Managing the risks of energy efficiency insurances in a portfolio context: An actuarial diversification approach

Highlights

• Quantitative analysis of Energy Efficiency Insurances (EEI)

• Insurers should consider different types of EEI in course of market introduction.

• EEI exhibit notable diversification potential for existing insurance portfolios.

• EEIs potentially replace weather derivatives in diversified portfolios.

Abstract

To achieve ambitious international climate goals, an increase of energy efficiency investments is necessary and, thus, a growing market potential arises. Concomitantly, the relevance of managing the risk of financing and insuring energy efficiency measures increases continuously. Energy Efficiency Insurances encourage investors by guaranteeing a predefined energy efficiency performance. However, literature on quantitative analysis of pricing and diversification effects of such novel insurance solutions is scarce. This paper provides a first approach for the analysis of diversification potential on three levels: collective risk diversification, cross product line diversification, and financial hedging. Based on an extensive real-world data set for German residential buildings, the analysis reveals that underwriting different Energy Efficiency Insurance types and constructing Markowitz Minimum Variance Portfolios halves overall risk in terms of standard deviation. We evince that Energy Efficiency Insurances can diversify property insurance portfolios and reduce regulatory capital for insurers under Solvency II constraints. Moreover, we show that Energy Efficiency Insurances potentially supersede financial market instruments such as weather derivatives in diversifying property insurance portfolios. In summary, these three levels of diversification effects constitute an additional benefit for the introduction of Energy Efficiency Insurances and may positively impact their market development.

Introduction

Total energy demand is steadily increasing while anthropogenic climate change already induces severe consequences, especially for developing countries (Bathiany, Dakos, Scheffer, & Lenton, 2018). Ambitious international climate goals contribute to the rising worldwide interest in energy efficiency (EE) investments. However, various barriers associated with EE investments lead to a well-researched underinvestment situation dubbed “energy efficiency gap” (Gillingham & Palmer, 2014; Jaffe & Stavins, 1994). Risk transfer solutions may overcome these barriers especially prevalent in the private sector by guaranteeing a certain project performance (Häckel, Pfosser, & Tränkler, 2017; Töppel & Tränkler, 2019). While in the business sector Energy Service Companies already offer risk transfer contracts and Energy Efficiency Insurances (EEI) slowly gain a foothold (Hartford Steam Boiler, 2015; KlimaProtect, 2018; Mills, 2003a; Mills, Kromer, Weiss, & Mathew, 2006), so far research and real-world applications for the private sector from the viewpoint of insurers is scarce. Thus, the main objective of this paper is to quantitatively analyze emerging diversification effects when adding novel EEIs to an existing insurance portfolio. EEIs guarantee a certain level of energy bill savings or maximum costs in return for a premium payment by the insured entity and could be an interesting insurance business opportunity for several reasons (Micale & Deason, 2014; Mills, 2003a): First, research on decision-making has shown that individual decision-makers should be very receptive to insurance solutions due to their individual risk preferences (Häckel et al., 2017; Shogren & Taylor, 2008; Stern, 2011). Thus, we exemplarily focus on EEIs for private residential building retrofitting. Second, an enormous retrofitting potential and promising market situation prevails in Europe. For example, the EE targets of the Paris climate agreement imply that the retrofitting rate of the residential building stock for the case of Germany needs to double from 1% to 2% (Achtnicht & Madlener, 2014). Third, the market potential is additionally supported by an increasing green consciousness of consumers (Achtnicht & Madlener, 2014). Consequently, green financial products such as green bonds enjoy increasing popularity among investors. Fourth, EE investments offer direct and indirect loss-prevention benefits for insurers. Direct loss-prevention is associated with auxiliary co-benefits that reduce insurance claims (Mills, 2003b; Pye & McKane, 2000). For instance, Mills (2003b) finds 78 examples that offer risk-management benefits such as fire-safety of high-efficiency torchiere light fixtures. Indirect loss-prevention benefits are realized by the reduction of climate change and its adverse effects (Mills, 2007; Parry, 1993; Tucker, 1997). When EE investments reduce global warming, insurers may be faced with lower economic costs of natural disasters associated with climate change (Botzen, van den Bergh, & Bouwer, 2010; Kousky, 2014; Mills, 2005).

In this paper, we examine whether arising diversification effects constitute an additional benefit of EEIs from the viewpoint of insurers. When insurance claims of EEIs and those of other insurance types are not perfectly positively correlated, the overall risk of the portfolio can be reduced. To analyze diversification effects of EEIs, we stepwise evaluate portfolio risk reduction on three levels based on the regulatory framework of Solvency II: First, we look at the EEI portfolio level and investigate the diversification effects of combining different EEIs. Second, we analyze the impact of adding EEIs to existing insurance portfolios such as property insurances. Third, we examine the risk reduction of hedging with financial derivatives when holding a portfolio consisting of EEIs and property insurances. Most of the insurance literature on diversification effects is based on empirical evidence. As EEIs define a new product category historical data is unavailable. Thus, we use real-world data on the underlying risk factors to forecast insurance claims and calculate premiums based on a risk-neutral pricing approach.

Thereby, to the best of our knowledge, we are the first to quantitatively apply concepts of diversification to evaluate the advantageousness of EEIs from a portfolio perspective. Our analysis has several interesting implications: First, by introducing EEIs with different contractually defined risk events, risk exposure may already be reduced within this novel insurance class. Thus, insurers should consider both policy types. Second, meaningful diversification effects with other insurance products could be a driver for a wide market introduction of EEIs in the private sector. In turn, this could significantly accelerate EE investments (Micale & Deason, 2014). Third, the introduction of EEIs potentially reduces the need for costly financial hedging instruments such as weather derivatives. Because EEIs are highly dependent on outdoor temperature, they could be a natural hedge for insurance products exhibiting opposite risk exposures.

The remainder of the paper is structured as follows: Section 2 elaborates on two different EEIs and elements of portfolio analysis based on the relevant literature. Section 3 introduces our asset and portfolio modeling as well as the optimization approach. The empirical data sets and model selections for the risk factors are presented in Section 4. Subsequently, the results of the simulated diversification effects are presented and discussed in Section 5. Practical and managerial implications are provided in Section 6. The final Section 7 summarizes and concludes.