Valuation Of Insurance Liabilities Research Articles

The aporetic financialisation of insurance liabilities: Reserving under Solvency II

AbstractThe valuation of insurance liabilities has traditionally been dealt with by actuaries, who closely monitored underlying illiquid features, assumed a long-term perspective, and exercised their own subjective, expert judgment. However, the new EU regulatory regime of Solvency II (S2) has come to require market-consistent valuation supplemented by a risk-sensitive capital. This is considered an unwanted shift towards short-termism that is misaligned with the industry's long term and countercyclical character. The new principles place the ‘technicalising’ logic of financial economics over ‘contextualising’ actuarial know-how. Following existing analytics of valuation from the ethnography of reinsurance markets and the social studies of finance, such requirements appear either as an alarming attack against the actuarial component of traditional valuation practice, or else as a preserver of it, through a process of enfolding at the heart of the financialisation project. This article holds that the case of S2 challenges both these analytics of valuation. S2’s financialisation project, precisely by attempting to construct itself, deconstructs itself into an actuarial project, in a recurring, aporetic process. In this respect, fair (or otherwise) valuation remains always undecidable, inconclusive, and thus responsible.

Fair dynamic valuation of insurance liabilities: a loss averse convex hedging approach

Hedging techniques have been widely adopted in market-consistent or fair valuation approach required by recent solvency regulations, to take into account the market prices of the hedgeable parts of insurance liabilities. In this study, we investigate the fair dynamic valuation of insurance liabilities, which are model-consistent (mark-to-model), market-consistent (mark-to-market), and time-consistent, as proposed by Barigou et al. (2019) in a multi-period setting. We introduce the loss averse convex hedging technique, which ‘punishes’ loss outcomes more than gain outcomes. We prove that fair dynamic valuations are equivalent to the class of loss averse convex hedge-based valuation. Moreover, we propose and provide a complete characterization of loss averse mean–variance hedging and show how to implement loss averse mean–variance hedge-based dynamic valuations using numerical examples.

The valuation of stochastic insurance liabilities using a structural model approach

Liability drives insurers' businesses. This paper examines the structural model approach of credit risk for the valuation of insurance liabilities and insurers' equity, and considers a stochastic process for liability. Grosen and Jørgensen's (2002) study presents the current approach taken by insurers; however, the model's structure is very simple, and its liability structure in particular has a deterministic time function. In contrast, we analyze a model that analytically evaluates an insurer's liability with the stochastic process. Furthermore, we analyze the model's default option originally presented by Myers and Read (2001).

From ruin theory to solvency in non-life insurance

We start from ruin theory considerations in the classical Cramér–Lundberg model. We modify these considerations step by step so that finally we arrive at today’s solvency assessments for non-life insurance companies. These modifications include discussions about time horizons, risk measures, financial returns, and valuation of insurance liabilities.

A Comparative Overview of Deterministic and Stochastic Modeling in Actuarial Applications

There has been a significant increase in the use of stochastic models in actuarial applications in recent years. Stochastic actuarial models are increasingly being used to determine regulatory and economic capital, and in the valuation of insurance liabilities, especially those containing complex embedded guarantees or derivatives. For example, variable annuities in the U.S. and segregated funds in Canada. The disadvantages of deterministic modeling in risk assessment are numerically illustrated using the Solvency II, US RBC and Canadian MCCSR standard formulas as examples of deterministic risk models. Generally, the analysis in the paper supports a stochastic modeling framework for the solvency assessment of an insurer given a market valuation paradigm for its assets and liabilities.

A Fair Value Discount Factor (Deflator) Applied to the Valuation of Earnouts

Abstract In this article, I propose an approach to determine the appropriate discount factors to value an earnout. I start with an example and provide a set of discount factors to value the earnout. I then show that the proposed discount factors meet certain conditions required to ensure that the valuation of the earnout is market consistent. Since the discount factors derived here are scenario specific, the same set of discount factors can be used to value any earnout structure based on the same performance metric and time period. The approach I present is by no means original, only an application of techniques used in other areas of valuations (in particular, in the valuation of insurance liabilities). To be consistent with the actuarial literature, I term the scenario-specific discount factors “stochastic deflators.”

“An Approach to Fair Valuation of Insurance Liabilities Using the Firm’s Cost of Capital”, Luke N. Girard, July 2002

(2002). “An Approach to Fair Valuation of Insurance Liabilities Using the Firm’s Cost of Capital”, Luke N. Girard, July 2002. North American Actuarial Journal: Vol. 6, No. 2, pp. 41-46.

An Approach to Fair Valuation of Insurance Liabilities Using the Firm’s Cost of Capital

There are two competing and seemingly different methodologies for calculating fair values—the direct and indirect methods. The direct approach has the advantage of providing a more reliable assessment of the risk of financial leverage. The indirect method can be structured to adjust for financial leverage, however, the methodology becomes excessively complex. The advantage of the indirect method is that it can be more easily related to exit prices. Intuitively, an exit price should reflect both the creditworthiness of the firm and the cost of capital of the firm. How are these two concepts related? This paper attempts to advance the fair valuation methodology by addressing these questions and presenting a methodology for deriving the firm or own credit risk assumption (to be used with the direct method) that is consistent with the cost of capital assumption used with the indirect method.