Suchergebnisse

Abstract
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.

Abstract
Morbidity and Mortality have also been a reason for concern for the insurers as increased morbidity and mortality contribute to a higher cost of claims including claim frequency. Currently, there are only two rating factors (Age and types of cattle) being adopted by the insurers while determining the premium rates and there is no risk-based pricing adopted for Cattle Insurance in India. The main objective of this paper is to identify the important rating factors influencing the mortality and morbidity trends among different cattle types in India. Secondly, there is a need to examine whether the mortality and morbidity trends vary across different parameters like animal type, breeds, age, gender, agro-climatic zone, types of formers/animal owners, etc. If it varies, then to find out the degree of variations and also measure the impact of these rating factors on cattle mortality. This paper focuses on the analysis of the morbidity and mortality of cattle across different types of cattle, breeds, age groups, gender, and different agro-climatic regions, etc. Further, it also examines the differences in cattle management practices; particularly the frequency and the quantity of feed, types, and quality of feed (nutritional value) given, animal healthcare management, exposure to catastrophic risk hazards, etc., with a view to developing risk-based pricing for cattle insurance. This would help insurers to understand the changes in cattle mortality and morbid trends and also build a comprehensive mortality table across different types and breeds of cattle. This would also immensely help the insurers in determining risk-based premium rates among different types of animals, their breeds, geographic regions, customer types, etc. which would enable in developing sustainable cattle insurance portfolio in the Indian insurance market. The output of the analysis can also be used by the insurers to develop index-based livestock insurance as well as parametric insurance.