The Corality Training Academy

Financial Modelling for Mining Projects

Available dates

Dec 3—5, 2019
3 days
London, United Kingdom
TBD
Feb 11—13, 2020
3 days
Sydney, Australia
TBD
Feb 18—20, 2020
3 days
Singapore
TBD
+2 more options

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Full disclaimer.

About the course

Learn the skills required to build an integrated financial model for a mining project in this hand-on training course – from essential Excel functionality to powerful commercial scenario analysis.

Overview of the lifecycle of the model for a mining project, from PFS and BFS to financial close and operations:

  • Explore the different requirements in functionality and expectations from a technical model to a financial model for investment decision
  • Understand what financiers and investors look for when assessing a financial model during the investment, project finance or due diligence process
  • Identify typical pain points from a financial modelling perspective across the mine lifecycle

Master proven techniques for best practice modelling resulting in better models built faster:

  • Understand the 10 foundation principles of SMART financial modelling – Corality’s best practice methodology – and how it applies to the mining industry
  • Review the visual representation of SMART while highlighting good vs. bad modelling techniques using real-life examples
  • Master the art of consistency amongst your team in calculation techniques and presentation of outputs to drive trust and reliability in analysis and comparable analysis

Build a foundation structure of your financial model which is robust, flexible and scalable for future project developments:

  • Build a flexible timing structure in the financial model using appropriate date functions and binary flags – this is an essential modelling component for scalability and flexibility
  • Construct modularised units that form the building blocks of a professional model and ensures transparency and allows for rapid expansion or modification of the financial model
  • Establish key constants in the model using full scope of Excel range name function

Focus on the physical production of the mining project with a structured approach to physical assumptions and calculations:

  • Structure assumptions for Mine Reserves and Production (Mining, Milling, etc) in a flexible and transparent way for future flexibility
  • Develop essential modules including Stockpile Calculation, Grade Analysis, Levels and Yields and prepare for powerful sensitivity and scenario analysis
  • Understand the flow of physical calculations and how they interact with the full financial model

Comprehensive Revenue calculation functionality for your mining financial model:

  • Incorporate pricing path flexibility to analyse different views on future commodity pricing
  • Model hedging contracts and discuss how typical instruments can be incorporated
  • Develop a Scenario Manager in Excel to assess the impact on revenue of different production cases

Project finance modelling: Understand the structure of cashflow waterfalls and the importance of 'seniority' of payments:

  • Cash Flow Available for Debt Service (“CFADS”) – expand the financial model to incorporate this fundamental line item for project finance analysis.
  • Build transparent calculation steps to showcase the Cashflow Waterfall principles and cashflow available at every significant step
  • Understand the risk of Circular References in Excel and how these can best be avoided using clear logic and some simple rules

Developed integrated financial statements into your financial model – a required step for comprehensive analysis:

  • Extend the Cashflow Waterfall functionality with integrated financial statements
  • Master the structured process of developing a balance sheet with no balancing items
  • Integrate integrity checks and logic assessment of the model workings to avoid errors

Project finance modelling: Incorporate debt analysis:

  • Structure financial modelling of term debt and annuity repayment from first principles for full transparency in analysis
  • Develop functionality for target Debt Service Coverage Ratio repayment for powerful project finance analysis
  • Discuss alternative debt repayment options (linear, bullet, etc) and how these are modelled in project finance

Mining specific calculations and output metrics:

  • Financial modelling of depreciation on a life-of-mine basis
  • Understand how a reserve life coverage ratio feeds into the credit process of a project finance bank
  • Account for the value of stockpile inventory
  • Calculate C1, C2 and C3 cost profiles

Project finance and investment modelling: Essential covenants and investment metrics:

  • Learn the importance of credit ratios and their purposes in analysis
  • Build commonly used ratios in project finance banking (DSCR, LLCR, PLCR, RLCR) from first principles for full transparency
  • Extract key metrics from ratios using a range of advanced Excel functions

Investment analysis modelling: Calculate financial returns understand the role of dividends policy:

  • Discuss the reason and impact of dividends policy on valuations of mining projects
  • Integrate internal rate of returns and NPV, understand role of the discount rate
  • Learn differences between NPV and XNPV functions and common errors in their application

Take control of robust and rapid sensitivity and scenario analysis through powerful Excel techniques:

  • Save time and deliver rapid analysis with Corality’s approach to scenario management in financial models
  • Use the Scenario Manager for dynamic integrity testing across all Scenarios – live at the same time
  • Build confidence in your analysis through pre-programmed combinations of model inputs

Who should attend

The training course content is suitable for anyone who needs to build, review or analyse project models within the mining sector, either for internal investments/operations/strategy, project finance transactions or greenfield development analysis.

Typical attendees include to analysts, managers, senior managers, associate directors and CFOs from natural resource companies.

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