Year: 2024
Type: article
Abstract: Artificial Intelligence (AI) and Machine learning (ML) systems are increasingly being used to solve basic day-to-day problems. Chatbots such as Alexa and Siri play a big role in our day-to-day life with our reliance on these systems increasing by the day. The use of AI and ML systems is being increasingly explored, in fraud detection. particularly for the detection of fraud health insurance claims submitted by providers. Recently, several studies have leveraged AI/ML techniques to develop health claims fraud detection models with close to 100% accuracy rates. This paper looks at the limitations of the deep learning-based AI and ML models in the case of health claims fraud detection, and the associated challenges and implications. We then define an integrated AI/ML strategy augmented by human intelligence for comprehensive fraud control to address the challenges and fraud detection using AI/ML responsibly without impacting the patient experience and health outcomes.
Source: Mapana Journal of Sciences
DOI: 10.12723/mjs.sp3.5
Authors: Parul Naib, Sudha Chandrashekar, Shiv D Gupta
Institution: IIHMR University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412142323