AI-Enabled Fraud Detection and Analytics for India's National Health Insurance Scheme (AB PM-JAY)

Overview

The Ayushman Bharat - Pradhan Mantri Jan Arogya Yojana (AB PM-JAY) fraud detection system is an operational AI and machine learning deployment by India's National Health Authority (NHA) designed to proactively detect, prevent and deter healthcare fraud across the world's largest government-funded health insurance scheme. AB PM-JAY provides cashless secondary and tertiary care hospitalisation coverage of up to INR 5 lakh per family per year to over 55 crore beneficiaries from economically vulnerable households. The fraud analytics system operates within a zero-tolerance framework targeting suspect or non-genuine medical treatment claims, impersonation of beneficiaries, and up-coding of treatment packages and procedures (PIB, 2022; MoHFW, 2025).

The institutional architecture centres on a two-tier structure: the National Anti-Fraud Unit (NAFU) established at the NHA for overall monitoring and implementation of the anti-fraud framework, supported by State Anti-Fraud Units (SAFUs) operating at the state level. NAFU coordinates joint investigations with SAFUs across all participating states and union territories. The NHA has issued comprehensive anti-fraud guidelines that govern the investigation, escalation and sanctioning processes (NHA, 2022; PIB, 2022).

The technology stack deployed by NAFU encompasses 57 distinct technologies and analytical methods. These include rule-based triggers that flag transactions meeting predefined suspicious criteria, machine learning algorithms that identify complex patterns of fraudulent behaviour across large volumes of claims data, fuzzy logic for approximate matching and entity resolution, image classification for verifying medical documentation and patient photographs, and de-duplication algorithms to detect multiple claims filed for the same patient or treatment episode. Together, these technologies enable risk-scoring of individual hospitals and claims, identification of outlier billing patterns, and collusion analytics to detect coordinated fraud networks among providers (IBTimes India, 2025; PIB, 2022).

Transaction data flowing through NHA's IT systems is monitored on a near real-time basis through a dedicated dashboard known as the Risk Assessment, Detection and Analytical Reporting (RADAR) system. This dashboard highlights suspicious cases to investigators, enabling rapid triage. States and union territories have access to real-time dashboards that enhance transparency and accountability in claims processing. Regular monitoring and cleansing of databases, combined with additional data analytic techniques, form part of the ongoing surveillance infrastructure (IBTimes India, 2025; MoHFW, 2025).

The NHA engaged five specialist data analytics firms to develop and deploy the fraud analytics solution: SAS Institute, MFX, Optum, LexisNexis, and GreenOjo. These firms were selected from among 24 applicants following a Request for Empanelment (RFE) process. The engagement of multiple analytics providers reflects the scale and complexity of the fraud detection challenge across millions of claims (Medibulletin, 2020; NHA, 2025 RFE).

Aadhaar-based biometric verification of beneficiaries at the time of hospital admission and discharge has been mandated at all private hospitals empanelled under the scheme. This biometric layer serves as a deterrent against impersonation fraud and ensures that the person receiving treatment matches the enrolled beneficiary. All claims additionally require mandatory supporting documentation and on-bed patient photographs before authorisation can proceed (PIB, 2022).

The human oversight model follows a human-in-the-loop (HITL) approach. Algorithmic flags and risk scores generated by the AI systems do not automatically trigger sanctions. Instead, flagged cases are routed through desk audits conducted by medical professionals and, where warranted, field investigations and surprise inspections carried out by State Health Agencies. Only after this human review process are penalties, suspensions, or de-empanelment actions taken against hospitals found to have engaged in fraud or abuse (NHA, 2022; MoHFW, 2025).

The enforcement outcomes demonstrate the system's operational scale and impact. As of December 2024, NAFU had processed 6.66 crore claims, identifying 2.7 lakh claims from private hospitals worth INR 562.4 crore as non-admissible on account of abuse, misuse, or incorrect entries. A total of 3,42,988 fraud cases were detected across the scheme. In terms of sanctions, 3,167 hospitals were found guilty of irregularities or violations, 1,114 hospitals were de-empanelled from the scheme entirely, 549 hospitals were suspended, and INR 122 crore in penalties were levied on 1,504 errant hospitals. Over 3 lakh Ayushman beneficiary cards were also disabled where fraud was confirmed. Earlier reporting indicated INR 9.5 crore recovered through the AI/ML-based anti-fraud initiative specifically (MoHFW, 2025; IBTimes India, 2025; GS SCORE, 2022).

The system has been operational since approximately 2020, evolving from an initial rule-based approach to incorporate increasingly sophisticated ML algorithms and the engagement of external analytics firms. Approximately 0.18 per cent of total authorised hospital admissions have been confirmed as fraudulent since inception, though the broader screening identifies a significantly larger pool of suspicious transactions for human review (PIB, 2022; IBTimes India, 2025).

Key challenges include the scale of the programme across India's federated health system with varying state-level capacity, the need for continuous model retraining as fraud patterns evolve, and ensuring that false positive flags do not unduly burden legitimate healthcare providers or delay patient access to covered treatments. The procurement of analytics services through competitive RFE processes suggests ongoing evolution of the technology platform rather than a single settled deployment.

Classification

Programme Details

India's national publicly funded health insurance scheme providing cashless secondary and tertiary care hospitalisation coverage of up to INR 5 lakh per family per year to over 55 crore beneficiaries from economically vulnerable households. Administered by the National Health Authority (NHA) under the Ministry of Health and Family Welfare.

Implementation Details

Risk & Oversight

Deployment & Outcomes

Sources

1. SRC-003-IND-006 IBTimes India (2025) 'Government Detects Rs 562.4 Crore in Fake AB-PMJAY Claims, Implements AI-Based Monitoring to Curb Fraud', International Business Times India, [online]. Available at: https://www.ibtimes.co.in/government-detects-rs-562-4-crore-fake-ab-pmjay-claims-implements-ai-based-monitoring-curb-fraud-879401 (Accessed: 24 March 2026).
   https://www.ibtimes.co.in/government-detects-rs-562-4-crore-fake-ab-pmjay-claims-implements-ai-based-monitoring-curb-fraud-879401
2. SRC-004-IND-006 Medibulletin (2020) '5 analytical firms look for fraud in Ayushman Bharat PMJAY', Medibulletin, [online]. Available at: https://medibulletin.com/5-analytical-firms-look-for-fraud-in-ayushman-bharat-pmjay/ (Accessed: 24 March 2026).
   https://medibulletin.com/5-analytical-firms-look-for-fraud-in-ayushman-bharat-pmjay/
3. SRC-002-IND-006 Ministry of Health and Family Welfare (2025) 'Update on Strengthening of PM-JAY Implementation' (Rajya Sabha written reply, 19 August). New Delhi: MoHFW/PIB. Available at: https://www.mohfw.gov.in/?q=en/press-info/9166 (Accessed: 31 October 2025).
   https://www.mohfw.gov.in/?q=en/press-info/9166
4. SRC-006-IND-006 National Health Authority (2024) Anti-Fraud Framework Practitioners' Guidebook: Ayushman Bharat Pradhan Mantri Jan Arogya Yojana. New Delhi: NHA. Available at: https://cdnbbsr.s3waas.gov.in/s3169779d3852b32ce8b1a1724dbf5217d/uploads/2024/09/20240924831436164.pdf (Accessed: 24 March 2026).
   https://cdnbbsr.s3waas.gov.in/s3169779d3852b32ce8b1a1724dbf5217d/uploads/2024/09/20240924831436164.pdf
5. SRC-001-IND-006 Press Information Bureau (2022) 'Anti-fraud system for India's National Health Insurance Scheme (AB-PMJAY)'. New Delhi: PIB, Ministry of Health and Family Welfare, 2 August. Available at: https://pib.gov.in/PressReleseDetailm.aspx?PRID=1847423 (Accessed: 31 October 2025).
   https://pib.gov.in/PressReleseDetailm.aspx?PRID=1847423
6. SRC-005-IND-006 Press Information Bureau (2023) 'Use of AI for checking frauds under AB-PMJAY' (Rajya Sabha written reply, 8 August). New Delhi: PIB, Ministry of Health and Family Welfare. Available at: https://www.pib.gov.in/PressReleasePage.aspx?PRID=1946706 (Accessed: 24 March 2026).
   https://www.pib.gov.in/PressReleasePage.aspx?PRID=1946706