June 2026 Summaries

By December 2026, every EU member state must provide a certified European Digital Identity (EUDI) Wallet to its citizens and residents under eIDAS 2.0, which is a major update to the EU's digital identity legislation aiming for widespread adoption by 2030. The EUDI Wallet acts as a secure digital counterpart to physical wallets, allowing users to store and share verified credentials like identity documents and professional licenses with a focus on privacy and data minimization. This regulation requires technical teams to adapt applications to ensure compliance, impacting sectors such as finance through changes to identity verification, onboarding, and strong customer authentication processes. The wallet's selective disclosure feature aligns with GDPR principles by enabling users to share only necessary information, while device intelligence can enhance security by maintaining continuity across sessions. Compliance involves auditing identity workflows, aligning technical infrastructure, and partnering with Qualified Trust Service Providers, with the regulation also applying to non-EU businesses that serve European customers in regulated sectors.

Fraud prevention in online retail is evolving beyond traditional measures like passwords and CAPTCHAs, which are increasingly ineffective against sophisticated, AI-driven threats. The shift towards omnichannel shopping has expanded the attack surface, with loyalty programs and Buy Online, Pick Up In Store (BOPIS) models becoming prime targets for fraudsters. Account takeovers, payment fraud, and chargebacks are significant concerns, with global e-commerce fraud losses projected to nearly double by 2029. Traditional security measures often increase user friction, negatively impacting customer experience and conversion rates. A more effective approach involves leveraging device-level intelligence to accurately identify and flag suspicious activity without disrupting legitimate users, thus optimizing fraud detection and reducing associated costs. This strategy can improve the efficiency of fraud teams and enhance customer retention by minimizing false positives and unnecessary security challenges.

Automated traffic is increasingly dominated by AI agents performing various tasks, necessitating enhanced fraud detection capabilities to differentiate between legitimate activities and threats. Recent updates include AI Agent Detection and AI Assistant Detection, which identify AI-driven browser sessions and verify requests from AI assistants like ChatGPT and Claude, respectively. New Smart Signals, such as Rare Device Detection and iOS Simulator Detection, provide more precise risk assessments by identifying unusual device configurations and non-genuine devices. Additionally, the Suspect Score feature now offers AI-driven recommendations based on user-labeled fraud data, while the Fingerprint MCP Server allows for quick querying of device intelligence data to streamline fraud analysis and prevention. Developers can integrate AI coding environments to expedite the development of fraud-prevention features, with support available for demonstrations and early access.

Fingerprint has enhanced its AI Agent Detection with a beta feature called AI Assistant Detection, aimed at identifying and authenticating HTTP-level traffic from AI assistants such as OpenAI's ChatGPT, Google's Gemini, and Anthropic's Claude. This feature addresses the challenge of distinguishing legitimate AI assistant requests from malicious imitations that exploit user-agent strings to bypass bot defenses, which traditional methods cannot verify effectively. The solution operates at the edge, evaluating multiple signals like IPs and reverse DNS to provide a confidence verdict on incoming requests, allowing users to tailor their site’s response to actual assistant traffic without altering application code. This dual-layered approach, combining AI Agent Detection for browser-driven sessions and AI Assistant Detection for direct HTTP requests, offers a comprehensive overview of AI traffic, enabling businesses to optimize content visibility, improve analytics, and prevent fraud while accommodating legitimate non-human traffic. As the web evolves to include a significant share of non-human interactions, Fingerprint's solution facilitates a balanced approach to managing AI-driven traffic without compromising security or discovery opportunities.