From risk appetite to intelligent action in three integrated layers
RiskMetrica operates through three integrated layers that work seamlessly together
Board-approved risk appetite statements are translated into machine-readable rules that define what actions AI agents can and cannot take. This creates dynamic governance guardrails that adapt to changing risk conditions.
Risk appetite statements approved at board level
Converted to executable rules and tolerances
Real-time enforcement of approved boundaries
AI-powered decision intelligence learns from every risk decision to provide increasingly accurate predictive guidance. Machine learning models continuously improve as they process more risk events and outcomes.
Models improve with every risk decision
Identifies emerging risks before materialisation
Forecasts probability and impact of risk events
Six categories of AI agents execute risk management tasks at machine speed, operating within the boundaries set by risk appetite and guided by decision intelligence. Each agent category specialises in a specific domain.
Execute approved decisions in milliseconds
Escalate edge cases to human decision-makers
Complete record of all agent actions and reasoning
Each layer feeds into the next, creating a continuous cycle of governance, intelligence, and execution
Constrains
Board-approved risk appetite defines the boundaries within which decision intelligence operates, ensuring all predictions and recommendations comply with strategic risk tolerance.
Guides
Decision intelligence provides predictive risk scores and recommended actions that guide AI agents, improving decision quality while maintaining governance compliance.
Informs
Agent actions and outcomes generate data that informs future risk appetite refinement, creating a continuous feedback loop for governance improvement.
Specialised agents for every domain of enterprise risk management
Monitor compliance with risk appetite statements in real-time
Detect behavioural patterns that indicate cultural risk
Learn from risk decisions to improve future predictions
Automate regulatory reporting and breach detection
Forecast risk events using statistical and ML models
Ensure all AI operates ethically and transparently
Request a demonstration to see the three-layer architecture in action