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The Distribution of Failure in Medical and Health Insurance Claim: The Implications of Multiple Binary Logistic Regressions

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2023, v.21 no.11, pp.91-102
Norimah RAMBELI (Universiti Pendidikan Sultan Idris)
Norasibah Abdul JALIL (Universiti Pendidikan Sultan Idris)
Nooraisah KATMON (Universiti Pendidikan Sultan Idris)
Asmawi HASHIM (Universiti Pendidikan Sultan Idris)
Emilda HASHIM (Universiti Pendidikan Sultan Idris)
Mohamad Rohieszan RAMDAN (Universiti Pendidikan Sultan Idris)
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Abstract

Purpose: Ownership of insurance policy among Malaysians is growing, especially since the Covid-19 pandemic at the end of 2019. The aim of this study is to examine the effects of economic and non-economic factors that may contribute to incidence of failures in medical and health insurance claims. Research design, data and methodology: This study used primary data with samples collected in an online survey involving 210 respondents, in Perak State. By adopting the Howards-Sheth consumer behavior theory, the multiple binary logistic regressions were used. Results: The study established that income, saving and prior experience is the significant factors effecting the incidence of claim failures in at least 95 percent cases. This is supported by the Howards-Sheth consumer behavior theory. When the odds ratio value of income is at 47.84 percent, insurance claim will have less probability of success. At a certain income level, the probability of failure in insurance claim will be lower. Conclusions: The study confirms that an increase in income will increase the probability success rate in insurance claim. Yet, rising income, the probability of the insurance policyholder to fail in insurance premium payment will be reduced. In conclusion, an increase in income of the policyholder is expected to reduce the probability of failure in insurance claims.

keywords
Insurance Claims, Social and Economic Factors, Income, Insurance Claim Failure

The Journal of Distribution Science