How can corporate treasury use big data to help the business maintain its competitive edge?
In 2017, professional sport has become as much about the analysis of big data as it has the physical performance of athletes.
With the margin of victory so fine, individuals, teams and associations are increasingly crunching the numbers around athlete performance, tactics and even diets, looking for that edge that will lead them to victory.
The same is true in business. The digital age has spurred increased competition and put pressure on margins. Finding that competitive edge has, therefore, become crucial.
No department is immune from this trend. Indeed, corporate treasury, with its newly found strategic importance, may be at the very forefront of this. But how can treasury begin to use big data effectively?
Look outside the department
With limited resources within treasury teams and big data being an incredibly complex space to navigate, Jose Franco, EMEA Product Executive at J.P. Morgan recommends that treasurers don’t tackle big data on their own.
“Technological innovation is reshaping financial services,” he says. “Banks are transforming how they engage with companies, what solutions and services they deliver, and how they deliver them and big data is critical to this.”
Banks such as J.P. Morgan have therefore invested heavily in their digital capabilities which means that they are able to analyse vast amounts of data aggregated from diverse sources. Banks essentially have become big data hubs.
“By synthesising this data and identifying patterns, banks are able to support corporate treasurers with actionable insights unlike ever before,” says Franco. “This data intelligence from banks can enhance tactical and strategic execution for treasurers and when used effectively, will drive improvement in the underlying business model,” says Franco.
And Franco believes that the data banks have and the insights they will be able to offer their customers will only become richer as more and more businesses leverage new digital payments, such as e-commerce and mobile. “Treasury will have greater and timelier access to vast quantities of data and more importantly, a deeper understanding of what that data means,” he says.
But where in particular can banks and treasury teams work together to derive straight insights from big data? Solving the age old problem of cash flow forecasting is one that may peak treasurers interest. Franco highlights that this is an area the bank is working on with its clients to enable them to better forecast on a real-time basis. “This has become possible because the timeliness of payments and collections has improved and with “track and trace” expanding the visibility of payments and collections,” he says.
Elsewhere, in the card space, mining spend data obtained from the business can be married with payments data obtained from the department or bank to surface insights that can be used to develop compelling offers for cardholders that will increase loyalty and revenues.
Peer benchmarking is another area where treasurers can benefit from big data analysis. This can include points of efficiency such as a comparison of a company to industry STP rates or average transaction costs, says Franco.
It is clear from just these few use cases that the value big data can offer to treasury teams is vast and it will only increase as banks and corporates hold more and more data.
But there is also danger associated with data, most notably the danger of over-relying on it. Treasury departments that place too great an emphasis on big data without correct management are likely to end up data rich, but insight poor.
As Franco explains: “The data itself needs to achieve a specific treasury objective, which remains focused on maximising shareholder value by optimising capital efficiency and managing liquidity, currency, and economic risks.”
That being said, it is an exciting space and one that looks set to fundamentally redefine how businesses and treasury departments operate. And it is a trend that treasurers cannot escape because those treasury teams who utilise big data to its fullest are likely to be those that are most successful.