Finance itself is a complicated field. It is difficult to understand the nature of relationships between various financial variables which finally culminate in the financial statements. However, financial modeling is considered to be one of the most complex tasks, even in the financial field. There are several reasons behind this assumed complexity. Some of the reasons have been listed below in this article.

Backward Looking or Forward-Looking?

Normally, there are different branches of finance where the calculations are either forward-looking or backward-looking. For instance, financial reporting is all about backward-looking calculations. It is all about keeping score of what happened in the past and reporting the same to different stakeholder groups viz. tax authorities, shareholders, suppliers, etc.

At the same time, managerial accounting and costing are forward-looking. This is the financial process where budgets are created in order to keep track of events which are likely to happen in the future. All the figures mentioned in these plans are expected figures and not actual figures pertaining to past events.

The problem with financial modeling is that it has to be backward-looking as well as forward-looking at the same time. Some elements of financial modeling have to be taken from financial reports, whereas others have to be taken from costing plans.

Financial Modelling: A Hybrid between Backward Forward-Looking Statements

During financial modeling, output variables are determined. Then steps are taken to define the relationship between output variables and their underlying causal factors. For instance, revenue can be considered to be an output variable which a financial modeler may be interested in.

A financial modeler is required to evaluate past financial statements of the firm. This is done to ascertain the hidden drivers which influence revenue growth. The chain of causality is seldom simple.

The causal factors which affect revenue may themselves be affected by other causal factors. Therefore, a financial modeler is supposed to look at the backward-looking financial statements with great attention to detail. This needs to be done to unearth the hidden parameters which affect the actual numbers. This is what makes financial modeling much more complex as compared to financial accounting

The financial modeler has to look backward to unearth the causal links and create a model. However, once this model is created, the financial modeler now has to look forward. This is because after the inputs have been clearly identified, the financial modeler is supposed to identify the possible variations in these inputs.

It needs to be ascertained whether the inputs will vary all at once or whether only some factors will vary at the same time.

The financial modeler is then supposed to predict the values of important variables such as interest rates, tax rates, and so on. These assessments have to be made based on the knowledge of current affairs. Some extreme scenarios also need to consider for stress testing purposes. This is what adds to the complexity of financial modeling.

Financial Modelling: Underlying Assumptions

Another problem with financial modeling is that there a lot of assumptions which are hidden and which the modeler may not even be aware of. Some of these assumptions are based on empirical values and hence may not be completely true. This is because these assumptions could be found to untrue if black swan events occur.

For instance, prior to subprime mortgage, all financial models were built on the assumption that loan defaults could not happen in large numbers all across the countries. This is the reason that mortgages from Texas would be pooled along with mortgages from other far-flung states like Wisconsin since it was assumed that all the mortgages couldn’t go bad at the same time.

However, when the subprime mortgage actually occurred, home prices started falling all across the country, and this led to mortgage defaults all across as well. The models weren’t really equipped to foresee this situation because of the underlying assumption. As a result, there was carnage in the markets!

Financial Modelling: Level of Detail

Another issue which increases the complexity of financial modeling is the level of detail which needs to be built in the model. Ideally, decision-makers would like to view the information in as much granularity as possible.

Therefore, ideally, the model should have the ability to allow the user to drill down the data from the aggregate to the granular level. This ability needs to be designed by the financial modeler. Therefore a financial modeler is expected to have a better understanding of how the numbers work at a bird’s eye level as well as at a granular level.

The above-mentioned points just provide some of the highlights about what makes financial modeling challenging. Also, it needs to be understood that apart from understanding the financial details, a financial modeler also needs to be an expert in using technology. This is because understanding the process is not enough. It needs to be expressed in the form of a reusable model, and that requires the use of technology as well. Since the job requires a person to be an expert in so many fields, financial modeling jobs are some of the highest-paying jobs in the entire finance domain.