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Building operational resilience with agentic AI in financial services

What happened
Based on Google Cloud Blog · Aug 18, 2026

Deutsche Bank and Google Cloud have built an AI-driven platform to meet the EU’s Digital Operational Resiliency Act (DORA) by transforming manual resilience exercises into automated, evidence-ready simulations based on real operational data.

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Building operational resilience with agentic AI in financial services
Google Cloud Blog — Google
Key points
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For financial institutions, operational resilience has long been embedded in regulatory and supervisory expectations — to say nothing of the high expectations of consumers.
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With the implementation of the European Union’s Digital Operational Resiliency Act (DORA), those expectations have become even more stringent, with more explicit, harmonized, and evidence-driven requirements.
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Firms must now demonstrate that their critical business services and supporting digital infrastructures can withstand disruption, support coordinated response, and recover with control.
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The platform builds enterprise context from architecture, data flows, logs, incident history, alerting signals, and operational telemetry to generate scenarios, simulated operational evidence, structured session records, and regulator-ready artifacts.

Deutsche Bank developed an AI-powered agentic resilience platform to modernize its regulatory tabletop exercises, replacing manual preparation with context-aware simulations grounded in actual operational data such as architecture diagrams, logs, and incident history. The platform generates regulator-ready scenarios and artifacts by analyzing enterprise signals, ensuring exercises reflect real system dependencies and failure patterns rather than static assumptions. To meet supervisory expectations, Deutsche Bank collaborated with Google Cloud, leveraging its agentic AI tools to transition from episodic drills to a continuous intelligence model for resilience testing and root-cause analysis.

The platform uses a dual-orchestration architecture, separating workflows into governed, traceable processes for regulatory compliance and adaptive investigations for operational flexibility. LangGraph ensures deterministic scenario generation with clear audit trails, while the same agents analyze architecture, data flows, and logs across both planned exercises and real incidents to maintain a consistent resilience model. This separation allows Deutsche Bank to combine strict governance with dynamic analysis, supporting scalable and compliant resilience workflows across its global operations.

Deutsche Bank’s platform integrates Google Cloud services—Cloud Run for elastic execution, Gemini Enterprise Agent Platform for scenario structuring, Google ADK for agent coordination, and Cloud SQL for persistent evidence storage—to enable traceable, controlled, and auditable resilience testing. Each scenario drives a structured tabletop session, producing audit-ready evidence that demonstrates coordinated response and recovery capabilities under frameworks like DORA. The platform’s real-time grounding in enterprise context strengthens consistency across teams and ensures exercises align with actual operational conditions.

The platform extends its value beyond planned exercises by using root-cause analysis from real incidents to refine future scenarios and playbooks, creating a feedback loop between production events and resilience testing. Deutsche Bank is now applying this model across multiple portfolios to establish scalable resilience paradigms and a replicable blueprint for the financial sector. The next phase involves expanding the platform into a broader resilience intelligence layer, supporting playbook refinement, recovery-readiness assessments, and continuous validation of controls against evolving system conditions.

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