Monte Carlo valuation. To apply this method in forward-looking scenario applications is, however, extremely time- consuming. To circumvent these excessively long calculation times, approximation techniques like curve fitting, Least-Squares Monte Carlo (LSMC) and replicating portfolios have been developed.

In this article we discuss how our proprietary approximation method, the Option Interpolation Model (OIM), takes the value of options and guarantees into account in a correct and consistent manner for the various applications of the insurer. The great appeal of this method is its general applicability, flexibility and accuracy. This makes it highly suitable for the insurance market.

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