Abstract
As the different countries around the world evolve into a more economical-based and stimulating their economy is the goal. The main purpose of most of these countries is to fight off money launderers and fraudsters for better economic growth. A popular fraud topic in this regard is insurance fraud since it costs the companies and the public billions. Applying data analysis and machine learning are great ways used to address many problems regarding any automated system. To address this problem, first extensive research should be made to check out what has been applied and what the most promising solution using machine learning and data analytics is out there. After learning, then applying and building upon the findings of the research we propose a model that can flag these suspicious fraudulent claims for the insurance companies to help them out in saving money and time and helping them become more efficient in reacting to these fraudulent claims.
Publication Date
Fall 2022
Document Type
Master's Project
Student Type
Graduate
Degree Name
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research (Dubai)
Advisor
Sanjay Modak
Advisor/Committee Member
Ehsan Warriach
Recommended Citation
Alrais, Arif Ismail, "Fraudulent Insurance Claims Detection Using Machine Learning" (2022). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/11376
Campus
RIT Dubai
