Six key online fraud trends to watch in 2026

Online crime is evolving at an alarming pace. This article explores global fraud trends, the risks posed by emerging technologies, and the opportunities for businesses to strengthen their defenses.

As fraudsters become more sophisticated, businesses and consumers face increasingly complex threats. From impersonation fraud to emulator and injection attacks, the landscape of online fraud is constantly shifting. Drawing on insights from the 2026 Identity Fraud Report, we project the following fraud trends to dominate in 2026 and provide actionable strategies to combat them.

1. Impersonation fraud: The dominant threat

Impersonation fraud accounted for over 85% of all fraud attacks in 2025, making it the most prevalent form of online fraud. This method involves using stolen or falsified identity information to pose as someone else, often with counterfeit documents.

Despite its dominance, impersonation fraud has grown significantly more sophisticated in 2025, with fraudsters increasingly leveraging AI-generated deepfakes, synthetic identities, and document manipulation techniques to bypass traditional verification methods. This evolution—from high-volume, low-sophistication attacks to targeted, technologically advanced schemes—underscores the critical need for businesses to adopt advanced identity verification systems incorporating facial biometrics, behavioral analytics, and AI-powered document validation to detect and prevent these emerging threats.

2. Adversary-in-the-Middle (AiTM) attacks: A declining but persistent risk

Both physical and digital AiTM attacks saw significant declines in 2025, with physical attacks dropping by 34% and digital attacks by 66%. However, these attacks remain a concern due to their complexity. Fraudsters increasingly deploy ready-made phishing kits that intercept login credentials and session cookies in real time, allowing them to bypass traditional multi-factor authentication (MFA) by relaying user interactions to legitimate sites. These attacks often leverage AI-generated phishing emails with flawless grammar and formatting, making them harder to detect.

 To counter this, businesses must move beyond conventional MFA methods, which can be circumvented through session token capture or MFA fatigue attacks. Instead, they should adopt phishing-resistant MFA solutions, or certificate-based authentication. These technologies cryptographically bind the authentication process to the legitimate domain, enabling the system to distinguish between real and fake login pages.

3. Document fraud: A mixed trend

While document fraud saw a 13% year-on-year decline globally, it remains a significant issue in regions like North America, where it accounted for 20% of all fraud in 2025. The rise of digital identity wallets adds a new layer of complexity, as businesses must now verify both physical and digital IDs.

Organizations should invest in advanced document verification technologies and conduct regular training to recognize different types of forgery attempts.

4. Emulator and injection attacks: A growing concern

While threats like AiTM are declining, other technical attack vectors are gaining ground—particularly emulator and injection attacks, posing a significant threat to businesses. Emulator attacks involve fraudsters using software to mimic legitimate mobile devices, allowing them to bypass device-based detection systems. These attacks often target financial services, where fraud rates were 30% higher than the global average in 2025.

To effectively prevent injection attacks, organizations should adopt an advanced, AI-powered defense framework that holistically analyzes behavioral patterns, biometric liveness, device authenticity, and temporal dynamics during identity verification. By evaluating the integrity of user interactions across multiple modalities—such as facial movements, document handling, and interaction timing—these systems can detect injected media and distinguish between genuine human activity and automated manipulation. This integrated, intelligence-driven approach ensures robust protection against sophisticated fraud attempts while maintaining seamless user experiences.

5. AI and automation: A double-edged sword

AI is transforming the fraud landscape, enabling both fraudsters and businesses to innovate. Fraudsters use AI to create deepfakes and launch large-scale attacks, while businesses leverage AI-driven algorithms to detect anomalies and reduce false positives.

To stay ahead, businesses must invest in advanced AI-powered anti-fraud solutions and comply with evolving regulations like the EU AI Act, which enforces strict rules for high-risk systems.

6. E-commerce: A prime target

E-commerce platforms experienced a net fraud rate of 19.2% in 2025, nearly five times the global average. The expansion of real-time payment systems has exacerbated the problem, enabling faster, irreversible fund transfers that fraudsters exploit. This sector remains highly vulnerable due to its reliance on lightweight fraud defenses.

 To combat this, businesses must move beyond basic defenses and adopt comprehensive fraud prevention strategies. These include advanced behavioral analytics, device and network fingerprinting, real-time transaction monitoring, and AI-driven risk scoring to detect anomalies indicative of scams.

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Regional fraud trends in 2025

The 2026 Identity Fraud Report highlights notable regional differences in fraud patterns:

• North America: Document fraud accounted for 20% of all fraud, emphasizing the need for advanced verification technologies.
• EU and UK: Impersonation fraud increased by 2.3 times, requiring biometric authentication and multi-factor verification.
• Latin America: Fraud attempts rose by 32%, the highest regional increase, underscoring the need for real-time monitoring and international collaboration.

How businesses can stay ahead

To combat these evolving threats, businesses must adopt a proactive approach to fraud prevention. Key strategies include:

• Facial Biometric Verification: Authenticate users securely and prevent unauthorized access.
• Behavioral Analytics: Detect unusual patterns and mitigate risks in real-time.
• Machine Learning Algorithms: Enhance fraud detection and reduce false positives.
• Fraud Intelligence: Leverage enriched insights and RiskScores for effective decision-making.