Last month, I attended CeBIT for the Code_N event, a unique platform for innovative startups and entrepreneurs to show off new products and services. This year, the focus of the event was “driving the data revolution”; the 50 finalists presented innovative big data solutions across a wide variety of industries.

I was given the opportunity to present the keynote speech in the area of financial services. With so many exciting things happening in this area, there was a lot to talk about.

One of the key messages was about the current state of big data in financial services. While over 90% of financial services companies are planning to enhance their big data capability in 2014, only 9% now have a Hadoop solution in production (across all industries, the numbers are significantly lower). This highlights that while these new technologies have a lot of promise and banks easily recognize their value, they are not easy to implement and it is taking time for the banks to adopt them.

The use cases in both retail and investment banking are clear. In retail banking, the key lies in centralizing customer data so that the bank can more effectively understand their clients, provide a customized service, and help avoid fraud. In investment banking, the key data is not customer data, but trade data. By consolidating a rich, high quality trade history, an investment bank is able improve its P&L calculation, its market and credit risk measurement, and its capacity to produce regulatory reporting, e.g. the Volcker Rule, amongst many others.

What banks have done so far, though, is an evolutionary approach. By applying big data technologies to existing processes, they have made them more efficient. This is great, as it improves operational procedures and SLAs, but it also provides the capability to make new calculations and gather insights about the bank’s business.

However, I think the greatest benefit for investment banks will come by using these new technologies to revolutionize and de-silo the bank’s IT systems. Distributed storage and distributed computing give the banks the capability to finally centralize all their data and therefore reduce data and process redundancy which is so common throughout the sector. By having consistent, golden-sourced data, cost effective data management, and a unified view of customer, trade, and position data, the bank will have a more accurate and complete view of their business.

This will be not just an evolution, but a revolution.