A neural network-based approach in predicting consumers' intentions of purchasing insurance policies
Insurance is a crucial mechanism used to lighten the financial burden as it provides protection against financial losses resulting from unexpected events. Insurers adopt various approaches, such as machine learning, to attract the uninsured. By using machine learning, a company is able to tap into...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Prague University of Economics and Business
2021
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| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/1961/ http://eprints.sunway.edu.my/1961/1/Lai%20Kee%20Huong%20aip_aip-202102-0003.pdf |
| _version_ | 1848802168790843392 |
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| author | Chang, Wen Teng Lai, Kee Huong * |
| author_facet | Chang, Wen Teng Lai, Kee Huong * |
| author_sort | Chang, Wen Teng |
| building | SU Institutional Repository |
| collection | Online Access |
| description | Insurance is a crucial mechanism used to lighten the financial burden as it provides protection against
financial losses resulting from unexpected events. Insurers adopt various approaches, such as machine learning, to attract the uninsured. By using machine learning, a company is able to tap into the wealth of information of its potential customers. The main objective of this study is to apply artificial neural networks (ANNs) to predict the propensity of consumers to purchase an insurance policy by using the dataset from the Computational Intelligence and Learning (CoIL) Challenge 2000. In addition, this study also aims to identify factors that affect the propensity of customers to purchase insurance policies via feature selection. The dataset is pre-processed with feature construction and three feature selection methods, which are the neighbourhood component analysis (NCA), sequential forward selection (SFS) and sequential backward selection (SBS). Sampling techniques are carried out to address the issue of imbalanced class distributions. The results obtained are found to be comparable with the top few
entries of the CoIL Challenge 2000, which shows the efficiency of the proposed model in predicting
consumers’ intention of purchasing insurance policies. |
| first_indexed | 2025-11-14T21:19:04Z |
| format | Article |
| id | sunway-1961 |
| institution | Sunway University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:19:04Z |
| publishDate | 2021 |
| publisher | Prague University of Economics and Business |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | sunway-19612023-04-20T00:27:20Z http://eprints.sunway.edu.my/1961/ A neural network-based approach in predicting consumers' intentions of purchasing insurance policies Chang, Wen Teng Lai, Kee Huong * QA Mathematics Insurance is a crucial mechanism used to lighten the financial burden as it provides protection against financial losses resulting from unexpected events. Insurers adopt various approaches, such as machine learning, to attract the uninsured. By using machine learning, a company is able to tap into the wealth of information of its potential customers. The main objective of this study is to apply artificial neural networks (ANNs) to predict the propensity of consumers to purchase an insurance policy by using the dataset from the Computational Intelligence and Learning (CoIL) Challenge 2000. In addition, this study also aims to identify factors that affect the propensity of customers to purchase insurance policies via feature selection. The dataset is pre-processed with feature construction and three feature selection methods, which are the neighbourhood component analysis (NCA), sequential forward selection (SFS) and sequential backward selection (SBS). Sampling techniques are carried out to address the issue of imbalanced class distributions. The results obtained are found to be comparable with the top few entries of the CoIL Challenge 2000, which shows the efficiency of the proposed model in predicting consumers’ intention of purchasing insurance policies. Prague University of Economics and Business 2021 Article PeerReviewed text en cc_by_nc_4 http://eprints.sunway.edu.my/1961/1/Lai%20Kee%20Huong%20aip_aip-202102-0003.pdf Chang, Wen Teng and Lai, Kee Huong * (2021) A neural network-based approach in predicting consumers' intentions of purchasing insurance policies. Acta Informatica Pragensia, 10 (2). pp. 138-154. ISSN 1805-4951 http://doi.org/10.18267/j.aip.152 doi:10.18267/j.aip.152 |
| spellingShingle | QA Mathematics Chang, Wen Teng Lai, Kee Huong * A neural network-based approach in predicting consumers' intentions of purchasing insurance policies |
| title | A neural network-based approach in predicting consumers' intentions of purchasing insurance policies |
| title_full | A neural network-based approach in predicting consumers' intentions of purchasing insurance policies |
| title_fullStr | A neural network-based approach in predicting consumers' intentions of purchasing insurance policies |
| title_full_unstemmed | A neural network-based approach in predicting consumers' intentions of purchasing insurance policies |
| title_short | A neural network-based approach in predicting consumers' intentions of purchasing insurance policies |
| title_sort | neural network-based approach in predicting consumers' intentions of purchasing insurance policies |
| topic | QA Mathematics |
| url | http://eprints.sunway.edu.my/1961/ http://eprints.sunway.edu.my/1961/ http://eprints.sunway.edu.my/1961/ http://eprints.sunway.edu.my/1961/1/Lai%20Kee%20Huong%20aip_aip-202102-0003.pdf |