AI is rapidly expanding cyber risk across European banking vendor ecosystems. From deepfake fraud to third-party vulnerabilities, firms face growing threats that outpace governance. As regulation tightens and attack surfaces widen, banks must rethink vend
Artificial intelligence is reshaping
cyber risk across Europe’s financial services sector, but not always in ways
banks can control.
As institutions accelerate adoption,
the attack surface is expanding rapidly across third-party and vendor
ecosystems, exposing new vulnerabilities that traditional risk frameworks
struggle to contain.
Recent industry data shows the scale
of the challenge. A growing number of UK businesses are being targeted by
AI-powered cyberattacks, with nearly half reporting incidents linked to
automated threats.
The underlying issue is not just
volume, but velocity. AI is enabling attackers to operate faster, more
precisely, and at significantly greater scale than before.
This shift is fundamentally altering
the cyber threat landscape.
According to industry analysis, AI is
amplifying existing attack vectors rather than creating entirely new ones,
increasing “the volume and sophistication of attacks” and compressing response
times for financial institutions.
For banks, this means that vendor
risk is no longer a static assessment at onboarding, but a continuous and
dynamic challenge.
Nowhere is this more evident than in
third-party ecosystems. European banks rely heavily on complex networks of
vendors, cloud providers, and fintech partners.
Each connection represents a
potential entry point for attackers, particularly as vendors themselves adopt
AI tools with varying levels of governance and security.
The rise of AI-driven threats is
compounding existing concerns. Deepfake-enabled fraud, automated phishing, and
AI-generated impersonation attacks are becoming increasingly common.
Industry research shows that nearly
60% of businesses have experienced AI-enabled deception attacks, with one
report describing them as “a security nightmare for businesses everywhere.”
Critically, these risks extend beyond
external attackers. AI systems themselves can introduce new forms of internal
exposure.
Organizations are often granting AI
tools broad access to data and systems, effectively treating them as trusted
insiders without equivalent controls.
This creates a new category of risk
that sits between traditional cyber threats and operational vulnerabilities.
For European institutions, regulatory
pressure is intensifying. Frameworks such as DORA and NIS2 are pushing firms
toward more robust oversight of third-party risk and operational resilience.
However, policy gaps remain. Analysts
warn that current European cyber frameworks do not fully address emerging
challenges such as obsolete infrastructure and evolving AI threats, leaving
critical blind spots in the system.
