Business News | Mule Networks Biggest Fraud Threat for Indian Firms: India Fraud Report 2026
Get latest articles and stories on Business at LatestLY. A key finding from the report highlights the growing dominance of mule networks, with 48 per cent of Indian enterprises identifying them as the most difficult fraud threat to detect and control, ahead of phishing, synthetic identities, account takeover, and social engineering (which came second with 33 per cent). Designed to appear legitimate at every touchpoint, these networks distribute funds across large clusters of connected accounts, making them difficult to detect without cross-platform visibility.
Bengaluru (Karnataka) [India], March 27 (ANI): Bureau, an AI-powered unified risk decisioning platform, has released the India Fraud Report 2026, revealing a sharp shift in how fraud is being executed across India's digital economy.
A key finding from the report highlights the growing dominance of mule networks, with 48 per cent of Indian enterprises identifying them as the most difficult fraud threat to detect and control, ahead of phishing, synthetic identities, account takeover, and social engineering (which came second with 33 per cent).
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Designed to appear legitimate at every touchpoint, these networks distribute funds across large clusters of connected accounts, making them difficult to detect without cross-platform visibility.
With fraud losses surging to Rs 36,014 crore in the banking sector, as per the RBI Annual Report 2024 - 25, the Bureau Fraud Report finds that fraud operations are becoming faster, more organised, and increasingly industrialised, leveraging real-time payments, instant onboarding, and interconnected digital platforms to scale attacks.
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The report also reveals a growing operational challenge for risk teams. 58 per cent of organisations identified false positives as their primary risk, indicating that risk teams are spending a significant portion of their time investigating legitimate users while sophisticated threats slip through undetected.
In 2025, identity became the main entry point for fraud in India's digital economy, with fragmented and reusable identity data being misused at scale. As a result, organisations saw decision error as the biggest risk, as it is becoming harder to tell genuine users apart from fraudsters.
This is made worse by advanced AI tools that can create highly realistic fake images, documents, and even identities, often slipping past traditional verification systems. At the same time, fraud has become more accessible and scalable. With the rise of Fraud-as-a-Service, toolkits available on the dark web now offer plug-and-play access to stolen personal data, malicious APIs, and ready-to-use scam scripts, lowering the barrier to entry and enabling even low-skill actors to execute complex fraud operations.
Compliance practices are also contributing to the exposure gap. Only 20 per cent of organisations treat compliance as a strategic tool that strengthens detection and informs proactive risk investment.
In contrast, 50 per cent continue to view it as an obligation or protective shield against retaliatory measures or reputational damage. In an age where fraud tactics are constantly evolving and exploiting even minor vulnerabilities, organisations without built-in, adaptive anti-fraud systems leave their customers, especially first-time digital users, highly exposed.
Commenting on the findings, Sandesh GS, CTO, Bureau, said, "What gives us a real edge today is the network effect at scale. When you analyse identities and devices across ecosystems, you begin to see how the same fraud patterns, tools and behaviours repeat across platforms and even industries. Fraudsters reuse what works, which makes it important to look beyond isolated data points."
Bureau's platform intelligence illustrates the scale of this challenge. The company identified and disrupted multiple organised fraud operations, including one network involving more than 2,700 linked users operating across platforms, a pattern that becomes visible only when identity, device, and behavioural signals are analysed together rather than in isolation.
Fraud now moves across networks and enterprises, making isolated controls ineffective. To keep pace, risk teams need detection systems that combine device, behavioural, and contextual intelligence across platforms. Graph analysis helps map relationships between identities, devices, and transactions, allowing organisations to uncover coordinated fraud activity that would otherwise appear legitimate in isolation. (ANI)
(The above story is verified and authored by ANI staff, ANI is South Asia's leading multimedia news agency with over 100 bureaus in India, South Asia and across the globe. ANI brings the latest news on Politics and Current Affairs in India & around the World, Sports, Health, Fitness, Entertainment, & News. The views appearing in the above post do not reflect the opinions of LatestLY)