Rising Fraud Incidents Drive Demand for Advanced AI/ML Strategies, According to Experian Study

A recent study conducted by Forrester Consulting, commissioned by Experian, a global information services provider, highlights a notable surge in fraudulent activities in India. The study reveals that a substantial 64% of respondents have witnessed an increase in fraud losses over the past year. Moreover, 67% of businesses are grappling with the challenges posed by the swiftly evolving landscape of fraud threats.

The study emphasizes that the future of effective fraud prevention lies in the adoption of artificial intelligence (AI) and machine learning (ML) technologies. These cutting-edge solutions possess the capability to swiftly analyze extensive datasets, identify anomalies, and unveil fraudulent patterns. This proactive approach not only safeguards businesses from substantial losses but also represents a crucial step forward in fortifying the integrity of financial ecosystems.

Key Findings:

1. Financial Services Hit Hard: Year-on-year fraud losses are on the rise for nearly two-thirds (64%) of respondents, with financial services organizations reporting the most significant increase. Factors such as financial pressure on consumers, data breaches, and the accessibility of Generative AI are driving this surge in fraud attacks.

2. Increasing Volume of Fraud Attacks: Synthetic identity attacks, identity theft attacks, and account takeover attacks are on the rise. In the eCommerce sector, friendly fraud attacks, where customers dispute legitimate charges, have seen significant growth.

3. Fraud Prevention Challenges: The biggest challenges limiting businesses' ability to prevent fraud include a lack of device fingerprinting for fraud identification (62%) and an increasing number of referrals causing delays and increased costs (56%).

4. AI/ML: Shaping the Future: Two-thirds (67%) of businesses believe that the future of fraud prevention lies in AI/ML-powered solutions. The main benefits include increased acceptance rates, reduced losses through greater fraud detection accuracy, and a decrease in manual reviews and false positives.

5. Importance of Model Retraining: Continual automatic model retraining is considered crucial by 88% of respondents to stay ahead of evolving fraud threats. Transparent ML models are seen as essential for ethical AI use and future regulatory compliance.

Manish Jain, Country Managing Director, Experian India, states, "As technology advances, the landscape of fraud undergoes shifts, creating new complexities. Addressing this challenge requires a potent solution – Artificial Intelligence (AI). Unlike traditional methods, AI excels in swift adaptation and real-time analysis, actively defending against ever-changing threats."

The study, based on insights gathered from 308 fraud managers across the financial services, telco, and eCommerce sectors in ten countries, can be accessed in full here.