Volume 15, Issue 2

Increased dependency on technology and data usage has simultaneously enhanced the risk exposures and vulnerabilities of organizations globally. This paper investigates this issue in India by analyzing the survey-based data we collect and provides a framework for qualitative assessment of cyber risks. The paper uses the Structural Equation Model (SEM) to validate the conceptual cyber-risk model that we have developed using the key-risk factors, such as the level of awareness, perceived risk likelihood, level of cyber-security, and cyber-risk exposures. The study results show that the risk vulnerability and the perceived risk likelihood have a positive impact on risk exposure, while risk awareness, cybersecurity, and control measures have a negative relationship. This study also identifies the causal factors among the exposures and the findings can help organizations prioritize their cybersecurity protection investments and caution insurers to take necessary mitigation measures for effective cyber-risk management and financing for their clients.

The disposition effect is a commonly observed puzzle in financial markets. Several theoretical explanations for the disposition effect have been provided; however, it remains unresolved. We attempt to explain the effect by incorporating ambiguity attitudes that vary depending on the reference point. We extend the smooth model of ambiguity by Klibanoff, P., M. Marinacci, and S. Mukerji. 2005. “A Smooth Model of Decision Making under Ambiguity.” Econometrica 73: 1849–92 to depend on the reference point. Numerical examples show that the disposition effect is more pronounced under our reference-dependent smooth model of ambiguity if the investor gets her/his utility from the realized gains and losses.

The supply-side contribution to the surge of medical expense is overlooked in the Korean health insurance market. Commonly, the demand-side is accounted for the excessive increase in medical consumption. Previous studies suggest the moral hazard or adverse selection of Fee-For-Service Health Insurance (FFS) policyholders as the source of the problem. However, this paper focuses on the moral hazard of medical institutions using Korea Health Panel (KHP) Data version 1.5 from year 2008–2016. This study finds the medical usage difference between FFS holders and non-holders were greater for clinics and local hospital visits than the visits to general hospitals or special hospitals. This implies that supply-side contributes to the ex-post moral hazard of health insurance.

Climate change is predicted to make extreme weather events worse and more frequent in many places around the world. In New Zealand, the Earthquake Commission (EQC) was created to provide insurance for earthquakes. In some circumstances, however, homeowners affected by extreme weather events can also make claims to the EQC – for landslip, storm or flood events. In this paper, we explore the impact of this public natural hazard insurance on recovery from weather-related events. We do this by using a proxy for short-term economic recovery: satellite imagery of average monthly night-time radiance. Linking these night-time light data to precipitation data records, we compare areas which experienced damage from extreme rainfall episodes to those that suffered no damage even though they experienced extreme rainfall. Using data from three recent intense storms, we find that areas that experienced property damage, and were paid in a timely manner by EQC, did not fare any worse than areas that suffered no property damage but were exposed to these extreme precipitation events. This finding suggests that EQC insurance is serving its stated purpose by protecting claimants from the adverse impact of extreme weather events.

This study aims to demonstrate the effect of the cost of telematics and loss ratio improvement on the coverage demand for health promotion medical insurance. Real-time monitoring via telematics is expected to alleviate moral hazard of insured persons through the “analogical experience rating system,” resulting in a decreased claim cost and an improved loss ratio. In reality, however, the real-time monitoring on a continuous basis imposes a cost burden on insurers and thus, certain expense loadings apply to insurance premiums. The analysis based on the modified separating market equilibrium model reveals that people tend to opt for partial insurance coverage, and high-risk individuals even stay uninsured unless the expense loadings are not excessive. This result implies that the demand for health promotion medical insurance can decrease, and may conduce a market shrinkage, unless the improvement of loss ratio sufficiently surpasses the cost of telematics utilization.