Financial Modeling Errors

What are Financial Modeling Errors?

Errors in a financial model can significantly impact the accuracy of the model’s predictions and recommendations along with being time consuming to fix. In an ideal world, errors would not be present, but due to the high usage and frequent updates required to keep a model up to date they can creep in. Having the skills to swiftly locate and remove financial model errors is an attractive attribute for any analyst.

Here are some common types of errors:

• Incorrect References: These occur when the model refers to the wrong cell or uses the wrong timeline. This can be mitigated by keeping timelines clearly separated, using color coding, and checking copied formulas using dependency arrows.
• Inaccurate/Inconsistent Labelling: Precise, consistent, and unambiguous labelling is crucial for a model to pass an audit quickly. Unclear units can make it difficult to tell if a formula is correct.
• Structural Errors: These are fundamental errors in the structure of the model that can lead to incorrect results.
• Calculation Errors: These occur when the mathematical operations in the model are incorrect.
• Transparency Errors: These occur when the model is not clear or easy to understand, making it difficult to spot other errors.
• Inputting Incorrect Formulas or Data: This is a common source of errors where incorrect data is input into the model, or the formulas used for calculations are wrong.
• Logic Errors in Formulas: These errors occur when the logic used in the formulas is incorrect.
• Not Anticipating a Dynamic Range of Data: This happens when the model does not account for changes in the range of data.
• Rounding Errors: These errors occur when numbers are rounded in a way that impacts the model’s accuracy.
• Unused Assumptions: Unused assumptions can have a potential impact on calculations.

Remember, the key to effective financial modelling is to minimize the risk of errors so that the model always operates with the correct functions and information.

Error Checking Techniques

After finishing a model, analysts should always check the model for mistakes and errors. There are three main checks that can provide a swift screening to ensure glitches are removed before the work is complete.

1)     Sense Check

Sense checking involved looking at the data and inputs to decide if the figures ‘make sense’ and are working. When sense checking, we are essentially asking “Does the output make sense?”. In the example below, if Operating Costs go from 302, to 310, to 250 to 314, that 250 doesn’t look like it makes sense.

Again, if the net income goes from 12.3, to 14.6, to 4.3 to 18.4, the 4.3 doesn’t look right. To correct this the analyst will need to dive quickly into the drivers of the income statement and check the assumptions and calculations.

2)     Structure Check

We also want to make sure the formula structure is consistent and as expected within the model. When checking, analysts can work quickly through the columns, and then the rows to ensure they are happy with their work.

Consistent period columns – When looking at time periods, it is helpful to ensure all the data points are in the appropriate columns. For example, column F refers to Year 1, and column G refers to Year 2, and this is consistent across the balance sheet, income statement, operating statistics, assumptions, and debt calculations. We need to make sure that the formula on the balance sheet in Column F consistently links to other columns Fs where appropriate.

Consistent row labels – Looking at the assumptions below we can see that receivables is shown on the top, then inventories, then prepaids. On the balance sheet receivables is also at the top, followed by inventories, and then prepaids. Keeping the row labels consistent makes it easier to read and avoids any errors creeping in. Having these in the same order helps make inconsistent formulas more obvious to spot.

Linking to wrong columns – A sudden 0 in your final period, perhaps column K or M, might be a sign that you have linked to the wrong column.

3)     Stress Check

The Stress Check allows an analyst to ensure that the model has been created correctly and in line with expectations. Sense Checking is where an assumption is manually changed. This is done to make sure that any related items change appropriately to factor in the new figure.

For example, if we were to hard-code a figure that was double the previous revenue forecast into an income statement, what outcome might we expect? We might expect some costs to go up, and it is very likely that net income will go up to reflect the significantly higher sales. We also might expect equity on the balance sheet to go up. Stress checking your model helps to check that all those things that you expect to change do change.

When stress checking, it is best to use a large figure (such as 2x Sales) to ensure that you can see the desired impact in the model. It’s important to check that positive changes (such as increased sales) deliver the same direction in the dependent calculations.

It could also spot an error with positive and negative figures – it may reveal that costs need to be written as negative figures to align with the reported figures and the incumbent formulas within the model.

Most important of all, always remember to remove your stress test once complete and revert the model back to its original forecasts!

Keyboard Shortcuts for Checking

There are several keyboard shortcuts that can help you when error checking:

How to Build an Error Free Model

Speed

Taking time to build a model carefully will help avoid errors – building a model with integrity beats speed every time.

Complexity

Avoid too much complexity in one cell. If you’ve got 10 things happening in a cell, break it down into 10 separate cells or several cells. Long formulas can be hard to read and difficult to detect if the wrong calculation is used.

Consistency

The more consistent the model, the easier it is to find errors. Use similar formulas and similar construction in the model – e.g. if your formula is ‘Sales + growth rate assumption = forecast sales’ then it is a good idea to keep that formula-style consistent down the P&L. Use consistent data sourcing to help keep the model simple and readable.

Formatting

Use formatting to help you, if you have cells with hard-coded numbers input, then have them as one color, such as blue. If you’ve got cells with formulas in them, have them as another color, e.g. black. If you have cells with assumptions in, use a third color to distinguish them, or use block color for the cell where the assumptions sit.

Checking

Narrow down the universe, don’t check an entire model in one go. It is simpler and quicker to just check a portion of the income statement. Do checks in the first forecasting column before copying everything to the right for the duration of the model. If you know the formula works in this one cell, then you’ll know when you copy across it must be correct.

If the balance sheet is out of balance, there may be an erroneous input or else the calculations may be incorrect (either in one place or throughout the model). First try and identify the suspicious line item and if it can be resolved by dividing it by two. If this is the case, then it’s likely to be an issue with the signs (+/-) in the formulas.

Conclusion

A financial model needs to be accurate and error-free. To build an error-free model, construction best practices should be adhered to, and integrity checks should be applied throughout the process. It is important to prioritize accuracy and integrity over speed.

It’s crucial to conduct thorough checks including sense checks, structure checks, and stress checks. Utilizing keyboard shortcuts can aid in this process, but above all keep checking your model every time you update it to ensure it remains accurate and correctly linked.

Additional Resources

Essential Excel Shortcuts Financial Modeling

How to Build a Financial Model

Financial Modeling Interview Questions

Financial Modeling Course