Risk Modelling Training Course | LCT
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Risk Modelling and Scenario Analysis

Course schedule

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Course Overview

This course provides a practical approach to identifying, quantifying, and managing risk through advanced modelling techniques. Delegates will learn how to develop models that assess financial, operational, and strategic risks, using statistical methods and scenario analysis to forecast outcomes. The programme emphasises applying these tools to real-world contexts, enabling participants to make informed, data-driven risk management decisions.

Who Should Attend

Risk, finance, and compliance professionals responsible for assessing and mitigating risks.
Past delegates have included:

  • Risk Managers
  • Compliance Officers
  • Treasury Analysts
  • Financial Controllers
  • Operational Risk Specialists

Course Outcomes

By the end of the course, delegates will be able to:

  • Build quantitative risk assessment models.
  • Conduct Monte Carlo and sensitivity analysis.
  • Integrate risk models into enterprise decision-making.
  • Model credit, market, and operational risks.
  • Assess the financial impact of uncertainty.
  • Communicate risk findings to senior leadership.

Course Topics

Excel Best Practices for Modelling

  • Structuring workbooks for clarity and consistency.
  • Applying dynamic formulas and named ranges.
  • Using conditional formatting for error checking.
  • Documenting models for transparency and handover.

Data Integrity, Validation, and Audit Trails

  • Importing and cleaning large datasets.
  • Setting up data validation rules.
  • Building audit trails for compliance.
  • Protecting model integrity against accidental changes.

Effective Communication of Modelling Insights

  • Translating outputs into actionable recommendations.
  • Designing executive-friendly dashboards.
  • Visualising key results with charts and graphics.
  • Structuring impactful presentations for stakeholders.

Quantitative Risk Assessment Techniques

  • Selecting risk metrics and KPIs.
  • Building probabilistic models.
  • Applying Value-at-Risk (VaR) methods.
  • Integrating external risk data.

Scenario and Stress Testing in Risk Models

  • Designing adverse and extreme scenarios.
  • Modelling the impact of macro shocks.
  • Linking scenario outputs to mitigation strategies.
  • Creating decision-support dashboards.
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