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Harnessing AI for Insider Fraud Detection in Banking: Strategies for Internal Audit Directors
  7 min
Harnessing AI for Insider Fraud Detection in Banking: Strategies for Internal Audit Directors
Secure. Automate. – The FluxForce Podcast
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Introduction 

CIOs in global banks manage identity and access across regions that rarely align. One regulator wants strict session controls. Another expects deeper audit trails. These demands sit on top of hybrid work, multiple clouds, and fast-moving operations. It creates a landscape where a single weak point can slow a payment run or trigger a compliance inquiry. 

Public guidance from NIST stresses ongoing identity checks, and that view fits banking reality. Attackers prefer to compromise access rather than break networks. They often wait for an active session because it gives direct entry into payment systems and internal dashboards. This shift raises a simple question. How long can a bank trust a session once the user is authenticated? 

Banks once depended on network boundaries. That model struggles today. Staff move between office, remote, and mobile. Session tokens follow them. These changes create small cracks that attackers watch for. They know a firewall cannot detect unusual behavior inside a logged-in session. 

This becomes visible during high-value operations. A stolen session can affect a SWIFT message, a treasury approval, or a branch system update. The threat hides inside normal activity. This is why is zero trust important for modern banking. The zero trust security model focuses on continuous validation, not a one-time login. 

The case for watching sessions, not just identities

Banks are now shifting attention from login events to real user behavior. They need to see how a session evolves from the moment it starts. This is why continuous session monitoring for global banks is becoming a core expectation. It helps confirm that the right person remains behind the keyboard. It also gives CIOs early signs of drift, such as odd navigation paths or unusual timing patterns. 

This brings up a deeper question. What signals tell a CIO that a session is no longer trustworthy even if the user originally passed MFA? 

Continuous validation gives banks that clarity. It supports the identity-centric oversight regulators expect and reduces the blind spots that attackers exploit inside authenticated activity. 

How AI Interprets User Behaviour and Flags High-Risk Insider Activities


Why banks need ongoing identity checks ?

In global banking, a login is only the starting point. Continuous authentication keeps validating identity throughout the session, so trust does not weaken after MFA. Banks use it because attackers often target active sessions, not firewalls. It forms the baseline for continuous session monitoring for global banks, which becomes a core part of the CIO’s Zero Trust strategy. 

When MFA is not enough for high-value transactions ?

One-time MFA cannot protect long sessions used in SWIFT operations, treasury work, or trading desks. Attackers often wait until authentication is complete. They exploit session tokens and browser artifacts. This is why continuous risk-based authentication matters. It reacts to unusual behavior, odd navigation, or device changes in real time. 

Adaptive controls that strengthen session security 

Banks use adaptive authentication models to raise or lower scrutiny based on risk signals. Routine actions stay smooth. High-value actions trigger deeper checks. These signals feed directly into the Zero Trust layer that governs real-time session decisions. They help CIOs maintain identity confidence across borders and lay the foundation for fraud detectionbehavioral analysis, and stronger session trust inside the broader zero trust strategy.

Why existing controls don’t meet continuous session monitoring needs ?

Most global banks still depend on older monitoring models that verify users only at login, rely on scattered identity systems, and provide inconsistent visibility across regions. These shortcomings directly block the execution of a continuous session monitoring zero trust strategy because risk cannot be evaluated in real time. 

Why existing controls don’t meet continuous session monitoring needs

Core weaknesses that compromise session-level zero trust

1. Authentication that stops after login 
Traditional IAM validates identity once, then assumes the user stays trustworthy. High-risk areas like trading desks, cross-border payments, and treasury operations require ongoing validation, not static trust.

2. Identity silos across regions and business units

Banks often maintain separate identity stores for APAC, EMEA and North America. This breaks end-to-end session correlation, a mandatory requirement for continuous monitoring and zero trust. 

3. Legacy platforms with limited session telemetry

Mainframe systems, older trading applicationsand custom-built banking modules generate only basic logs. Without fine-grained session signals, tools cannot detect behavioural drift, abnormal access paths, or subtle insider misuse. 

4. API gateways without behavioural or risk controls

Older API layers simply pass requests without inspecting them for automation patterns, abnormal sequence flows or session hijacking attempts. This creates blind spots in workflows handling high-value customer and financial data.

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Strategic impact on a zero trust session model

These limitations prevent CIOs from enforcing a continuous verification posture

The result: 

  • gaps in risk-based access decisions 
  • delayed detection of session anomalies 
  • inconsistent enforcement across channels 
  • higher exposure during privileged or high-value actions 

Attackers specifically target these areas because they allow them to operate inside a “trusted” session without raising alerts.

The CIO strategy for continuous session monitoring

When we deployed continuous session monitoring across global banking operations, one truth stood out quickly: trust collapses the moment you treat a session as static. In a Zero Trust strategy, a session must evolve with the user, the workflow, the device, and the context. Anything less creates a blind spot wide enough for fraud, insider misuse, or session hijacking. 

The CIO strategy for continuous session monitoring

1. Treat session trust as a living control, not a login outcome

In practice, a login tells you almost nothing after the first few minutes. 
What mattered in real operations was how the session behaved during high-value tasks—approving a SWIFT transfer, querying large treasury datasets, or running a cross-border compliance check. 
So, we shifted from “authenticate, then trust” to “authenticate, then verify continuously.” 

How can a CIO allow a session to stay trusted when the behaviour inside it no longer matches the person who logged in? 

This mindset change allowed us to align continuous authentication with the bank’s enterprise risk model, not just its security stack. 

2. Build behaviour-driven identity as the anchor of zero trust computing

On the trading floor, we saw that genuine users had repeatable patterns: typing rhythm, navigation flow, decision speed, window-switching habits. Attackers could imitate credentials, but they could not imitate behaviour. So we integrated behavioural biometrics with IAM, creating a unified trust model that supported continuous risk-based authentication across regions. This gave us a measurable way to distinguish legitimate activity from controlled or hijacked sessions. 

3. Set governance rules before enabling analytics

The first challenge we faced was not technology. It was deciding which session signals could be collected in London, which could be processed in Singapore, and which could be stored centrally. Global banks cannot run unified analytics without clear governance. 

Once governance was defined, zero trust policy enforcement for financial institutions became predictable, repeatable, and compliant with each jurisdiction’s privacy rules. 

4. Use adaptive controls to protect high-value workflows

The turning point came when we mapped risk signals to micro-actions. If a trader’s behaviour drifted, we introduced a verification step. If a SWIFT operator’s session began showing unusual navigation, we moved the session to view-only mode until identity confidence recovered. 
If a compliance analyst accessed data from an unrecognized location pattern, we issued a just-in-time prompt. 

These adaptive controls protected essential operations without introducing friction.

5. Make privileged session oversight part of core operations 

When we integrated privileged session monitoring into daily operations, not just audits, the risk surface changed. Every privileged user had a live trust score. This made treasury desks, core banking admins, and vendor support far more transparent and far easier to govern under the zero trust network model.

6. Build an analytics loop that learns from real incidents

The strategy only reached full maturity when we created a feedback loop. Fraud patterns from APAC informed risk scoring in Europe. Behavioural anomalies in North America adjusted baselines in the Middle East. SOC insights refined our decision thresholds every month. 
This loop turned continuous session monitoring from a control into a learning system that strengthened Zero Trust day by day.

Enhance security with continuous session monitoring.

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Conclusion

Global banking cannot rely on static controls when most credential abuse happens inside active sessions. Weak identity trust creates gaps that spill directly into trade-compliance errors, audit delays, and regulatory exposure. A Continuous Session Monitoring Zero Trust Strategy gives CIOs a unified path to stabilize identity behavior, reduce manual review work, and maintain consistent compliance across regions. Research across the industry continues to show that real-time session analysis prevents the majority of identity-driven breaches. For global banks, this makes continuous monitoring not an enhancement but a foundation for secure and reliable compliance operations. 

With rising pressure on accuracy, speed, and risk governance, the direction is clear. Strengthening session trust is now central to strengthening the bank. 

Frequently Asked Questions

The system should pause the action or request a quick trust check. This prevents fraudulent steps from moving forward while keeping legitimate work on track. Real-time intervention protects high-value workflows without slowing the user unnecessarily.
Sudden changes in navigation, unusual data access and repeated failed attempts often indicate takeover. These deviations show that the session is no longer aligned with the user’s known banking behavior.
Reaction must be immediate so that risky steps cannot move from intent to execution. Continuous controls work only when signals trigger checks at the moment of deviation. This prevents unverified actions from reaching approval stages.
It evaluates trust throughout the session using behavior, device posture and contextual signals. Each action is treated as a new event that requires validation. This reduces the risk created by long authenticated sessions.
The bank is exposed to long-duration hijacks and credential abuse that go undetected. Once a session begins, every action occurs without fresh verification. This creates blind spots across payments, trade workflows and core banking tasks.
They appear when different regions use separate IAM policies and inconsistent logging formats. These gaps block unified visibility and make it difficult to track a user’s full activity path across borders.
Context-based prompts and temporary holds on sensitive steps help manage uncertainty. These responses keep the workflow alive while forcing reevaluation of trust. They maintain both productivity and safety.
High-value transfers and cross-border approvals become harder to verify. Audit teams lose confidence in who performed each step. This weakens the bank’s ability to prove proper oversight.
Behavioral signals reveal actions that do not match the user’s history. Deviation scoring highlights attempts to access data or perform tasks outside normal patterns. These markers expose misuse even when authentication appears clean.
Trade-compliance staff must slow decisions and request manual verification. This leads to bottlenecks in settlement and review queues. The uncertainty around session ownership forces extra checks and escalations.

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