Canary Wharf - Artistic Rendering
Working Prototype

MCMC Risk Dashboard

Interactive probabilistic risk network visualisation using Markov Chain Monte Carlo simulation for complex risk assessment scenarios.

Status: Functional

Core functionality implemented and ready for customisation to specific risk environments.

Technology Stack

React, D3.js, WebAssembly (for MCMC computation), TypeScript

Deployment Ready

Can be deployed and customised for specific organisational contexts within weeks.

What the Dashboard Does

This prototype demonstrates how Bayesian networks and MCMC simulation can transform risk assessment from static matrices to dynamic, interactive exploration tools.

Network Visualisation
Interactive risk relationship mapping

Displays risks as nodes in a network with connections showing probabilistic relationships. Users can explore how changes in one area affect the entire risk landscape.

  • Interactive node manipulation and exploration
  • Real-time relationship strength indicators
  • Conditional probability displays
  • Network clustering and grouping
MCMC Simulation
Robust uncertainty exploration

Runs thousands of scenarios using Markov Chain Monte Carlo methods to explore the full space of possible outcomes under uncertainty.

  • Posterior distribution sampling
  • Convergence diagnostics and validation
  • Scenario probability calculations
  • Sensitivity analysis across parameters
Scenario Testing
What-if analysis capabilities

Interactive scenario exploration allowing users to adjust assumptions and immediately see how changes propagate through the risk network.

  • Real-time parameter adjustment
  • Evidence insertion and belief updating
  • Comparative scenario analysis
  • Impact pathway tracing
Influence Analysis
Understanding what drives what

Identifies which risks have the greatest influence on others, helping prioritise attention and mitigation efforts where they'll have maximum impact.

  • Influence strength calculations
  • Critical pathway identification
  • Leverage point analysis
  • Cascade effect prediction

Technical Approach

Bayesian Network Foundation

The dashboard is built on a Bayesian network engine that represents probabilistic relationships between risk factors using directed acyclic graphs.

Network Structure

  • • Nodes represent risk factors or events
  • • Edges encode conditional dependencies
  • • Conditional probability tables define relationships
  • • Network topology captures domain expertise

Inference Engine

  • • Belief propagation for exact inference
  • • MCMC sampling for complex networks
  • • Evidence incorporation and updating
  • • Query answering and marginalisation

MCMC Implementation

For complex networks where exact inference is computationally intractable, we use Markov Chain Monte Carlo methods to sample from posterior distributions.

Sampling Strategy

Gibbs Sampling

For networks with conjugate priors and well-behaved posteriors

Metropolis-Hastings

For general-purpose sampling when Gibbs isn't applicable

Hamiltonian Monte Carlo

For continuous variables requiring efficient exploration

Interactive Visualisation

The user interface translates complex probabilistic computations into intuitive visual interactions that domain experts can understand and manipulate.

Network Layout

  • • Force-directed layout algorithms
  • • Hierarchical positioning options
  • • Clustering and grouping capabilities
  • • Zoom and pan for large networks

Real-time Updates

  • • WebAssembly for fast computation
  • • Incremental belief updating
  • • Progressive result rendering
  • • Responsive parameter adjustment

Potential Applications

This prototype can be adapted for various risk assessment contexts. Here are some potential applications we're excited to explore with early adopters.

Supply Chain Risk
Mapping interdependencies

Model how disruptions propagate through supply networks, identifying critical suppliers and vulnerable pathways.

Manufacturing
Logistics
Cybersecurity Threats
Attack pathway analysis

Understand how security vulnerabilities combine to create attack vectors, prioritising defences based on network effects.

IT Security
Finance
Financial Risk
Portfolio correlation analysis

Model how market conditions affect correlations between assets, especially during stress periods when diversification fails.

Banking
Investment
Operational Risk
Process failure interactions

Explore how operational failures in one area affect others, identifying system-wide vulnerabilities and mitigation priorities.

Healthcare
Energy
Regulatory Risk
Compliance interdependencies

Map how regulatory changes in one area trigger requirements in others, enabling proactive compliance planning.

Financial Services
Pharma
Climate Risk
Physical and transition risks

Model interactions between physical climate impacts and transition policies, understanding compound risk effects.

ESG
Insurance

Implementation Pathways

Pilot Deployment
Start with a focused use case

Deploy the dashboard for a specific risk domain in your organisation. Learn what works and refine the approach.

  • • 4-8 week deployment timeline
  • • Custom network configuration
  • • User training and support
  • • Iterative refinement process
Collaborative Development
Co-develop for your specific needs

Work with us to enhance the prototype with features specific to your industry or risk environment.

  • • Joint development partnership
  • • Domain-specific enhancements
  • • Shared intellectual property
  • • Open source contributions
Open Source Access
Self-implementation pathway

Access the open source codebase and implement the dashboard within your own technical environment.

  • • Full source code access
  • • Implementation documentation
  • • Community support forums
  • • Optional consulting support

Early Adopter Opportunities

We're particularly interested in working with organisations willing to share their experience and help us understand how probabilistic risk assessment performs in real-world environments. Early adopters benefit from preferential pricing, close collaboration, and the opportunity to influence the tool's evolution.

Technical Requirements

Deployment Options

Cloud Hosted (Recommended)

We host and maintain the dashboard, you access via web browser.

  • • No infrastructure requirements
  • • Automatic updates and maintenance
  • • Enterprise security and compliance
  • • Usage-based pricing

On-Premises Installation

Deploy within your own infrastructure for maximum control.

  • • Docker container deployment
  • • Kubernetes orchestration support
  • • Integration with existing systems
  • • Custom security configurations
Integration Capabilities

Data Sources

  • • REST API for external data feeds
  • • CSV/Excel file import
  • • Database connectivity (SQL/NoSQL)
  • • Real-time streaming data support

Export and Reporting

  • • Interactive report generation
  • • PDF/PowerPoint export
  • • Embedded dashboard widgets
  • • API for programmatic access

User Management

  • • Role-based access control
  • • Single sign-on (SSO) integration
  • • Audit logging and compliance
  • • Multi-tenant configuration

Ready to Explore Probabilistic Risk Assessment?

This dashboard represents a new approach to risk assessment that moves beyond traditional matrices to embrace the complexity and uncertainty of real-world risk environments.

What Happens Next?

  1. 1. Discovery Call - We discuss your risk environment and specific challenges
  2. 2. Prototype Demo - See the dashboard in action with sample scenarios
  3. 3. Pilot Planning - Design a focused pilot deployment for your context
  4. 4. Implementation - Deploy and customise the dashboard for your needs
  5. 5. Learning Journey - Iterate and refine based on real-world experience