European DORA and The Importance of Being Prepared Webinar

DORA exists to remove ambiguity across EU financial institutions by defining a consistent baseline for operational resilience. Instead of vague expectations, it provides a clear framework for how far organisations need to go to manage risk. This shifts security from interpretation to execution, reducing room for “good enough” compliance.

While GDPR focuses on personal data, DORA extends into operational continuity, system integrity, and service reliability. It introduces stronger emphasis on maintaining trust in financial systems, not just protecting information. Organisations must now secure not only data, but also the availability and authenticity of the services that depend on it.

DORA forces senior leadership to take ownership of cyber and operational risk, eliminating the ability to delegate responsibility entirely to IT or security teams. Risk management must become a real decision-making process, not a checkbox exercise. This creates direct accountability for how organisations prepare for, respond to, and recover from incidents.

Financial institutions rely heavily on vendors, cloud providers, and partners, but visibility into these environments is often limited. DORA requires stronger oversight, contractual controls, and continuous monitoring of third-party risk. Organisations must assume supplier risk is part of their own attack surface and manage it accordingly.

DORA cannot be implemented through isolated compliance or security initiatives. It demands coordination across risk, IT, security, legal, procurement, and business operations to ensure consistent controls and rapid response capability. Approaches like Zero Trust and SASE help by unifying access control, visibility, and enforcement into a single operational model.

In security operations, AI is already reducing manual workload by correlating alerts, analysing behaviour, and accelerating investigation. This allows analysts to focus on higher-value decisions rather than repetitive triage tasks. The real value of AI lies in speed, scale, and consistency of detection, not autonomous decision-making.