AI Driven Next Generation Cyber GRC Accelerator

Cyber Risk Quantification

Multi-level quantification processes (CRQ/RQ, RPQ, & RMQ) aligned to business risk exposure providing validation of ALE.
Line-speed processing, more advanced than FAIR with faster decision-making to address impact of risk exposure to reputation and clients’ assets.
More sophisticated than Monte Carlo simulations with patented ability to allocate risk exposure across LOBs, geographic regions and products.
Provides the ability to identify risk exposure as aligned to business risk appetite i.e. organization risk elements consisting of cyber insurance; capital set-asides and ability to absorb risk as a cost of doing business.

Threat Exposure is a critical element of the emerging risk-threat landscape establishing a holistic cybersecurity risk posture to support doing business.
The need for continuous risk-threat compliance and assessment is essential to stay focused on the velocity of local/geographic threat vector vulnerability exploits and associated business risk exposure.
Continuous risk-threat (exposure) governance is essential for ensuring organizations maintain resiliency to risk exposure.
Scheduling the conduct of near real-time risk-threat (exposure) quantified cyber risk assessment with multi-layered quantification covering risk identification, prioritization and remediation, drives a proactive/predictive understanding of the impact of cyber risk exposure on business reputation.

Supporting the transition from a traditional, tactical approach to cyber risk management which relies upon simple risk scores with limited value to the business.
Addressing cause and effect from legacy risk management methodologies to utilize risk exposure metrics that support and enhance business operational resiliency.
Risk exposure planning with visualization enables Decision Supremacy and risk mitigation decision-making.
Using AI driven CTEM within RiskOpsAI™ Integrated Risk Modelling & Decisioning Platform® enables businesses to address vulnerabilities, with alignment to business reputation and operational stability.

Effective measurement of maturity using Control Effectiveness over time provides accurate tracking of cyber risk program performance.
Maturity modeling supports an ongoing understanding of regulatory risk exposure, highlighting areas requiring attention to reduce potential liability.
Using Maturity Models to establish realistic cyber risk program enhancements, enables tracking of improvement and progress.
Maturity Models provide visualization of control effectiveness and cyber risk program improvement.