Validating Financial Models

Over the past few years I have shared many articles about the significant benefits available to corporate management from effective, flexible financial models that encompass all the key elements of the business case.

Recently, at the request of a major South African development finance institution, I created a new course, not about the building of financial models, about validating models presented by clients or client consultants in support of funding applications.

Having developed numerous financial modelling courses and presented them successfully all over the world, the idea of developing a course to validate financial models was an interesting challenge.

Being practitioners of best practice international modelling methodology and proponents of the FAST modelling standard, unconsciously one tends to assume that the creators of financial models would have similar views and capabilities.

In truth, this is often an error of judgement, and on many occasions the models presented as part of the finance application are deficient at best, and wrong at worst.

Furthermore, the reality is, that many of the people involved in receiving these models and being responsible for validating the accuracy and credibility of the models, are not experienced knowledgeable financial model builders.

This of course begs the question of how one can validate something, improve its structure, test validity and accuracy without having the skills and knowledge to create an effective model.

Most project models irrespective of the particular industry, are driven by technical inputs supplied by qualified industry engineers. e.g. mining engineers who provide detailed mining plans based on geographical studies. These plans encompass not only the size and scope and location of the particular resource, but also the mining method to be applied, the timescale for the development of the mine and the different capital expenditure phases in order to bring the mine to a productive state.

Listed below are some of the typical model issues, pertinent to project models, that require careful verification and validation:

Typical  – Financial Model Review Checklist

1. General Model Structure & Best Practices

1. Clear, categorised, comprehensive input assumptions
2. Clear separation of inputs, calculations, and outputs
3. Sequential, modular structure for input assumptions, support schedules, financials, analysis
4. Consistent formatting, naming conventions, and error-checking applied
5. No hardcoded values in formulas – no blank cells in formulas
6. Simple, logical time-based calculations – use of formula sets
7. Circular reference check – and proper handling of iterative calculations
8. Scenario analysis and sensitivity testing enabled

2. Input Assumptions Validation

2.1 Revenue Assumptions

1. Verification of all technical issues, processes and outputs, including timelines and capital

expenditures which are the fundamental drivers of resource production.

This can be a demanding challenge even when the person or persons validating the model are

themselves engineers.

1. Volumetric measures validated (production, capacity utilization, sales forecasts)
2. Price assumptions are market-based and aligned with contracts
3. Consideration for seasonality and cyclical fluctuations
4. Indexation/escalation of revenues aligns with economic indicators

2.2 Direct Costs & Overheads

1. Cost structures validated (raw materials, labour, utilities, maintenance)
2. Inflation adjustments applied appropriately
3. Correct classification of fixed vs. variable costs

2.3 Capital Expenditure (Capex)

1. Capex assumptions align with feasibility studies and engineering reports
2. Breakdown of initial investment, replacement cycles, contingencies
3. Decommissioning and residual values if relevant

2.4 Funding Structure & Debt Assumptions

1. Debt-to-equity ratio aligns with industry benchmarks
2. Debt serviceability stress-tested (DSCR > 1.2x or per lender requirement)
3. Loan terms (interest rates, repayment, grace periods) are reasonable
4. Fixed vs. floating rate risks considered

2.5 Inflation & Tax Assumptions

1. Revenue & cost inflation assumptions aligned with economic data
2. Corporate tax rates correctly applied, considering incentives and tax holidays

3. Verification of Financial Statements & Key Metrics

3.1 Financial Statements Review

1. Income Statement: Revenue, EBITDA, EBIT, and Net Profit correctly calculated
2. Cash Flow Statement: Breakdown into operating, investing, and financing cash flows
3. Correct calculation of CFADS ( Free Cash Fow)
4. Balance Sheet: Proper classification of assets, liabilities, and equity

3.2 Key Performance Metrics

1. Profitability: Gross Margin, EBITDA Margin, Net Profit Margin
2. Liquidity & Solvency: Current Ratio, Quick Ratio, Debt-to-Equity Ratio
3. Debt Serviceability: DSCR, Loan Life Coverage Ratio (LLCR), Interest Coverage Ratio (ICR)
4. Return Metrics: IRR, NPV, Payback Period, ROE, ROA
5. Project-Specific KPIs: Capacity Utilization, Unit Production Costs, Breakeven Levels

4. Sensitivity & Risk Analysis

1. Sensitivity testing for price declines, cost overruns, and lower demand
2. Viability maintained under worst-case scenarios
3. Key risks are identified and mitigation strategies applied:

Market Risk: Demand and price volatility

1. Operational Risk: Supply chain disruptions, inefficiencies
2. Financial Risk: Currency fluctuations, inflation impact, interest rate hikes
3. Regulatory Risk: Changes in tax laws, policies
4. Environmental & Social Risks: Compliance with ESG standards

5. Final Decision Criteria for Funding Approval

1. Positive NPV and IRR above the cost of capital
2. Acceptable debt service capacity (DSCR > 1.2x)
3. Project remains viable under sensitivity testing
4. Meets DFI lending policy criteria (leverage ratios, equity requirements)
5. Compliance with environmental, social, and governance (ESG) standards
6. No major regulatory or legal concerns

6. Final Recommendation Process

1. Validate key assumptions and technical inputs
2. Verify formula accuracy and financial integrity
3. Analyse financial statements and key metrics
4. Conduct sensitivity and risk analysis
5. Assess compliance with DFI policies and ESG standards
6. Provide funding recommendation based on overall feasibility

Conclusion

This checklist serves as a quick-reference guide for validating financial models, ensuring transparency, and mitigating risks in project financing.

Projects meeting all decision criteria should be considered for funding approval, while those failing key validation checks require further due diligence or restructuring.

Projects meeting all decision criteria should be considered for funding approval, while those failing key validation checks require further due diligence

A robust financial model is essential for evaluating the feasibility of a project.

By applying best practices in financial modelling, validating assumptions, and analysing key performance indicators, DFIs can make informed funding decisions while managing financial and operational risks effectively.

If you would like Goalfix to validate your financial models, please send an email to my email address or call me.

Colin Human CA(SA

CEO – Goalfix Financial Modellers

 colin@goalfix.co.za