Utilizing AI/ML for Real-Time Claims Analysis in Managed Care Systems

Authors: Selvakumar Kalyanasundaram

DOI: https://doi.org/10.37082/IJIRMPS.v14.i2.233072

Short DOI: https://doi.org/

Country: United States

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Abstract: The rapid growth of healthcare data and the increasing complexity of managed care systems have necessitated advanced analytical approaches for efficient claims processing. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies enabling real-time claims analysis, fraud detection, and decision optimization. This paper presents a comprehensive framework for integrating AI/ML into managed care claims processing systems, focusing on real-time analytics, fraud detection, and operational efficiency. The study discusses architectural design, key algorithms, evaluation metrics, and implementation challenges. Experimental insights from literature indicate significant improvements in detection accuracy, processing time, and cost efficiency. The paper concludes with future research directions emphasizing explainability, interoperability, and AI governance. Furthermore, the paper introduces the concept of Autonomous Claims Systems, leveraging agentic AI and workflow orchestration to enable self-learning, self-adapting, and minimally supervised claims processing environments. These systems represent the next evolution in managed care analytics by combining real-time decision intelligence with continuous operational optimization.

Keywords: Artificial Intelligence, Machine Learning, Managed Care, Claims Processing, Fraud Detection, Real-Time Analytics, Healthcare Informatics, Autonomous Systems, Agentic AI, Intelligent Automation

Paper Id: 233072

Published On: 2026-04-28

Published In: Volume 14, Issue 2, March-April 2026

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