What is the overall impact of identified risks on the company and, in particular, how great is the threat to the company as a going concern? This question can only be answered if the effects of the risks are determined using a suitable procedure, taking into account their respective probability of occurrence, their damage distribution and their interactions with one another. An aggregation of all relevant risks is therefore necessary. The objective of risk aggregation is to determine the overall risk position of a company, particularly with regard to these two variables, and to determine the relative importance of the individual risks, taking into account interactions (correlations) between these individual risks.
The assessment of the overall scope of risk enables a statement to be made as to whether the risk-bearing capacity of a company, as mentioned above, is sufficient to actually bear the scope of risk of the company and thus to ensure the company’s continued existence in the long term. If the existing risk volume of a company is too high in relation to its risk-bearing capacity, additional risk management measures will be required. For risk aggregation, the so-called “Monte Carlo simulation” is used. Here, the effects of the individual risks are first assigned to specific items, e.g., in the income statement or the balance sheet.
After the above-mentioned allocation of the effects of the individual risks to the P&L, several thousand risk-related P&L scenarios are calculated for a fiscal year. Thus, in each simulation run, a value is obtained for the target variable under consideration, e.g., sales, profit, or cash flow. The totality of these simulation runs can be described as a “representative sample”, showing a large number of possible risk scenarios for the company. Subsequently, it is analyzed which manifestation of the target variable occurred how often, allowing aggregated probability distributions to be derived.
With the result of the simulation runs, aggregated probability distributions are now available which directly indicate the probability (e.g. 95 %) of not falling below a certain minimum profit to be achieved or not exceeding a maximum acceptable loss – in other words, a kind of maximum loss analysis. This value is also known as the deviation value at risk (DVaR). The DVaR is the maximum loss value that will not be exceeded with a probability of 99% in an observation period of, for example, one year.
The calculated probability function of the profit naturally has a direct impact on the equity to be expected in the future: by offsetting these calculated profits and losses against the previous equity, the latter can be forecast for the future.This now makes it possible to determine the equity requirement and the probability of over-indebtedness (and thus to conclude on an appropriate rating). A similar approach is also possible for liquidity.
