Insider risk is no longer a niche security problem, it’s a governance challenge at the core of every organization. As businesses evolve toward hybrid operations and data-driven collaboration, the real question is not who has access, but how identities reflect trust, accountability, and intent.
This session explores how Identity and Access Management (IAM) programs can evolve into a foundation of insider risk management, not by adding more surveillance, but by embedding behavioral, ethical, and operational context into identity governance itself.
We’ll look at how identity becomes the language of trust across the enterprise:
• From provisioning to prediction — understanding the signals of privilege misuse and entitlement drift before they become incidents;
• From compliance to culture — turning access policies into expressions of organizational values and accountability;
• From detection to decision-making — using identity-centric risk insights to inform hiring, offboarding, and third-party engagement decisions.
Drawing on cases from finance, healthcare, and the public sector, we’ll demonstrate how organizations can use IAM not just to prevent incidents, but to strengthen their human trust architecture.
The result: a model of identity-driven insider risk management that aligns regulatory compliance with sustainable resilience, proving that trust can be engineered as deliberately as access itself.
Attendees will leave able to:
- Read IAM telemetry signals from existing IGA and PAM data that predict insider incidents earlier than detection tooling.
- Apply a four-node decision tree to test identity-based monitoring against EU proportionality requirements before deployment.
- Translate one identity maturity gap into a defensible annual loss range, anchored in published industry data.
