Risk Modelling and Scenario Analysis

Quantitative Risk Assessment Techniques

• Select appropriate probability distributions for key uncertainties.
• Estimate risk‑adjusted outcomes using simulation methods.
• Calculate downside metrics (e.g., VaR, CVaR) relevant to decisions.
• Rank mitigations by value‑at‑stake and feasibility.

Stress Testing and Sensitivity Design

• Define severe‑but‑plausible scenarios tied to strategic risks.
• Run one‑way and multi‑factor sensitivities to expose fragility.
• Incorporate correlation and tail‑risk behaviours into results.
• Frame management responses and contingency triggers.

Excel Best Practices for Financial Modelling

• Structure models with separate inputs, calculations, and outputs to improve auditability.
• Use consistent naming conventions, dynamic ranges, and version control to reduce errors.
• Implement checksums and reconciliation flags to validate calculations end‑to‑end.
• Document assumptions, sources, and logic to support review, handover, and maintenance.

Ensuring Data Integrity and Model Accuracy

• Design robust data import and transformation steps with traceable lineage.
• Apply validation tests (type, range, and logic checks) to catch anomalies early.
• Minimise hard‑coding; build driver‑based links that prevent circularity and drift.
• Create error‑handling and exception logs that surface issues for timely fixes.

Communicating Financial Insights Effectively

• Translate model outputs into clear narratives that answer the ‘so what?’.
• Use charts, bridges, and scenarios to highlight drivers, risks, and options.
• Present concise recommendations with quantified impacts and sensitivities.
• Package model files and executive packs for efficient decision meetings.