Volume 18, Issue 1

Most Asian countries exhibit modest income levels and low insurance penetration, while facing rising exposures to natural disasters due to climate change. This paper discusses a strategy for regional collaboration among Asian countries to build resilience through participation in a regional insurance pool. At the core of this strategy is a new type of Climate De-risk Insurance (CDRI) product, where a portion (10–20 %) of the premium is designated for risk assessment and mitigation as compared to conventional loss coverage. CDRI products are offered through commercial insurance companies in participating countries and distributed through a network of dedicated risk management agencies. CDRI insurance needs to be guided by enabling regulation, with greater emphasis on the effectiveness of the use of funds in risk mitigation and claims payments. Moreover, the CDRI development fund can be created in the form of a public-private partnership, as a means of mobilizing financial support for rolling out CDRI insurance.

In this paper, we introduce and employ a multi-agent model of entry to analyze barriers to entry in the U.S. property casualty insurance industry. Our estimations are conducted at the market-year level, enabling a detailed exploration of the relative importance of barriers across three dimensions: geography, product, and time. Our findings reveal that entry barriers are both prevalent and significant in the U.S. property casualty insurance industry, with de novo entrants encountering the most challenges from product barriers across all markets. We observe that expanding across product lines is more costly than expanding across states. Particularly, New York and California exhibit the strongest state barriers. Among various product lines, our research identifies that insurance expertise in mortgage guaranty and medical professional liability insurance presents the most substantial barriers to entry. This study contributes valuable insights into the dynamics of entry barriers in the U.S. property casualty insurance industry, highlighting the importance of considering geographic and product-specific knowledge, as well as temporal factors, in the context of market entry. Through analyses across these dimensions, we enhance the understanding of the challenges faced by new entrants and shed light on the specific market conditions shaping entry barriers.

Studying driving records (DR) and assessing their risk relativity is crucial for auto insurance rate regulation. Typically, the evaluation of DR involves estimating risk using empirical loss cost or modeling approaches such as Generalized Linear Models (GLM). This article presents a novel methodology employing Generalized Additive Models (GAM) to estimate the risk relativity of DR. By treating the integer level of DR as a continuous variable, the proposed method offers enhanced flexibility and practicality in evaluating the associated risk. Extending the linear model to GAM is a critical advancement that harnesses advanced statistical methods in actuarial practice, providing a more statistically robust application of the proposed approach. Moreover, the integration of functional patterns with Class or Territory enables the investigation of statistical evidence supporting the existence of associations between risk factors. This approach helps address the issue of potential double penalties in insurance pricing and calls for a statistical solution to overcome this challenge. Our study demonstrates that utilizing the GAM approach yields a more balanced estimation of DR relativity, thereby reducing discrimination among different DR levels. This finding highlights the potential of this statistical method to improve fairness and accuracy in auto insurance rate making and regulation.

Understanding climate-related risks and stresses is an emerging area of interest for life insurers globally. However, there are complexities in quantifying climate risk stress impacts due to the long-term nature of these risks, and the interactions between physical and transition risks over time. In this paper, we build on understanding the financial impacts of climate risk stresses for life insurers in Australia, by identifying key climate-related mortality risks, and quantifying these by applying short- and long-term stresses from existing literature to two synthetic life insurers. We perform sensitivity tests to demonstrate the variability and range of plausible results. Overall, results show that the expected financial impacts from short-term events in isolation are small relative to expected long-term changes in mortality. Furthermore, the value of a mortality hedge is even more apparent given the increased mortality risk for yearly renewable-term insurers in the short to medium term.