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Rectangularisation Issues in Health Economics &Insurance: Measures and Mitigations

Rectangularisation Issues in Health Economics &Insurance: Measures and Mitigations
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摘要 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. 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.
作者 S. Jayaprakash P. K. Dinakar Michael Ha Zhengjun Jiang Uthit Siriwan Manning Li Chukwuemeka Okeagu S. Jayaprakash;P. K. Dinakar;Michael Ha;Zhengjun Jiang;Uthit Siriwan;Manning Li;Chukwuemeka Okeagu(Nanobi Data and Analytics Private Ltd., Bangalore, India;The Institute of Actuaries of India, Mumbai, India;Xi’an Jiaotong-Liverpool University, Suzhou, China;Bryant College, Beijing Institute of Technology, Zhuhai, China;Faculty of Business, Charisma University, Turks and Caicos, UK;Bank of Communications, Suzhou Branch, Suzhou, China)
出处 《Journal of Applied Mathematics and Physics》 2016年第7期1327-1335,共10页 应用数学与应用物理(英文)
关键词 Claims Ratio VALUATION De-Risk Rectangularisation MORBIDITY Claims Ratio Valuation De-Risk Rectangularisation Morbidity
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