CRQ can bring tremendous benefits to an organization as a way to communicate and reduce cyber risk, but the devil is in the details. Sooner or later, you will be asked to defend your numbers and demonstrate how the risk ties to operational items.
This fast-paced workshop dives straight into the core challenge. We’ll show you how advancements in AI will enable you to build defensible models. Further, we’ll provide playbooks for scenario building and risk mitigations.
You’ll walk away with a solid grasp of CRQ and ready to rally your team laying out what you need.
Topic and agenda
Introduction & CRQ Fundamentals (10 minutes)
- Overview of CRQ and Why Precision Matters:
Understand the core principles of Cyber Risk Quantification.
- Current Gaps in Traditional Risk Models:
Identify where conventional methods fall short and the risks of metrics.
Deep Dive: Methodologies & Real-World Use Cases (20 minutes)
- Risk quantification methodologies
Top-down vs. bottom-up approaches
- Developing a rich model
Integrating industry loss data, threat intelligence, and automation
- Using AI for Transparency and Consistency
Explore how AI tools can elevate model quality and methodology
Operationalizing and reporting CRQ: From Numbers to Action (20 minutes)
- Integrating CRQ with Operational Risk Management:
How to embed quantitative risk data into daily business processes.
- Aligning Risk Outputs with Business Objectives:
Strategies for ensuring your numbers drive actionable insights.
- Defending Your Results:
Best practices for presenting and justifying your CRQ findings—what reports to create (and which ones to avoid) and setting the right prioritization thresholds.
Case study and Q&A and Wrap-Up (10 minutes)
- Case studies
Learn from organizations who have executed this successfully
- Open Discussion:
Address challenges and share experiences on applying these methods
