Capital markets firms are seeking to drive cost efficiencies through the use of Big Data analytics and managed services, as they face the twin obstacles of regulatory compliance and a restrained business environment.

“Regulatory change driving economic pressures driving institutions to lower cost and maintain agility Historically, technology initiatives started with front office electronic trading outsourcing to drive latency down,” said Roji Oommen, senior director of financial services at Savvis. “However, those are relatively small footprints, and those environments are a relatively insignificant proportion of total IT spend. We hear a lot of feedback from customers that they need to do something that significantly moves the dial. We’ve heard anecdotally that a lot of smaller niche players don’t have the scale to significantly move the dial.”

Savvis, which will become CenturyLink Technology Solutions on January 21, 2014, is investing in infrastructure and expanding its footprint to help firms deal with rapid regulatory change and information security.

Savvis has launched Big Data Solutions, a suite of managed hardware and software services for optimizing data storage, integration, retrieval and analysis.

The first set of services is called Savvis Big Data Foundation Services – a suite of standardized, fully hosted and managed services designed to help organizations glean the most value possible from all their data. The suite includes Savvis’ managed services for Cloudera and MapR platforms based on Hadoop.

Increasing competition and regulation are putting pressure on financial services firms’ revenue growth. To uncover opportunities, many firms are increasing their investment in customer analytics to glean insights from detailed information about customer accounts, demographics, and transactions.

“The ability to process larger, more detailed data sets can enable analysts to observe commonalities that will improve predictive and prescriptive analysis,” said Bill Fearnley, senior analyst at Celent’s securities and investments group. “User-created content such as social media interactions and web information, when combined with the firm’s existing data, can provide a broader picture of the customer.”

Many firms are also looking to add new sources of unstructured data to improve their knowledge of their customers as well as investor and market sentiment.

These can be converted and imported into existing customer analytics data warehouses using open source tools (e.g., Hadoop and MapReduce) to perform the extract-transform-load (ETL) process used to convert and load data.

“We also seeing open source big data and analytics tools which are acting as a complement to existing analytics and financial services systems,” said Fearnley. “If you want to add new data types, there are a number of technologies that can be used to capture that new data for much less than traditional analytics tools.”

The open source tools can capture huge amounts of new data; perform some preliminary analytics and data conversion and reduce huge data sets to just what’s needed for customer analytics, according to a Celent report. Many leading database providers such as IBM, Oracle and SAS provide software connectors to help load data from open source tools and import this data into existing relational databases.

“A lot of financial services firms are taking this unstructured data, using these open source tools to aggregate the data, and adding these new data sources into their existing analytics system,” Fearnley said. “So we believe that the open source movement is complementary to a lot of the analytics tools that are used today in the wealth management and capital markets space.”