AI-Driven Fraud Detection and Security Improvements in Doctor Appointment Systems

AI-Driven Fraud Detection and Security Improvements in Doctor Appointment Systems

Rushikesh Sopan Panchal1

Prof. Ramkrishna More College, Pradhikaran, Pune, India.

E-mail: panchalrushi22@gmail.com

Dr. Santosh Jagtap2

Prof. Ramkrishna More College, Pradhikaran, Pune, India.

E-mail: st.jagtap@gmail.com

Abstract:

Healthcare fraud remains a significant global challenge, with annual costs ranging from $68 billion to $300 billion in the U.S. alone, representing 3-10% of healthcare expenditures (SAS, 2024; Markovate, 2024). These fraudulent activities burden insurers, providers, and patients, increasing operational costs and limiting resources for genuine healthcare needs. With the growing adoption of online healthcare services, doctor appointment systems have become increasingly vulnerable to fraud and security breaches. This paper explores the integration of artificial intelligence (AI) techniques, including machine learning and natural language processing, to enhance fraud detection and strengthen system security. A strategic framework leveraging these technologies is proposed to effectively mitigate fraud while ensuring system integrity and maintaining user trust. The findings demonstrate that AI-based approaches can significantly reduce fraudulent activities and enhance the overall security of healthcare booking systems.