48% Enterprises Flag Mule Networks as Top Fraud Threat: Report

Digital fraud in India is becoming faster, more organised and increasingly industrialised, with attackers exploiting real-time payments, instant onboarding and interconnected platforms to scale operations. Multiple accounts and evading detection across systems, according to Bureau’s India Fraud Report 2026.

The report also reveals a growing operational challenge for risk teams. 58% 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% of organisations treat compliance as a strategic tool that strengthens detection and informs proactive risk investment.

In contrast, 50% 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.

“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.

"By building contextual intelligence, we can identify signals that should not logically repeat, such as the same identifiers appearing across different systems, and flag risks in real time. This is critical because fraud today operates as an interconnected network, not in silos,” Sandesh GS, CTO, Bureau, said.