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Backtesting liquidity plans

Backtesting liquidity plans

Just how exact was your planning?

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Börries Többens

Partner, Audit, Finance and Treasury Management, Finance Advisory

KPMG AG Wirtschaftsprüfungsgesellschaft

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liquidity planning

Have you ever backtested you liquidity planning and analyzed the discrepancies a bit closer? No? Most likely, most companies are in that position.
The truth is that existing liquidity plans often digress strongly from what happened eventually. Identifying the reasons and drivers for such discrepancies is usually not considered to be part of Corporate Treasury’s daily business, and sometimes the reason for a lack of backtesting lies in the scarcity of resources. However, looking back can sometimes be quite illuminating and make interdependencies even clearer. A systematic backtesting will divulge things that are unusual, anomalies and areas where the company could do better in future liquidity plans. So in fact, looking back can be quite useful for the future.

How accurate does liquidity planning have to be?

One of Treasury’s core tasks is to ensure the company's continuous solvency. For this, determining the planned liquidity is indispensable. Generally speaking, it is sufficient to forecast the liquidity balance at the level of the corporation in order to quantify the financial leeway in consideration of financing mechanisms.

Discrepancies between the plan and the actual values are perfectly normal when planning a corporation’s liquidity. It is practically impossible to prepare a plan that is of such accuracy that the predicted plan values are met exactly. And yet, a certain exactitude is elementary for any corporation in order not to drift off into insolvency but also to use the available capital efficiently.

In practice, liquidity planning often has to meet those very requirements; ideally, the plan’s quality should be adequate. One could certainly discuss just how good the quality of the planning has to be; however, the reason for an unsatisfying liquidity plan can usually be found in methodical weaknesses in how the processes are applied in the day-to-day business.

Treasurers often grapple with on-going quality assurance when it comes to drawing up the liquidity plan. Observations show that there are often only few validation possibilities because the current data reports lack detail. This makes continuously improving the liquidity plan based on variance analyses practically impossible.

Another challenge in the liquidity planning is transparency. In practice, the underlying reasons for discrepancies and outliers can often not be traced back to their origin. Unfortunately, a reasonably exact analysis at the level of individual legal entities and liquidity positions would be important for a transparent liquidity planning. Planning processes that have grown historically and heterogeneous system landscapes also make things more challenging. All of this makes taking decisions when managing liquidity all the more difficult.

Finally, meeting the expectations of their audience is also of significance for reports. The planning method and system landscape very often only partially cover the stakeholders’ expectations of the report.

Conditions for statistical analyses

One of the basic conditions for a quantitative analysis of the plan’s quality is the availability of data at sufficient granularity for both planned as well as actual values. The longer the period of the data, the more exact the ensuing analyses will be. As a rule, planned and actual data should exist for a full calendar year, i.e. a complete planning period.

Normally the planned cash flows come from the pertinent liquidity planning system or from the Controller’s budget. Ideally, actual data are readily available, for instance from the Treasury Management System, the ERP system or the banking tool. As an alternative, actual data may be compiled from Accounts Payable/Accounts Receivable (AP/AR) as well as HR and Treasury payments.

Backtesting approach

A quantitative backtesting can analyze the discrepancies between planned and actual data from the liquidity planning in order to systematically identify deviations at the level of legal entities, liquidity positions or periods. The statistical analysis of discrepancies and abnormalities and the related interpretation of the results can then be categorized according to different indicators, for instance systematic deviations, seasonal factors, one-off effects, etc.

An important category are systematic deviations. This involves identifying ongoing planning deviations that indicate systematic planning errors (example: planned amounts that are constantly too low or too high for a specific liquidity position or legal entity for a specific period).

Seasonal factors are indicators from repeated patterns of discrepancies between actual and planned figures, which indicate incorrect value date assumptions in the planning.

And finally, there are the one-off effects, which can also be measured using a key figure as an indicator. One-off effects describe the identification of individual, exceptional deviations between planned and actual figures, which are caused by frequent, exceptionally low or high plan values within a period (depending on the number of standard deviations).

Together, these indicators help analyze an enormous mass of data from the liquidity planning at an even higher granularity. This allows for a more in-depth interpretation of the results and relevant recommended actions.

Results

In order to obtain viable insights from the statistical analyses for both the liquidity planning and the corporation itself, the analyses have to be interpreted correctly and put into the context of the company-specific characteristics.  At first, the mass of data (depending on the liquidity plan’s granularity) may make an analysis of the results seem rather complex. However, all of this data is important in order to draw the right conclusions from the backtesting.

By implementing the deviation indicators listed above, the jumble of numbers in the liquidity planning suddenly becomes absolutely transparent. Seasonal factors, one-off effects and systematic deviations can be quickly identified and analyzed. These indicators, in turn, also allow an interpretation with specific actions in order to remedy the reasons for the high discrepancies in the liquidity planning.

Qualitative dimensions

In order to analyze and eliminate any deviations between an existing liquidity plan and the actual figures, backtesting is a comprehensive approach. Very often, the reasons for planning inaccuracies exist already much earlier before the planning data is even generated. Another dimension is necessary in order to look at a liquidity plan holistically and to uncover all of the potential for improvement regarding the planning’s quality: a qualitative review.

The basic elements of a qualitative review are:

  • Data (entry in the database, evaluation of the quality of the data)
  • Methods (direct versus indirect approach, definition of planning parameters, plan’s structure of liquidity positions, planning period)
  • System-related (technical implementation, functionalities of IT systems, connectivity between interfaces)

If one looks at the qualitative and quantitative (backtesting) dimensions of liquidity planning overall, you can make detailed observations on planning quality, deviations and their causes.

Conclusion

As mentioned at the beginning, looking back is good practice for Corporate Treasurers when it comes to their liquidity plan. Backtesting can take on different forms and levels of detail. What is of importance is that the insights are interpreted correctly and used in future liquidity plans. Making plans more accurate is also good for the corporation’s solvency. Another advantage is that the structured knowledge of the interrelations allows for a better scenario analysis and simulations. This enables a more precise analysis of the liquidity requirements and the necessary liquidity buffer. Besides allowing a more efficient allocation of capital, an increase in transparency on liquidity in the corporation is the most obvious advantage of backtesting.

Source: KPMG Corporate Treasury News, Edition 102, June 2020

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