Keeping An ‘AI’ On Fraud: How Artificial Intelligence Is Protecting Ayushman Bharat Health Scheme

Published 8 July 2026 · tech

Keeping An ‘AI’ On Fraud: How Artificial Intelligence Is Protecting Ayushman Bharat Health Scheme Written By, Last Updated: July 08, 2026, 19:01 IST The AI-driven

Keeping An ‘AI’ On Fraud: How Artificial Intelligence Is Protecting Ayushman Bharat Health Scheme Written By, Last Updated: July 08, 2026, 19:01 IST The AI-driven fraud analytics framework operates across multiple areas to identify suspicious patterns in real time. Rapid Read Ayushman Bharat The Centre is actively using Artificial Intelligence (AI) and Machine Learning (ML) to prevent, detect, and deter scams under the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY). Managed by the Health Authority (NHA) through its Anti-Fraud Unit (NAFU), these technologies process over 40,000 daily claims to flag systemic leakages, overbilling, and ghost beneficiaries. HOW AI DETECTS AND FLAGS MALPRACTICES The AI-driven fraud analytics framework operates across multiple areas to identify suspicious patterns in real time. Multilingual OCR (Optical Character Recognition) scans low-quality records to cross-check compliance with treatment guidelines. Advanced computer vision analyses Algorithms identify manipulated discharge summaries, forged signatures, and deepfake-generated or altered medical documents. Hospitals are required to submit an on-bed photo of the patient. The system flags cases where a single ICU patient’s photograph is recycled across different claims using altered names to illegally secure higher ICU-tier payouts.

AI flags temporal anomalies—such as claims submitted after a patient’s recorded date of death or before a formal diagnosis. It also tracks geo-tagging data to flag surgeries performed on the same patient simultaneously in different geographic locations. The system also evaluates clinical parameters. For example, it analyzes laboratory datasets to ensure blood reports genuinely justify major procedures like dialysis and flags instances where a minor fever is “upcoded" as a major surgery such as a knee replacement. AI assigns a dynamic risk score to both individual claims and empanelled hospitals, routing suspicious activity to human auditors for further evaluation. STRUCTURAL PILLARS OF THE DIGITAL SECURITY FRAMEWORK To make AI models effective against uniquely localised healthcare challenges, India has integrated specialised infrastructure BODH Platform: A specialised benchmarking platform developed with IIT Kanpur using India-specific clinical datasets to validate AI models for greater local accuracy. AI-Enabled KMS 2.0: An upgraded platform adopted by states including Maharashtra to automatically halt redundant surgeries and trace multi-hospital claim fraud. Aadhaar Biometrics: Mandatory Aadhaar-based biometric verification during patient admission and discharge to prevent impersonation.