A new fraud research report by Experian, conducted in collaboration with Forrester Consulting, has highlighted a growing mismatch between the sophistication of fraud attacks and the preparedness of businesses to counter them. 

The study, based on a survey of nearly 1,000 senior fraud leaders across nine countries including India, points to an increasingly complex threat landscape driven by organised global networks and emerging technologies. 

Surge in sector-specific fraud trends 

The report notes a sharp rise in social engineering and identity theft in financial services and telecom sectors while e-commerce continues to face growing incidents of friendly fraud and refund abuse. Identity verification has emerged as the most targeted vulnerability across industries. 

Defences lag as fraud becomes more scalable 

Fraud is becoming faster, cheaper, and more scalable, aided by transnational networks and generative AI tools. In India, 69% of organisations believe their fraud prevention technologies require significant upgrades. However, many firms remain delayed by prolonged “build vs. buy” decisions, slowing adoption of modern solutions. 

At the same time, 83% of respondents expressed interest in passive fraud detection methods such as behavioural and device intelligence to reduce customer friction, while 64% are planning to adopt integrated frameworks combining fraud prevention with credit risk assessment. 

Machine learning (ML) is increasingly becoming central to fraud detection strategies. The report found that 54% of ML users have recorded measurable improvements in detection accuracy, while 65% of senior decision-makers said ML enables better prioritisation of cases for manual review. 

Real-time detection was cited by 55% of respondents as ML’s biggest advantage, along with its ability to continuously retrain on new data. Notably, half of the respondents said ML can detect fraud patterns that traditional rule-based systems often miss. 

Collaboration and capability gaps remain 

Despite rising adoption, 76% of Indian businesses acknowledged a lack of in-house expertise to build or manage ML-based fraud systems. Nevertheless, 74% plan to integrate ML-driven solutions into their workflows. 

The report also underscores the importance of shared intelligence, with 63% of respondents indicating that proven returns from peer networks would accelerate adoption. Experian is enabling such collaboration through secure, API-based fraud intelligence hubs. 

GenAI emerges as a major threat 

Businesses are increasingly alarmed by the rise of generative AI-driven fraud. Around 65% of respondents consider GenAI the most significant fraud threat to date, while 74% reported a noticeable increase in such attacks. 

Further, 69% said their current KYC and identity verification systems are not equipped to detect AI-generated documents, and 57% struggle to determine whether GenAI was used in fraud incidents, making its true impact difficult to quantify.

Commenting on the findings, Manish Jain said fraud has entered a new phase driven by economic volatility, organised networks, and rapid advances in generative AI. He emphasised the need for Indian businesses to adopt machine learning, behavioural analytics, and collaborative fraud intelligence to stay ahead. 

Shail Deep added that increasing investment in fraud technology, over human-led analysis, reflects a shift away from traditional systems. She noted that collaboration and innovation will be critical to building resilience as fraud continues to evolve.