A Comprehensive Review of Linear Regression, Random Forest, XGBoost, and SVR: Integrating Machine Learning and Actuarial Science for Health Insurance Pricing
- Title
- A Comprehensive Review of Linear Regression, Random Forest, XGBoost, and SVR: Integrating Machine Learning and Actuarial Science for Health Insurance Pricing
- Creator
- Agarwal V.; Singh M.; Kumar K.P.
- Description
- Actuarial science and data science are being studied as a fusion using Industry 4.0 technologies such as the Internet of Things, artificial intelligence, big data, and machine learning (ML) algorithms. When analyzing earlier components of actuarial science, it could have been more accurate and quick, but when later stages of AI and ML were integrated, the algorithms weren't up to the standard, and actuaries experienced some accuracy concerns. The company requires actuaries to be precise with analysis to acquire reliable results. As a result of the large amount of data these companies collect, a choice made manually may turn out to be incorrect. We will, therefore, examine alternative models in this article as part of the decision-making process. Once we have chosen the best path of action, we will use our actuarial expertise to evaluate the risk associated with specific charges features. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Lecture Notes in Networks and Systems, Vol-922 LNNS, pp. 355-367.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Actuarial science; Artificial intelligence; Data science; Machine learning; Supervised learning
- Coverage
- Agarwal V., Christ (Deemed to be University), Bangalore, India; Singh M., Christ (Deemed to be University), Bangalore, India; Kumar K.P., Christ (Deemed to be University), Bangalore, India
- Rights
- Restricted Access
- Relation
- ISSN: 23673370; ISBN: 978-981970974-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Agarwal V.; Singh M.; Kumar K.P., “A Comprehensive Review of Linear Regression, Random Forest, XGBoost, and SVR: Integrating Machine Learning and Actuarial Science for Health Insurance Pricing,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19422.