Survey of 300 financial services leaders reveals how agentic AI is outpacing legacy security defenses
CHICAGO--(BUSINESS WIRE)--#ai--Fingerprint, the industry leader in device intelligence, today released its 2026 State of AI Traffic in Financial Services report. The survey polled 300 U.S. financial services leaders, revealing a gap between confidence in detection and the reality of mitigation at scale. 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.
Fingerprint’s 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.
- Only 45% detect spoofed AI traffic and successfully mitigate it in real time.
- Just 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.
Traditional Security Tools Can’t Keep Up
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 only 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. Only 43% 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 rapid rise of AI agents and headless traffic has shifted how financial service organizations operate. Companies designed their legacy defenses for humans using web browsers and basic bots, but the AI-native web increasingly operates directly over HTTP," said Dan Pinto, CEO and co-founder of Fingerprint. "Financial institutions built their defenses for a web where humans opened browsers that executed JavaScript. Many AI agents circumvent this model, so the challenge now is knowing whether automated traffic is actually what it claims to be."
A Growing Compliance and Business Risk
The gap in verifying automated traffic is more than just a fraud issue. It is also a massive compliance risk. 70% of financial organizations agree they cannot guarantee consumer data privacy compliance if their security stack cannot verify automated traffic at the HTTP level.
Despite these threats, organizations are wary of blunt-force security measures. 40% of respondents primarily fear that if they inadvertently block a legitimate consumer AI assistant, their users could switch to a competitor that allows AI tools.
Organizations are thus starting to pivot their security investments. 32% of respondents rank real-time IP-range and DNS verification for AI provider networks as the top priority for next year. Additionally, 46% said upgrading their application security to support "edge-deployed, no-JavaScript required" identification is a critical or high-priority project already planned or funded for the next 6 to 12 months.
To read the full findings and learn how financial institutions are adapting to the browserless web, download the 2026 State of AI Traffic in Financial Services report.
Report Methodology
Censuswide conducted this research between June and August 2026 by surveying 300 U.S. financial services leaders (CISOs, Chief Risk Officers, CTOs, VPs and Directors of Fraud Strategy, and more) across Retail Banking, Fintech, Wealth Management, and Investment Banking. Censuswide abides by and employs members of the Market Research Society and follows the MRS code of conduct and ESOMAR principles. Censuswide is also a member of the British Polling Council.
About Fingerprint
Fingerprint detects the intent of human and agentic visitors. Our device intelligence platform identifies over 1 billion unique devices every month and processes hundreds of signals to help fraud teams distinguish trusted visitors from bad actors at speed and scale. Over 6,000 companies, including innovators like Plaid, Booking.com, Dropbox, Trustpilot, and Checkout.com, use Fingerprint every day to recognize high-risk activity in real time, prevent fraud attacks, and deliver frictionless user experiences. Learn more at fingerprint.com.
Frequently Asked Questions (FAQ)
Why are legacy security tools failing to detect threats in modern web traffic?
Legacy fraud detection tools were built for human traffic interacting through web browsers, but today's AI assistants and autonomous tools operate without a browser. Because 61% of financial organizations still rely on client-side JavaScript tags or native SDKs for automated traffic and bot detection, and AI agents bypass JavaScript entirely, organizations are left with major security blind spots.
Are financial institutions catching malicious AI traffic?
While 95% of organizations are confident they can spot genuine AI assistants, only 45% said they detected spoofed AI traffic bypassing perimeter defenses and successfully mitigated the incident in real time. Furthermore, 79% of financial organizations have detected a malicious bot or scraper bypassing a perimeter defense by spoofing a legit AI assistant or search crawler identity.
Why don't financial organizations just block all automated traffic?
Blocking all automation is no longer a viable business strategy. 40% primarily fear the business risk of severe customer friction and churn if they inadvertently block a legit consumer AI assistant. Customers want to use these tools, and if one institution blocks them, they could simply migrate to a competitor that allows them.
What are the main risks of failing to verify browserless traffic?
Aside from scraping and fraud, it is a massive compliance and risk exposure liability. 70% of financial organizations state they cannot guarantee consumer data privacy compliance if their security stack cannot verify automated traffic at the HTTP level.
How is the financial industry upgrading its defenses?
Detection is moving off the client-side and onto the CDN edge, middleware, or backend. 46% of financial organizations are making it a critical priority to upgrade to "edge-deployed, no-JavaScript required" identification for automated and AI-native web traffic in their next budget cycle. Additionally, 32% rank real-time IP-range and DNS verification for AI provider networks as their top priority for the next year.
Contacts
Media Contact
Treble
Katie Pesek
fingerprint@treblepr.com
