Two ways treasury management can approach big data

Big data systems have dramatically impacted the way various industries operate, from manufacturing to healthcare. Take Rolls Royce. When monitoring the status of its aircraft engines it uses big data. The technology has helped the company anticipate potential hardware problems and provide early warnings for ground crews on routine maintenance.

Now the use of big data could make an impact in the treasury management realm, which has to deal with ever-changing regulatory and reporting standards, and the need for real-time financial data, which is crucial for capitalizing on opportunities and avoiding risks.

Mix this in with treasury teams often struggling for talent and you have a situation where technology can help support an under-manned team. When looking at big data usage within a treasury functionality companies can approach it in two ways.

One involves the internal push for analytical systems within an organization. First, the management board need to understand the role big data systems play in aiding the decision-making process for CFOs. Second, the data need to be sizable enough to be useful. Third, and relatedly, the data need to cover all bases to give a complete picture. Finally, there needs to be a high frequency of data to ensure data are timely and up to date.

Once established, big data can help with various treasury actions such as hedging, by allowing companies to run simulations on sudden changes on interest and currency rates. Cash management processes stand to gain from big data systems as the information can be used to develop appropriate payment terms to vendors and analyze customer collection patterns.

“To implement big data and analytics into the treasury function, organizations can look into developing a big data-aligned treasury change management agenda, covering the management model, treasury operating model and the IT architecture,” comments an EY report.   

Another way to make use of big data is to use the data of banking partners to gain market information. Over the past couple of years several banks have been leveraging on the financial data of their client base to provide individual clients or potential clients insights into how they compare against similar companies within their industry.

Industry data about days sales outstanding, days payable outstanding and cash conversation cycle are just some of the factors banks have been presenting to their clients in hopes of getting them to further optimize their working capital.