Data analytics: transforming the role of the treasurer?
March 05, 2019
Have you started to consider how data analytics can better help solve your everyday treasury problems leaving you freer to work on more interesting challenges and opportunities?
From what I have seen, even though there is interest, the Treasury community is perhaps lagging behind their peers in finance, marketing and strategy in using data analytics. For example predictive analytics is now commonly used to better understand consumer trends in many markets and as a tool to help pinpoint areas for investment.
So how might the Treasurer use data analytics tools effectively?
Problem 1: Unclear real use of cash by businesses restricting the ability to release cash for investment or repayment of debt
For some treasuries, it’s an ongoing battle with the businesses to reduce cash balances held without introducing a fully automated sweeping solution which may be time consuming while potentially facing regulatory and operational constraints. With the use of software, it’s possible to study key variables over time – historic balances, intercompany and third party payments and receipts, forecasts versus actuals – to understand the real levels of cash required in each business and hence prove to local management that they can operate with less cash. The payback for such an exercise can be quite significant.
Problem 2: Ambiguity around whether Foreign Exchange (FX) hedges were actually required to meet forecasted foreign currency needs
One of our clients, with complex forecasted foreign currency flows, wanted to understand to what extent their FX forward transactions were actually being used to manage risk. Tools were used to compare historical FX hedges with actual cash flows and balances over time to understand historical discrepancies between actual and forecasted FX cash flows, time lags of currency movements and whether any FX hedges were not used. With this they were able to amend their hedging strategy and reduce its associated costs.
Problem 3: The real cost of banking is often unknown
Owing to the complexities of banking charges and the ambiguous recording of these on bank statements and in internal finance systems, it has in the past been very difficult to fully analyse whether corporates are paying too much. Now data analytics tools are being used to more efficiently analyse statements against transactions to help the treasurer gain better visibility so that focus can be on where costs are highest. Visible fees are also a useful bargaining tool for re-negotiating bank fees or supporting a business case to change relationship banks.
The above are just three examples where FinTech solutions can assist the Treasurer. Of course you don’t necessarily have to invest in new technology to take advantage of data analytics. I believe that use of spreadsheets with applications of basic variance or statistical analysis can produce meaningful results. However, one note of caution, in my experience, you must ensure adequate time is spent understanding the nature of all data to be analysed and then cleansing unwanted data. Without this significant pre-work your results may be meaningless.
Camila Montagni | Manager