Decision on Insurance Policy Selection by weighted Correlation Approach on Neutrosophic Fuzziness through TOPSIS

Risk management recognizes and controls the hazards connected with our decisions and activities, whether they involve our assets or health. The fundamental goal of insurance is to mitigate the risks an insured person experiences. Term insurance is a kind of life insurance that is polarized among insurance policy buyers. The quantitative and qualitative attributes of term insurance are often articulated using language terminology. Consequently, the selection of a term insurance policy can be characterized as an uncertain multicriteria decision-making (MCDM) problem. In this work, we substituted the distance measure in the technique for order preference by similarity to an ideal solution (TOPSIS) with a neutrosophic weighted correlation coefficient to address the ambiguity involved in the selection of distance measure in the TOPSIS approach. This work also offers weighted closeness measures and an index coefficient required in the neutrosophic TOPSIS approach. The suggested neutrosophic TOPSIS is used to identify the best term insurance policy for its clients. The outcome of the neutrosophic TOPSIS suggests that the tenth insurance firm exhibits the highest level of acceptance, whereas the first firm represents the least favorable option. The consistency and robustness of the proposed approach are established through comparison and sensitivity analysis.

Abstract licence: CC BY-NC

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