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Auto Insurance Customer Prediction

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dc.contributor.author Jayan, Eksara
dc.date.accessioned 2023-01-18T04:40:03Z
dc.date.available 2023-01-18T04:40:03Z
dc.date.issued 2022
dc.identifier.citation Jayan, Eksara (2022) Auto Insurance Customer Prediction. MSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20200088
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1446
dc.description.abstract "This research paper discusses the use of machine learning in the insurance industry. Literary review was done on customer churning, insurance sales forecast and future customer prediction using Machine Learning. By selecting future customer prediction as the topic, the paper had discuss more on using Supervised learning techniques and visualization techniques to come with good insights. The first chapter takes reader through the introduction. Introduction includes a go through about the background for the project and what the project is about. It discusses the business environment, the needs, the wants, the trends and much more. This section little by little elaborate into the domain of the study which is insurance. Then the use of technology in the field. Why this research needs to be conducted is discussed with the problem statement. This depicts each problem that the segment or the business domain is facing which needs a solution. Then the study talks about the research questions. This is the wide range of questions to which this research provides the solution. This includes multiple questions ranging from predicting the future customers. After that the research introduction talks about the aims and goals of the research from which the reader can get a good holistically understanding of the aim and the intent of the writer. All of these details are then further elaborated in the upcoming chapters of the study. Then a small briefing on the technology stack used for the study is given. Techniques, models and tools are discussed here. Also, there can be new additions to the technologies discussed which are out of the scope of this document when scaling the product. " en_US
dc.language.iso en en_US
dc.subject Insurance en_US
dc.title Auto Insurance Customer Prediction en_US
dc.type Thesis en_US


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