Extremely large data sets that can be analyzed digitally to reveal patterns, trends and association have been defining business plans of companies from many sectors over the past several years.

In the financial sector, "big data" sets are finding some use in transaction banking in the hope banks can get better insights into their treasury operations.

Citi for example developed its Global Flows Analytics service which allows its clients to get an overview of their working capital compared to other players in the market place. By combining Citi's internal data with public data the bank is able to map out supply chain networks and essentially reveal credit risk arbitrages.

It is a similar situation in Asia where Singaporean-based DBS bank last year launched its Working Capital Advisory Programme which enabled its customers to identify and unlock trapped cash. Using its proprietary benchmarking and diagnostic tools the bank claims to have increased operational cash flows by 20-30%.

An increasing amount of C-suite (e.g. CEO, CFO) executives have been looking to invest more time and energy into understanding these datasets. According to consultancy firm Capgemini, nine out of 10 business leaders now consider data to be the fourth factor of production behind the traditional land, labor and capital.

Outside of transaction banking big data is being used by banks to help understand the behaviour of their customers. China Merchants Bank (CMB) for example, began analyzing customer data in 2012 and as a result began developing tailored made products. CMB recently decided to work with Huawei Technologies to provide its FusionInsight Big Data Solution. Deutsche Bank on the other hand used big data for risk mitigation purposes. The bank said it was able to analyze future P&L risk and market risk of the bank by referring to historical data.

However, banks looking to go down this big data path must be ready to fully commit to the often long process of effectively utilizing this information. A recent Deutsche whitepaper highlighted that there was four phases in big data adoption for companies, starting from gathering in-depth information to applying initiatives based on big data information. A Deutsche survey on client's adaptation of big data discovered that around half of them were developing a strategy for using the information. Less than 4% stated that they were actually successful in deploying these big data schemes.