Over Half of Financial Service Leaders Miss Spoofed AI Traffic
A report by Fingerprint analyzed the state of artificial intelligence (AI) traffic within financial services organizations. The report found that while most financial institutions (95%) said they’re confident in their ability to distinguish genuine AI assistants from spoofed traffic, four out of five (79%) have detected a malicious bot or scraper bypassing a perimeter defense by spoofing a legitimate AI assistant or search crawler identity.
The research highlights how the rapid transition toward a browserless, AI-native web is straining traditional security tools and creating blind spots against AI agents and assistants. While 97% claim to be prepared for traffic that interacts with systems without opening a traditional browser, over half (53%) admit they rely on significant manual oversight and custom rules to handle it.
Key findings include:
- 79% have detected a malicious bot or scraper bypassing perimeter defenses by spoofing a legitimate AI assistant or search crawler.
- 45% detect spoofed AI traffic and successfully mitigate it in real time.
- 26% have full visibility into automated traffic that bypasses client-side JavaScript detection.
- 61% still rely on client-side JavaScript tags or native SDKs for automated traffic and bot detection.
- 70% say they cannot guarantee consumer data privacy compliance if they cannot verify automated traffic at the HTTP level.
- 95% report an increase in automated traffic interacting with their web properties and APIs over the past 12 months.
Less than half (45%) of financial organizations said they detect spoofed AI traffic bypassing perimeter defenses and successfully mitigate the incident in real time while a quarter (26%) said they have full visibility into automated traffic that completely bypasses client-side JavaScript detection.
Furthermore, three out of five financial organizations (61%) still rely on client-side JavaScript tags or native SDKs for automated traffic and bot detection. As more AI traffic operates without executing client-side JavaScript, this creates visibility gaps that leave organizations at risk of not detecting spoofed AI assistant, agent, or search crawler identities. Forty-three percent said they verify traffic through authorized IP ranges or DNS in real time.
The tools designed for human-driven browser interactions are being outpaced by the browserless web. Because AI assistants and agents interact with websites and APIs through a mix of direct HTTP requests and browser automation, requests that do not execute client-side JavaScript can create blind spots for JS-based detection. Separately, fraudsters can spoof user-agent strings and other headers to impersonate trusted AI tools, bypassing legacy defenses. In the survey, 95% of financial services respondents said the volume of automated traffic interacting with their web properties and APIs had increased over the past 12 months.
The gap in verifying automated traffic is more than just a fraud issue. It is also a massive compliance risk. Seventy percent of financial organizations agree they cannot guarantee consumer data privacy compliance if their security stack cannot verify automated traffic at the HTTP level.
Looking for a reprint of this article?
From high-res PDFs to custom plaques, order your copy today!
