Thesis Abstract

Abstract
This thesis explores the impact of artificial intelligence (AI) on claim processing within the insurance industry. With the increasing integration of AI technologies in various sectors, the insurance industry has also begun to leverage AI to enhance efficiency and accuracy in claim processing. This study aims to provide a comprehensive analysis of how AI is transforming traditional claim processing practices and the implications of these changes on the industry as a whole. The research begins with an introduction that sets the stage for the study by outlining the background of the insurance industry, the significance of claim processing, and the growing importance of AI technologies. The problem statement highlights the challenges faced by insurance companies in claim processing and the potential benefits of integrating AI solutions. The objectives of the study focus on understanding the impact of AI on claim processing efficiency, accuracy, and customer satisfaction. The literature review in this thesis covers ten key areas related to AI in claim processing, including the evolution of AI in insurance, the benefits and challenges of AI adoption, the role of machine learning and natural language processing in claim processing, and the ethical considerations of AI implementation. Drawing on existing research and industry insights, this chapter provides a comprehensive overview of the current state of AI in claim processing. The research methodology section outlines the approach taken to investigate the impact of AI on claim processing in the insurance industry. This chapter covers the research design, data collection methods, sample selection, data analysis techniques, and ethical considerations. By adopting a mixed-methods approach, this study aims to provide a holistic understanding of how AI is reshaping claim processing practices. The findings of this research are presented in the discussion chapter, where the implications of AI integration on claim processing efficiency, accuracy, and customer satisfaction are analyzed. Key themes that emerge from the data include the potential for AI to streamline claims processing, reduce error rates, improve fraud detection, and enhance customer experience. The discussion also highlights the challenges and limitations associated with AI adoption in claim processing. In the conclusion and summary chapter, the key findings of the study are synthesized, and the implications for the insurance industry are discussed. The study concludes by emphasizing the transformative potential of AI in claim processing and the need for insurance companies to strategically integrate AI technologies to stay competitive in the evolving landscape of the industry. Overall, this thesis contributes to the growing body of knowledge on the impact of AI on claim processing in the insurance industry, providing valuable insights for industry practitioners, policymakers, and researchers. By shedding light on the opportunities and challenges of AI adoption in claim processing, this study aims to inform strategic decision-making and promote further research in this critical area.

Thesis Overview