Market-consistent embedded value in non-life insurance: how to measure it and why
Purpose – The purpose of this paper is to transfer the concept of market-consistent embedded value (MCEV) from life to non-life insurance. This is an important undertaking since differences in management techniques between life and non-life insurance make management at the group level very difficult. The purpose of this paper is to offer a solution to this problem. Design/methodology/approach – After explaining MCEV, the authors derive differences between life and non-life insurance and develop a MCEV model for non-life business. The model framework is applied to a German non-life insurance company to illustrate its usefulness in different applications. Findings – The authors show an MCEV calculation based on empirical data and set up an economic balance sheet. The value implications of varying loss ratios, cancellation rates, and costs within a sensitivity analysis are analyzed. The usefulness of the model is illustrated within a value-added analysis. The authors also embed the MCEV concept in a simplified model for an insurance group, to derive group MCEV and outline differences between local GAAP, IFRS and MCEV. Practical implications – The analysis provides new and relevant information to the stakeholders of an insurance company. The model provides information comparable to that provided by embedded value models currently used in the life insurance industry and fills a gap in the literature. The authors reveal significant valuation difference between MCEV and IFRS and argue that there is a need for a consistent MCEV approach at the insurance-group level. Originality/value – The paper presents a new valuation technique for non-life insurance that is easy to use, simple to interpret, and directly comparable to life insurance. Despite the growing policy interest in embedded value, not much academic attention has been given to this methodology. The authors hope that this work will encourage further discussion on this topic in academia and practice.
