Risk Modeling
Our risk modeling services empower businesses to make informed decisions by accurately identifying, quantifying, and mitigating potential threats using data-driven approaches.
- We apply sophisticated methods such as Monte Carlo simulations, scenario analysis, and Value at Risk (VaR) calculations to identify and forecast risks.
- Our team also leverages machine learning and predictive analytics to uncover emerging risk trends and detect early warning indicators
- Predictive Modeling Utilizing advanced analytics to forecast and quantify potential risks
- Scenario Planning Exploring “what-if” scenarios to test stress resilience and ensure organizational adaptability
- We rigorously test and validate each model to ensure accuracy and reliability.
- Our experts work closely with your teams to integrate risk modeling practices into daily operations, decision-making, and reporting.
- We provide ongoing support, updates, and recalibrations to keep models aligned with evolving market dynamics.
- Predictive Analytics & Foresight Identifying future trends and potential risk events to drive strategic planning
- Scenario Analysis & Probability Testing Exploring "what-if" scenarios to assess resilience and guide crisis management strategies
- Model Testing & Validation Evaluating the accuracy of existing models and enhancing methodologies
- Risk Modeling Training Customized programs to build in-house capabilities, covering fundamentals and advanced quantitative techniques
- Full Model Development End-to-end development of risk models—including design, calibration, testing, and full documentation for transparency and effectiveness
- Pre-built Model Review Comprehensive assessment of existing models to identify performance gaps and opportunities for improvement
Risk Analysis Tools
The DecisionTools Suite is a comprehensive set of applications for risk management and decision-making, aimed at enhancing key organizational performance indicators. The suite includes @RISK and other analytics tools covering decision analysis, probability analysis, statistics, and optimization—all operating within a user-friendly Microsoft Excel environment.
We also support: Building decision trees, Optimizing resource allocation, Identifying critical factors, Estimating costs, Incorporating uncertainty into project schedules.
With advanced features like Monte Carlo simulation that calculates all possible outcomes of scenarios, and presentation-ready reporting, you can use the DecisionTools Suite to structure complex decisions, forecast data, allocate limited resources, and make confident, high-impact decisions.
Risk Analysis with Monte Carlo Simulation
@RISK is used for risk analysis through Monte Carlo simulation. It calculates and tracks numerous potential future scenarios, shows the probability of each, and simplifies decision-making to achieve optimal outcomes.
Results Visualization
PrecisionTree supports decision analysis using decision trees and influence diagrams. It visually maps complex decisions in a structured, step-by-step format to identify all possible alternatives and select the best option.
Identifying Critical Factors
TopRank automatically performs “what-if” sensitivity analysis on Microsoft Excel spreadsheets, allowing you to identify and rank all critical input factors
Leverage Data for Forecasting
StatTools enables forecasting and statistical analysis to support data-driven decision-making
Foresight Forecasting
NeuralTools enables forecasting using advanced neural networks. It mimics brain functions to "learn" patterns in known data and uses these patterns to make predictions from new, incomplete data. It also updates predictions automatically as input data changes—saving time and enabling more accurate analysis
Solving Complex Allocation Problems
Evolver optimizes using genetic algorithms and linear programming, finding optimal solutions for both small and large linear problems. It also delivers the best overall results for complex nonlinear challenges where other methods fall short
Optimization with Monte Carlo Simulation
RISKOptimizer combines genetic algorithms with Monte Carlo simulation to solve optimization problems by testing different options to meet objectives. It runs a Monte Carlo simulation on each trial solution to account for inherent uncertainty and reach the most accurate outcome
Managing Uncertainty in Project Schedules
ScheduleRiskAnalysis (SRA) analyzes schedule risks using Monte Carlo simulation via @RISK, identifying the probability of all potential scheduling outcomes.
