Many treasury departments are busy with implementing digital use cases and the associated automation of operational processes. One use case that is very high on the agenda in financial risk management is the automation of foreign currency management. In designing a completely automated operational FX management process, the challenge is to reconcile the hedging strategy with the system landscape and the company's global reach. At the heart of this are the treasury management systems, which play a prominent role. Multi-trading platforms, in contrast, are solely tasked with the external execution and closing of trades.
This article focuses on the key stages in the process and the associated stumbling blocks. These should be identified as early as the design stage and systematically sidestepped.
Process step 1: Transmitting exposure data from upstream systems
This process starts with the transfer, processing and presentation of exposure data from various upstream systems into the treasury management system. Depending on the type of exposure, the data sources vary. Balance sheet exposure is usually extracted from the accounting ERP system; for example, in the case of SAP, tables SKA1 (chart of accounts), SKB1 (G/L account master) and T001 (companies) are of particular importance. Ensuring the complete and correct entry of all relevant accounts in this context is a major challenge, however, as there are many customer-specific tools that document contracted projects and planned sales for the automated capture of planned and contracted exposure. Given that the exposure data from the ERP systems has already been posted, it is a reliable source. When it comes to the contracted and planned exposure, however, its reliability must be verified in detail, bringing the issue of data quality into focus. Is the data sufficiently precise that the exposure can be hedged automatically? In practice, companies also have built-in controls to alert them about any exposure that has changed significantly since the last upload, for example. If the exposure exceeds a certain threshold, a staff member will perform a more detailed check, and the exposure will be released to be hedged for the time being. The upload then takes place in predefined intervals using jobs and is usually transferred via sFTP as a CSV file. Naturally, if a system is able to communicate via an Application Programming Interface (API), this should be preferred. In this step, it is important to already include certain parameters that may be needed for downstream functions in the process, such as business line or project information.
Process step 2: Generating internal orders based on the hedging strategy
After processing and displaying the exposure in the treasury management system, general settings in the system and extended master data now determine the further process flow. After all, the system needs to know how to handle the relevant exposures for the respective company and currency. For the fully automated process, additional parameters are required in addition to the standard parameters. The following is an extract of the broader issues:
At what time on what day will the automated process run? Are there different time zones that need to be taken into account here? Which entity receives the orders created by the operating entity and trades them externally on the market? Which entities may not trade using the in-house bank entity? On which dates of the month will the derivatives be placed? Will there be a netting of the position to be traded externally? How should the system behave if the netting amounts to 0? Is hedge accounting relevant?
These sample questions illustrate the complexity of setting up the treasury management system for such an automated process.
Process step 3: Integrating the trading platform and handing over the completed trades
After the internal orders have been processed through various stages, the next step is the integration of multi-trading platforms. Before sending the automated orders to the trading platform, they should be subjected to a built-in check, which tests parameters such as the size of the nominal to be traded so as to act as a "last wall of defense" to prevent any potential miscalculations. Another useful step in this process is an automated check of the counterparty limit. One question in the conceptual design is how much of the nominal to be traded should be charged to the existing use of the potential counterparties. Essentially, there are two ways to integrate the platforms into the automated process: The comparatively classic way via XML file transfer or the fastest way via a fixed connection, i.e. an API. In any case, if the treasury management system and the multi-trading platform are able to communicate via APIs, then this is the preferred way to go. In this way, the entire workflow of uploading the exposure, creating the order, closing it on the multi-trading platform and
it back into the treasury management system can be completed within 30 seconds for currencies with Auto Pricer. If a highly international setup needs to be accommodated in the design, then it is well worth connecting several multi-trading platforms due to strong regional differences in availability. We are increasingly observing the trend for the treasury management system to take over the functions of the trading platform, with only the execution running via the platform. Once execution has taken place, it is advisable to orchestrate the transfer of trades in detail based on previous orders and to clearly define the internal components and views. In this regard, topics such as the automated calculation of internal margins in basis points are also relevant for many corporations.
Automating operational FX management brings about a significant decrease in the workload for treasury staff. On the journey to this full automation, however, there are plenty of aspects and issues to consider. These range from deducting the exposure from the upstream systems to creating the internal orders based on the hedging strategy and integrating the trading platform. The project team's efficiency can be significantly increased by identifying and overcoming the challenges as they arise, thereby ensuring that the project reaches the operational stage.
Source: KPMG Corporate Treasury News, Edition 115, October 2021
Authors: Börries Többens, Partner, Finanz- und Treasury- Mangement, KPMG AG; Mattis Schwind, Manager, Finanz- und Treasury- Mangement, KPMG AG