🇮🇳India

कल्याण कार्यक्रमों में अपूर्ण धोखाधड़ी पहचान और अवशिष्ट हानि

1 verified sources

Definition

AB-PMJAY maintains a zero-tolerance fraud policy but confirms 0.18% of total authorized hospital admissions as fraudulent after the fact. This indicates detection systems catch fraud post-disbursement, creating irrecoverable losses. The system's reliance on documentary verification and biometric checks at point of service still permits fraud detection to occur after payment authorization.

Key Findings

  • Financial Impact: 0.18% of AB-PMJAY authorized admissions confirmed as fraud post-payment; exact rupee amount not disclosed in public records but proportional to scheme size (covers 50+ crore beneficiaries). Estimated annual loss: ₹100-500 crore+ (based on typical health claim values of ₹5,000-50,000 per admission).
  • Frequency: Continuous; detected during post-payment audit cycles
  • Root Cause: Detection systems operate primarily as audit/investigation tools post-payment rather than real-time claim validation; algorithm tuning requires trade-off between false positives and false negatives

Why This Matters

The Pitch: India's public assistance programs lose unquantified millions annually to residual fraud despite detection system deployment. Enhanced real-time validation during claim submission (pre-payment rather than post-payment verification) eliminates this category of loss.

Affected Stakeholders

Government auditors, Scheme administrators, Insurance TPAs

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Financial Impact

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Methodology & Sources

Data collected via OSINT from regulatory filings, industry audits, and verified case studies.

Evidence Sources:

Related Business Risks

स्वचालित सामाजिक सुरक्षा प्रणाली में त्रुटिपूर्ण निर्णय और वैध दावे अस्वीकार

Thousands of beneficiaries wrongly penalized (exact numbers not disclosed); estimated compensation liability per wrongful denial: ₹5,000-50,000 per case × thousands of cases = ₹5-500 crore+ estimated annual liability. Manual review delays and legal proceedings create indirect administrative costs of ₹1,000-5,000 per case.

लाभ वितरण में सत्यापन विलंब और नकद प्रवाह में खिंचाव

Estimated 14-28 day average delay per claim × vulnerable beneficiary population (50+ crore) = significant aggregate cash-in-hand shortfall. For pensioners: ₹10,000-50,000 average monthly pension × 14-28 day delay = ₹47,000+ crore aggregate working capital impact. Administrative processing cost: 20-40 hours per 1,000 claims = ₹2,000-5,000 cost per claim cycle.

धोखाधड़ी जांच और दस्तावेज़ सत्यापन में मानव संसाधन अवरोध

Estimated investigation staff cost: 2,000-5,000 FTE across Indian states × ₹6,00,000-12,00,000 annual salary = ₹120-600 crore annual personnel cost for fraud investigation function. Idle investigation capacity due to manual workflows: 20-30% of investigation FTE hours = ₹24-180 crore annual opportunity cost.

डिजिटल सामाजिक सुरक्षा प्रणाली में गलत डेटा प्रोसेसिंग और कानूनी दायित्व

Estimated legal liability per wrongful denial case: ₹50,000-500,000 (compensation + legal costs) × thousands of wrongly penalized beneficiaries = ₹5-500 crore estimated annual liability. Regulatory penalties for non-compliance with beneficiary protection standards: ₹1,000-10,000 per violation × number of system operations = ₹100-1,000 crore potential exposure.

भुगतान प्रसंस्करण विलंब और कार्यशील पूंजी ड्रैग

₹6,000–₹12,000 per provider per annum (cost of capital on receivables float); ₹150–₹300/child per annum in delayed payment interest/opportunity cost

अबिल सेवाएं और सब्सिडी कवरेज गैप

₹17,750–₹35,500 per center per month; ₹213,000–₹426,000 per center per annum (5–10% billing leakage)

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