Abstract
Aim: Actuaries are financial engineers who construct arrays of risk models combining mathematical techniques in order to carry out required actuarial calculations, such as reserve valuation and pricing. The main purpose is to identify some reliable models which price risk factors embedded in insurance products. Health insurance products which are very different in nature from life insurance products must be examined and priced carefully. This paper discusses predominantly two risks. Excess claims ratio and Rectangularisation risks. Background: The first author, Dr. S. Jayaprakash was responsible for Enterprise Risk Management with MetLife India. He was earlier associated with Life Insurance Corporation of India & Oracle Financial Services. Dr. P. K. Dinakar, the second author, qualified as Fellow of the Institute of Actuaries of India, was Chief Actuary of MetLife India Insurance. He was earlier associated with Life Insurance Corporation of India & Birla Sunlife. The third author, Dr. Michael Ha, FSA, MAAA, CFA, CPA (Australia), FRM, PRM, LLM, was Vice President of Strategic Business Initiatives Units at ING Life Insurance in its Taiwan operation. He started his actuarial career at MetLife, Canada. Earlier, the first and third authors worked on a research paper titled “Modeling Policyholder Behavior through Insurance Resonant Marts for Pricing Options and Guarantees” [1] which was presented at the 5th World Congress on Engineering and Technology. The seven authors decided to collaborate on the current research paper for health insurance design and financing purposes.
Highlights
IntroductionThere is no ideal health care model or health Insurance plan that could solve the challenging issues
Health Care & Health Insurance poses major challenges across the globe
We present a theoretical model to look at the Rectangularisation of survival curve and compression of the morbidity factors based on some hypothetical scenarios
Summary
There is no ideal health care model or health Insurance plan that could solve the challenging issues. Health insurance losses contain both tangible and intangible components with the latter being hidden and embedded implicitly. It requires a higher degree of cooperation and management by sector stakeholders. Though the risk factors that exist in health insurance are various, the problems faced in the health insurance industry are common and numerous. Based on the primary & secondary data, we analyze the issues faced and build theoretical models that could help individuals to determine an “Ideal Age for purchasing Health Insurance” similar to the idea of “Ideal age to plan for pension & annuity”
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