The AI insider risk reshaping financial services

In financial services, trusted access no longer starts and ends with people. As the sector increasingly embraces AI agents to support digital transformation, non-human identities are becoming part of daily industry processes.

While the rapid adoption of AI agents and autonomous workflows is a promising path forward to accelerate operational efficiency, it doesn't come without increased risk.

Across financial services, AI and AI agents are being used to support decision-making, automate workflows and move information among customer, payment, claims, trading and compliance systems. This shift is already well underway, with 75% of U.K. financial services firms now using AI, according to a U.K. Parliament report. AI is set to transform productivity, but that promise depends on how securely organizations move forward with its adoption.

Financial organizations need to treat AI as a new insider: an entity with access to sensitive data, systems and workflows. With the right security and governance controls, AI can safely transform productivity. Without those controls, businesses risk giving powerful autonomous systems the ability to access, move and act on sensitive information at machine speed.

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To ensure defenses can compete in the modern threat landscape, financial institutions need a security model that keeps pace with both human and non-human identities. This requires a model that provides context on how employees, accounts and AI agents behave over time and spots when legitimate access quickly turns into risk.

Trusted access becomes the risk

Financial services organizations depend on trusted access as a key pillar of their services. Traditionally, this has focused on employees, contractors and administrators holding responsibility for sensitive data and critical processes. With environments becoming more automated, interconnected and AI-driven, trusted access now extends beyond human activity.

Security teams are now monitoring AI agents that operate continuously, process large volumes of information and act in seconds. These agents may inherit access from employees, service accounts or third-party integrations, making it harder to see where activity originated, why a decision was made and who is accountable.

With this comes a new layer of insider risk. The insider is no longer limited to an employee acting carelessly or maliciously. It can also arise from a non-human identity or AI-enabled process that has been granted legitimate access that enables exposure.

While traditional controls still matter, they were not designed to work at this level of speed, autonomy and context. They can confirm whether an identity has permission to access a system, but not always whether that access is appropriate. In financial services, firms need to know not only who or what has access, but whether their activity is normal, permitted and secure.

Securing AI agents without blocking innovation

Organizations in the financial space should not respond to AI risk by blocking AI tools. AI agents can deliver tangible value, from improving customer service and reducing manual work to supporting faster decisions.

The priority is trusted adoption. This involves not inherently assuming AI agents will always act with accuracy and reliability. Financial firms need governance, human oversight and accountability around how AI agents access systems, use data and make decisions. All that while providing security teams with behavioral analytics to detect unusual activity, investigate risk and respond with greater context.

To support secure AI adoption, the sector should focus on:

Maintaining trust with AI oversight

AI agents will continue to move faster, act across more systems and take on more operational responsibility. The priority now is making sure security can move with them.

Trust in financial services can no longer rely on access controls alone. The firms that will gain the most value from AI will be the ones that can use agents confidently, with the right visibility and oversight in place to protect customers, data and the trust the sector is built on.

The goal is not to slow AI down, but to ensure every action can be understood, trusted and defended.

How is your organization managing AI agent risk? Email us at [email protected].