Forensic Analytics in Pharmaceutical Fraud Investigations: Lessons from Recent Cases

From Global Perspective

The pharmaceutical industry faces escalating risks from sophisticated fraud schemes, including counterfeit drug distribution, billing irregularities, and corporate malfeasance. Forensic analytics—powered by AI and advanced data analytics—has emerged as a critical defense, enabling organizations to detect anomalies, predict risks, and investigate fraud with unprecedented precision.

The Rising Imperative for Forensic Analytics

Global counterfeit drug trade now exceeds $200 billion annually, with toxic substitutes like fentanyl and leaded paint found in 10% of medications worldwide.¹ Recent enforcement actions reveal that:

• 97% of U.S. seized counterfeit drugs originate from China, India, and Singapore¹
• 45,000+ social media posts promoted illegal online pharmacies in a single two-week period¹
• $150 billion AI healthcare fraud detection market by 2026 reflects growing reliance on predictive tools²

These threats demand proactive measures. For instance, Thermo Fisher’s 2024 acquisition of Microtrace LLC enhanced microanalysis capabilities to identify drug contaminants at granular levels,³ while Agilent Technologies merged forensic software with analytical instruments to automate fraud pattern recognition.³

Key Forensic Analytics Techniques Transforming Pharma

1. AI-Driven Prescription Monitoring

Machine learning models analyze prescribing patterns across geographies, flagging outliers like:

• Clinics billing for 3x the regional average of high-cost biologics
• Providers with sudden spikes in opioid prescriptions without patient volume changes²

Example: A 2024 Kansas unemployment fraud case used risk-scoring algorithms to identify $441M in suspicious claims—a method now adapted to track irregular drug shipments.⁴

2. Predictive Modeling for Supply Chain Risks

AI tools cross-reference:

• Shipping manifests
• Dark web drug listings
• Social media sentiment to predict counterfeit hotspots. NABP reports that 94% of illicit online pharmacies sell non-FDA-approved drugs,¹ often detectable through digital footprint analysis.

3. Real-Time Biometric Authentication

• Voice biometrics verify distributor identities during orders, reducing impersonation risks²
• Blockchain-tracked serialization now authenticates 85% of legitimate drug batches in pilot programs⁵
   

Lessons from Recent Enforcement Actions

1. Case 1: Counterfeit Oncology Drug Ring (2024)
   • AI red flags: Unusual shipping routes from Southeast Asia to rural U.S. clinics
   • Outcome: $120M recovery using geo-analytics and supplier network mapping³
2. Case 2: Insurer-Provider Collusion (2025)
   • Detection: Natural Language Processing (NLP) flagged mismatched clinical notes and billing codes
   • Impact: Prevented $45M in fraudulent claims through automated audit triggers⁵
      

Action Points for Internal Audit & Risk Leaders

1. Adopt Tiered AI Solutions
   • Priority 1: Deploy real-time anomaly detection for high-risk areas (e.g., controlled substances, specialty drugs)
   • Priority 2: Integrate blockchain for end-to-end supply chain transparency
      
2. Collaborate Cross-Functionally
   • Partner with IT to embed forensic tools in enterprise resource planning (ERP) systems
   • Train auditors on interpreting AI-generated risk scores
      
3. Benchmark Against Peers
   • 73% of leading pharma firms now use predictive fraud modeling—laggards face 2.5x higher compliance costs⁵
      
4. Engage Third-Party Experts
   Leverage firms like Ankura for:
   • Fraud analytics platform selection
   • Rapid deployment of National Institute of Standards & Technology (NIST)-aligned forensic frameworks³

The convergence of AI, biometrics, and regulatory tech has redefined pharmaceutical fraud detection. For audit and risk teams, the mandate is clear: transition from reactive audits to predictive, analytics-driven vigilance. As synthetic opioids and cyber-enabled fraud evolve, embedding forensic capabilities into core workflows is not optional—it is existential.

From India Perspective

The pharmaceutical industry in India is grappling with significant challenges related to fraud, particularly concerning counterfeit drugs and substandard medications. As the sector continues to expand, leveraging advanced data analytics and artificial intelligence (AI) has become essential for detecting and investigating fraudulent activities. This article explores how forensic analytics is being utilized in India, drawing lessons from recent cases and providing actionable insights for internal audit heads and risk officers.
 

The Indian Pharmaceutical Landscape: A Growing Concern

India is recognized as the "pharmacy of the world," supplying affordable medicines to over 200 countries. However, the rise of counterfeit drugs poses a serious threat to public health and the industry's reputation. Recent reports indicate that nearly 3,000 drugs failed quality tests in FY24, with 282 classified as spurious.⁶ The Central Drugs Standard Control Organization (CDSCO) has identified numerous instances of counterfeit drugs entering the market, leading to calls for stricter regulations and enforcement.^7,8 In 2024 alone, the Supreme Court issued notices to regulatory bodies concerning the rampant manufacturing and selling of fake pharmaceutical drugs, highlighting the urgent need for comprehensive guidelines and proactive measures.⁷ The Indian Pharmaceutical Alliance (IPA) has emphasized that the lack of enforcement has weakened deterrence against counterfeit operations, allowing these fraudulent products to proliferate.⁸

Forensic Analytics Techniques in India

1. AI-Powered Prescription Monitoring

In India, AI technologies are being deployed to analyze prescription patterns across various regions. This involves identifying anomalies such as:

• Clinics with unusually high prescriptions for specific medications
• Providers who bill for medications without corresponding patient visits

Example: The implementation of AI-driven analytics in monitoring opioid prescriptions has helped authorities identify potential abuse patterns, similar to initiatives seen in other countries.

2. Predictive Modeling for Supply Chain Integrity

Advanced data analytics tools are being utilized to enhance supply chain security by:

• Cross-referencing shipping data with known counterfeit hotspots
• Analyzing social media and online marketplaces for illicit drug sales

The CDSCO's recent initiatives include risk-based inspections of pharmaceutical manufacturers, which have led to significant seizures of counterfeit products.⁶

3. Real-Time Monitoring Systems

The Reserve Bank of India (RBI) has introduced a Central Payment Fraud Information Registry (CPFIR) that employs AI and machine learning to track payment fraud. This system can be adapted for monitoring pharmaceutical transactions, ensuring that suspicious activities are flagged in real-time.

Lessons from Recent Indian Cases

1. Case 1: Counterfeit Drug Operations (2024)
   • Detection Method: AI algorithms flag unusual distribution patterns linked to specific manufacturers.
   • Outcome: Regulatory agencies conducted raids leading to significant seizures of counterfeit drugs worth millions.
      
2. Case 2: Substandard Drug Quality Alerts (2024)
   • Detection Method: CDSCO's alerts regarding "not of standard quality" drugs prompted immediate investigations into manufacturing practices.
   • Impact: Over 600 prosecutions were initiated against non-compliant manufacturers.⁶

Action Points for Internal Audit & Risk Leaders in India

1. Implement Advanced Analytics Solutions
   • Invest in AI-driven tools for real-time monitoring of prescription patterns and supply chain integrity.
      
2. Strengthen Regulatory Compliance Frameworks
   • Collaborate with regulatory bodies like CDSCO to ensure compliance with updated guidelines on drug quality and safety.
      
3. Enhance Training Programs
   • Provide training for auditors on utilizing forensic analytics tools effectively and interpreting data insights.
      
4. Engage in Public Awareness Campaigns
   • Promote awareness about counterfeit drugs among healthcare professionals and consumers to foster a culture of vigilance.
      
5. Leverage Collaborative Networks
   • Work with industry peers and law enforcement agencies to share intelligence on emerging fraud trends and best practices.

As the pharmaceutical industry continues to evolve, Ankura's Forensic Analytics team stands ready to provide expert guidance and cutting-edge solutions to combat fraud. With a proven track record and unparalleled expertise, we empower organizations to proactively safeguard their operations and reputation. Leveraging advanced tools like our Early Warning System (EWS) for real-time anomaly detection and data integrity investigations, we help clients navigate regulatory complexities, mitigate risks, and maintain the highest standards of compliance and integrity.
 

^{[1] https://www.lilly.com/safety/medication-safety/product-protection} 

^{[2] https://www.pindrop.com/article/how-ai-can-improve-healthcare-fraud-protection/} 

^{[3] https://media.market.us/forensic-products-market-news-2024/} 

^{[4] https://www.forvismazars.us/forsights/2022/12/using-data-analytics-to-recover-from-prevent-unemployment-fraud} 

^{[5] https://www.avenga.com/magazine/fraud-detection-in-healthcare-and-the-pharmaceutical-industry/} 

^{[6] https://economictimes.indiatimes.com/industry/healthcare/biotech/pharmaceuticals/nearly-3000-drugs-failed-quality-test-in-fy24-282-were-spurious/articleshow/115981824.cms} 

^{[7] https://www.livelaw.in/top-stories/supreme-court-issues-notice-in-plea-seeking-guidelines-against-manufacturing-and-selling-of-fake-pharma-drugs-276850} 

^{[8] https://economictimes.indiatimes.com/industry/healthcare/biotech/pharmaceuticals/pharma-companies-seek-more-teeth-for-agencies-to-fight-fakes/articleshow/113993063.cms}

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^{© Copyright 2025. The views expressed herein are those of the author(s) and not necessarily the views of Ankura Consulting Group, LLC., its management, its subsidiaries, its affiliates, or its other professionals. Ankura is not a law firm and cannot provide legal advice.}