1. Vehicle Insurance Policy Document Summarizer, AI Insurance Agent and On-The-Spot Claimer
- Author
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Prasan Yapa, Y. R. Gamaarachchi, H. T. D. Samarasinghe, H. S. S. Dabare, N. A. D. M Herath, and Koliya Pulasinghe
- Subjects
Computer science ,media_common.quotation_subject ,Assertion ,02 engineering and technology ,Recommender system ,Automatic summarization ,Variety (cybernetics) ,Risk analysis (engineering) ,Order (business) ,020204 information systems ,Insurance policy ,Component (UML) ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Function (engineering) ,media_common - Abstract
This paper proposes an automated vehicle insurance policy summarizing application. “Explain to Me” is one such software/tool which enable you to summarize the content of documents regarding vehicle insurance policies by using the NLP, machine learning and deep learning applications. The program targets mainly insurance users and suppliers of insurance services. Due to the increase of vehicle accidents, the vehicle insurance industry has gained more popularity currently. Therefore, different insurance companies have introduced a variety of insurance policies to customers. Vehicle insurance policy documents consist lot of insurance terms that should be read with more attention. As the main objective, this system filters unnecessary data in the particular document, and finalize a summary as the output. As another major component, the application “On the spot claimer” which is never before in Sri Lankan vehicle insurance industry, is another major part of this project that works as suggesting the most relevant insurance claiming that can be claimed by the user after detection of the type of damage through mobile phone camera. Another part of this research project, the function known as the Recommender, which works along with the summarization tool, is a recommendation system with a view of recommending more favorable rules for the assertion of alternatives that exist in the corresponding, equivalent documents of other companies. Finally, in order to interact with custody concerns about how to insure an automobile, CNN, which are based on the extraction of images, are used for the implementation of the ETM system in NLP.
- Published
- 2021