A cash management trend to watch: big data
For many of us, the concept of big data — extremely large sets of structured and unstructured data that may be analyzed by computers to reveal trends — can be intimidating. It’s like trying to detect meaningful patterns in the infinite number of stars on a clear, dark night. But big data is an emerging asset for many of our business clients and will likely grow in effectiveness.
The array of what businesses can do with all the data they collect is amazing, such as predicting buying habits of customers, segmented by age and geography. The data sets also can help with key business applications, particularly in corporate treasuries.
Uses of big data could extend to cash flow forecasting, foreign exchange, and liquidity planning. The data can help corporate teams move beyond the manual aggregation of hundreds of Excel-like templates to view potential cash flows in a more centralized way. And what if the data patterns could help your company make more advantageous decisions about timing payments to certain vendors? The possibilities are appealing.
Harnessing big data for a range of cash management applications may not be widespread yet, but I’ve talked with clients and many peers in the industry who are on board. Some of the available technology allows software programs to learn and update continually and develop their own logic. This necessitates having a treasurer and relevant staff nearby to guide and drive the tools to meaningful conclusions, and it may involve corporate infrastructure changes and executive buy-in, which takes time.
The appetite is growing, nonetheless. The International Data Corporation (IDC) predicts revenue from the sales of big data and business analytics tools to corporations will increase more than 50% between 2015 and 2019, as reported by InformationWeek.
Some clients of both Bank of the West and BNP Paribas already appreciate the value big data can bring to analyze flows in payment processing and inventory. One example, a leading online fashion platform, uses a dedicated team of mathematicians and physicists developing data analysis models to help with decision-making and boost learning on such variables as the impact of weather on sales.
Another client, a global paint company, is using big data to analyze varying flows in payment processes. It enables the corporate treasury team to identify payments that use the wrong instruments and take action to correct them.
These examples of applying machine learning suggest what’s to come as businesses innovate to make their cash management processes more efficient. It’s an exciting trend to watch!
For more information on this and other innovations, visit the Journeys to Treasury site.