The Title of the dissertation is ‘Do open-source machine learning models save ti

The Title of the dissertation is ‘Do open-source machine learning models save time compared to traditional techniques in detecting insurance claim fraud whilst maintaining the same level of accuracy?’
Please base the project on a UK company too please This project aims to assess the performance of publicly available AI and machine learning (ML) models in identifying potential fraudulent insurance claims. With the insurance industry losing billions annually to fraud, leveraging AI for fraud detection can significantly reduce losses. However, the accuracy, reliability, and ethical implications of using such AI tools remain areas of concern. This essay will seek to cover objectives such as:
– Selecting a suitable AI model (R Studio) and applying it to a publicly available dataset of insurance claims
– Assess the models’ accuracy and precision in identifying fraudulent claims. Compare the performance of different models to determine the most effective approach.
– Discuss the ethical implications of deploying AI in fraud detection, including potential biases in data and algorithms, privacy concerns, and the risk of false positives.
– Analyse the practical aspects of implementing these AI solutions in an actuarial context and how they’ll impact the workforce.
– Based on the findings, provide practical advice for young actuaries on leveraging AI for fraud detection.
This project addresses a critical challenge in the insurance industry and provides insights into the practicality and implications of using AI in actuarial work. By evaluating open-source AI tools, the project can offer valuable guidance to actuaries looking to incorporate AI into their fraud detection strategies, ensuring they do so effectively and ethically.
Please use the following the following resources as well as any other you find that can be helpful
•https://www.sciencedirect.com/science/article/pii/S2666827021000372
• https://onlinelibrary.wiley.com/doi/full/10.1111/jori.12427
• https://www.mdpi.com/2227-9091/11/9/160
• “Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner” by Vijay Kotu and Bala Deshpande
• https://www.wipro.com/analytics/comparative-analysis-of-machine-learning-techniques-for-detectin/
• https://repository.rit.edu/cgi/viewcontent.cgi?article=12510&context=theses
• https://www.cigniti.com/blog/fraud-detection-insurance-claim-process-artificial-intelligence/#:~:text=Insurance%20companies%20can%20use%20AI,better%20early%20fraud%20risk%20detection.
• https://www.insurancebusinessmag.com/us/guides/revealed–the-10-worst-insurance-fraud-cases-of-all-time-433114.aspx
• https://www.businessinsider.com/insurance-fraud-artificial-intelligence-detection-2023-10?r=US&IR=T
Please make the structure for this very thouht over and concise.
If any charts or graphs are required please just let me know or if anything else is needed please let me know