Excel vs. Automation in Financial Modeling

What Software is Used in Financial Modeling?

Before we discuss Excel vs. automation in financial modeling, let’s take a look first at how software is used to build financial models. Financial modeling involves creating an abstract representation of an actual or projected financial event. Thus, a financial model is a mathematical tool that can be used in software like Microsoft Excel to help in designing the abstract model.

Financial modeling is important to businesses because it can help to predict how a company is likely to perform financially in the future. To predict financial performance, a financial modeler utilizes the company’s historical performance while making assumptions about the future.

There are two ways of doing financial modeling. The traditional way involves using Excel spreadsheets. However, companies are starting to embrace the concept of automating the task of financial modeling.

Excel vs. Automation – Building and Designing Financial Models

When designing financial models, one needs to make many tradeoffs between using Excel and other software that automates most tasks. Financial analysts and other users of financial information continue to debate on which one is better. Let’s see the differences between the two:

1. Customization

Given that Excel is manned by a human modeler, it offers a great deal of customization. The fact that Excel allows one to design a model from scratch means that individuals enjoy a lot of freedom in structuring the model the way they want. Also, they can format the model based on the needs of the business for which they are modeling.

For example, if there are some asset-specific features that need addressing in the model, those may only be achieved using Excel. In contrast, using specific financial modeling software may limit the scope of customization, as it is already pre-programmed.

2. Structured outcome

The best time to use financial modeling software is if one is dealing with a specific structure for a model. In such a way, the human modeler can reduce the likelihood of making errors as most of the tools they will use are programmed to prevent errors.

On the other hand, the likelihood of making errors when using an Excel model is higher than with an automated system. So, if there’s an emphasis on standardization and accuracy, the better approach is to use financial modeling software.

3. Development of analytical skills

However, if a modeler is more interested in understanding a business, an Excel model is much better. This is because using Excel involves going through the meticulous process of calculating pretty much everything. Although tedious, the act of computing different financial records really helps one to understand the business better.

Now imagine that the modeler was using a software program instead. The program would use the company’s financial statements, capital structure, and forecast, and then reveal a net present value (or a different desired output) spontaneously. Even though it saves time, it would not teach the modeler much about the business itself.

Learn more about different ways of utilizing Excel to model financial statements.

4. Risk analysis

Although specific modeling software doesn’t necessarily enlighten a modeler about a business, it is generally better than Excel with regards to risk management. Even though one can run a sensitivity analysis on Excel, the whole process will be completely manual; hence, increasing the probability of making errors or observing incorrect results. Risk analysis methods like sensitivity analysis and Monte Carlo simulation are more easily performed with financial modeling software, which offers higher precision.

5. Logical interpretation

To be able to forecast accurately, a financial modeler needs to apply a specific logic to determine an outcome, and this may only be possible in Excel. With an Excel spreadsheet, the analyst can examine a company’s data, make certain assumptions, study the relationship between financial statements, and ultimately compute the formula.

There’s a need to assess the relationship between the dependent variables in order to apply logic, and that can be very hard to achieve when using software. Since certain financial modeling software uses built-in tools of logic, it’s not always possible to analyze the flow of individual operations.

6. Visual representation

Visual representation makes up an important part of financial modeling. While Excel is very good at representing data in graphical form, there may be other, third-party resources that are even better.

7. Handling complex data

Although Excel has proven to be an effective method thus far, there are a few areas where it falls short, particularly in handling complex sets of data. However, with financial modeling software, one can compute multidimensional and large sets of data without any difficulty. Most programs allow modelers to create and switch the rows and columns layout of the model based on the situation at hand.

Should companies automate financial modeling?

Whether financial modeling should be automated or not will depend on individual company needs. As an example, small businesses that deal with small data sets and don’t need very structured outcomes should use Excel because it gives the owner insight into their operations.

However, if a company is dealing with diverse and large data sets or is more interested in precision and risk management, then automating its financial modeling is the best option.

Additional Resources

CFI offers the Financial Modeling & Valuation Analyst (FMVA)™ certification program for those looking to take their careers to the next level. To keep learning and advancing your career, the following CFI resources will be helpful:

• Documenting Excel Models Best Practices
• Free Financial Modeling Guide
• Risk Management
• Sensitivity Analysis
• See all financial modeling resources
• See all Excel resources