Risk programs have never had more ground to cover — cyber, third-party concentration, operational resiliency, AI — while the organizations they govern grow more complex every quarter. Most programs respond by adding people, repositories, and assessments, but capacity has never been the constraint.

The underlying problem doesn’t move: risk data stays fragmented across GRC systems, spreadsheets, and documents, with no shared definition of what the business actually does — so no one can say with confidence what’s covered and what isn’t. 72% of banks report limited adoption of advanced technologies within the risk function, and institutions still running on manual processes report seven times more examiner questions and concerns.

A Digital Twin of an Organization is a living, connected model of how the enterprise operates — every process, in every org unit, linked to the systems that support it, the controls that govern it, the regulations that apply to it, the vendors it depends on, and the metrics that measure it. The result is a governed, queryable model that both people and AI can read. With it, coverage gaps become visible instead of assumed, change impact is computed instead of estimated, and risk assessment shifts from filling in a blank RCSA in a workshop to reviewing and challenging what the model already proposes.

This session covers what a Digital Twin of an Organization is, how one is built, and what it changes across operational risk, compliance, resiliency, and third-party risk — including a live walkthrough of a working digital twin of a bank.

In This Session
• Why risk programs still struggle despite significant investment
• What a Digital Twin of an Organization is — and how it differs from traditional process documentation and a GRC repository
• Building the foundation: the Process Inventory
• Connecting the model: aligning risks, controls, systems, regulations, vendors, roles, and metrics to process
• Governance — keeping the twin accurate enough to be trusted
• Automated risk assessment — inferring risk profiles from the model, and moving the risk team from authoring assessments to challenging them
• Risk reporting and regulatory engagement backed by traceable evidence