The expected default frequency (EDF) model is widely used across the world in order to effectively manage credit risk. In the previous article, we understood the basics of how this model works. However, in this article, we will have a closer look at the advantages and disadvantages of this model. The idea is to enable the user to weigh the pros and cons and make an informed decision.

Advantages of Expected Default Frequency

There are several advantages of using the expected default frequency (EDF) model. Some of them have been listed below:

1. Highly Sensitive to Credit Quality: The primary reason that firms prefer the expected default frequency (EDF) model to other models is its accuracy. This model provides a much more realistic estimate of default probability than any other model. It has been estimated that the expected default frequency (EDF) model is able to predict default at least one year earlier than other models. It is this extreme sensitivity to credit data that makes this model a favorite amongst credit analysts.

2. Connected to the Equity Market: The accuracy of this model stems from the fact that this model uses data that is taken from the equity market. The competitive nature of the equity market is such that it reflects the valuation based on the most current data. This is what makes this model superior to other models. Other models rely on a periodic credit check whereas the expected default frequency (EDF) model can provide daily information about how the company is moving closer to or farther from default.

3. Considers the Firm as a Whole: Another important aspect of the expected default frequency (EDF) model is that it provides a structured approach to credit valuation. This means that it does not look at the debt of the firm as if it were somehow independent of the equity. The expected default frequency (EDF) model is based on the assumption that debt can only be paid off on time if the value creation process which primarily impacts equity prices is in good shape. Hence, it would be fair to say that the expected default frequency (EDF) model considers a holistic approach towards credit management.

Disadvantages of Expected Default Frequency

Despite all its advantages, the expected default frequency (EDF) model also has some serious shortcomings. Some of these have been explained below:

1. Subjective Inputs: Firstly, any formula is only as good as the inputs being used in it. Now, the inputs being used in the expected default frequency (EDF) model can be varied based on the biases of the person using the formula. As a result, if different people run the expected default frequency (EDF) model for the same company and for the same time period, they are likely to get very different results. This is what makes this model arbitrary and unreliable to some extent.

2. Faulty Assumptions: Just like all major theories which are used in finance, the expected default frequency (EDF) model has been built on some very questionable foundations. The assumptions used in the model do not reflect reality.

   Hence, the results given by the model cannot be applied to reality straight away either. For instance, there is an assumption made that the returns offered by the market always follow a normal distribution. However, this is not the case. Also, the model assumes that all debt has to be paid back on the same date. This assumption is also an incorrect representation of reality.

3. Private Firms: The expected default frequency (EDF) model has limited utility if the default probability of private firms has to be gauged. This is because the shares of private companies are not traded on any exchange. As a result, guessing the value of the total assets owned by the firm becomes quite difficult. Also, private companies may or may not release their periodic financial data exacerbating the underlying problem.

   Hence, it can be said that the expected default frequency (EDF) model is only useful while evaluating the credit of a handful of public companies. It cannot be used for small and medium enterprises which form the vast majority of business organizations in the world.

4. Does Not Differentiate Between Debt: Another important shortcoming of the expected default frequency (EDF) model is that it does not differentiate between the various kinds of debt.

   There can be short-term or long-term debt. Some of these debts are secured by collateral whereas others aren’t. However, the expected default frequency (EDF) model does not differentiate between them. This is because the expected default frequency (EDF) model predicts the possibility that the firm will default. Now, even if a firm defaults, it is possible that it will still pay out its priority creditors in full and only the lower order creditors will lose their money. This hierarchy of debt is not considered in the expected default frequency (EDF) model.

Hence, it would be fair to say that the expected default frequency (EDF) model is a high accuracy model. However, it has limited applications because of the shortcomings which have been mentioned above. However, it can be very useful while dealing with companies that are listed on public exchanges.