Customization of health insurance premiums using machine learning and explainable AI
This study presents an analysis of health insurance premiums across various customer segments. Specifically, it aims to identify the factors influencing the pricing of health insurance premiums, vis a vis their impact on different customer segments. Using a dataset from consumer surveys, coupled wit...
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | International Journal of Information Management Data Insights |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096825000102 |
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| _version_ | 1825199258252345344 |
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| author | Manohar Kapse Vinod Sharma Rutuj Vidhale Varun Vellanki |
| author_facet | Manohar Kapse Vinod Sharma Rutuj Vidhale Varun Vellanki |
| author_sort | Manohar Kapse |
| collection | DOAJ |
| description | This study presents an analysis of health insurance premiums across various customer segments. Specifically, it aims to identify the factors influencing the pricing of health insurance premiums, vis a vis their impact on different customer segments. Using a dataset from consumer surveys, coupled with multiple Machine Learning models, the study analyzed and predicted features of importance for premiums paid across various age groups, gender, health conditions, policy duration, and the number of members included in the policy. Finally, the explainable AI was used to predict the weightage of each variable in determining the price of the insurance policy for the individuals. The findings provide crucial insights into the factors such as demographic factors and lifestyle that effectively influence the pricing of health insurance premiums vis a vis their impact on various customer segments. The results of this study will assist prospective buyers and decision-makers in choosing the best health insurance plans. |
| format | Article |
| id | doaj-art-608aa3b0241a42809c89d2629a32bcc6 |
| institution | Kabale University |
| issn | 2667-0968 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Information Management Data Insights |
| spelling | doaj-art-608aa3b0241a42809c89d2629a32bcc62025-02-08T05:01:35ZengElsevierInternational Journal of Information Management Data Insights2667-09682025-06-0151100328Customization of health insurance premiums using machine learning and explainable AIManohar Kapse0Vinod Sharma1Rutuj Vidhale2Varun Vellanki3Jaipuria Institute of Management Indore, India; Corresponding author.Symbiosis Centre for Management and Human Resource Development, Symbiosis International (Deemed University), Pune, IndiaSymbiosis Centre for Management and Human Resource Development, Symbiosis International (Deemed University), Pune, IndiaSymbiosis Centre for Management and Human Resource Development, Symbiosis International (Deemed University), Pune, IndiaThis study presents an analysis of health insurance premiums across various customer segments. Specifically, it aims to identify the factors influencing the pricing of health insurance premiums, vis a vis their impact on different customer segments. Using a dataset from consumer surveys, coupled with multiple Machine Learning models, the study analyzed and predicted features of importance for premiums paid across various age groups, gender, health conditions, policy duration, and the number of members included in the policy. Finally, the explainable AI was used to predict the weightage of each variable in determining the price of the insurance policy for the individuals. The findings provide crucial insights into the factors such as demographic factors and lifestyle that effectively influence the pricing of health insurance premiums vis a vis their impact on various customer segments. The results of this study will assist prospective buyers and decision-makers in choosing the best health insurance plans.http://www.sciencedirect.com/science/article/pii/S2667096825000102Premium predictionPredictive modelingMachine learningHealth insuranceExplainable AIXG boost |
| spellingShingle | Manohar Kapse Vinod Sharma Rutuj Vidhale Varun Vellanki Customization of health insurance premiums using machine learning and explainable AI International Journal of Information Management Data Insights Premium prediction Predictive modeling Machine learning Health insurance Explainable AI XG boost |
| title | Customization of health insurance premiums using machine learning and explainable AI |
| title_full | Customization of health insurance premiums using machine learning and explainable AI |
| title_fullStr | Customization of health insurance premiums using machine learning and explainable AI |
| title_full_unstemmed | Customization of health insurance premiums using machine learning and explainable AI |
| title_short | Customization of health insurance premiums using machine learning and explainable AI |
| title_sort | customization of health insurance premiums using machine learning and explainable ai |
| topic | Premium prediction Predictive modeling Machine learning Health insurance Explainable AI XG boost |
| url | http://www.sciencedirect.com/science/article/pii/S2667096825000102 |
| work_keys_str_mv | AT manoharkapse customizationofhealthinsurancepremiumsusingmachinelearningandexplainableai AT vinodsharma customizationofhealthinsurancepremiumsusingmachinelearningandexplainableai AT rutujvidhale customizationofhealthinsurancepremiumsusingmachinelearningandexplainableai AT varunvellanki customizationofhealthinsurancepremiumsusingmachinelearningandexplainableai |