Insurance Tender Selection Using Multiple Criteria Decision Making

Abstract

Introduction: This paper involves assessing the most suitable insurance company for company X1 using Multiple Criteria Decision Making (MCDM). This company is one of the biggest financial organizations and problems were identified with the existing process of insurance tender selection. The manual nature of the current process is very tedious and takes almost three months to complete and this increases the probability of error and also leads to employee dissatisfaction.Artifact: To provide a solution to this problem, several MCDM models including Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and Fuzzy Sets were researched to determine the best MCDM model for this scenario. After conducting a thorough research it was concluded that the best approach would be to use a hybrid methodology that combines AHP and TOPSIS. By using AHP to calculate the weights and using TOPSIS to determine the best alternative, accurate results can be obtained, as it combines the strengths of the two methodologies. In terms of time and complexity also this hybrid methodology doesn’t involve a high level of complexity as in ANP and also with regard to the time factor, although the calculation of weights may require some time, using TOPSIS the best alternative can be determined relatively fast.Methodology: To validate and verify the quality and to ensure that the system worked as intended, several testing strategies such as User Acceptance testing and Accuracy testing was used. The samples used for these testing methods were the staff of the insurance department in company X.Results: The results of the user acceptance testing showed an over 70% satisfaction with the system. The system had been greatly improved in terms of the time taken as well as the efficiency and accuracy of the decision. Two cases were taken for the accuracy testing and in both cases the manual calculation and system calculation matched except for slight differences to the decimal point. However the overall results were the same. This showed that the model worked successfully in determining the best insurance tender.Conclusion: AHP-TOPSIS could be combined to form a more effective model that combines the strengths of each model to reduce its limitations in order to select the best insurance tender. By using this model the throughput efficiency of the evaluation process was increased to 70% and the time taken to complete the overall process was reduced to at least a month.