Although many banks are embracing the new era of big data (this week BBVA acquired Spanish startup Madiva Soluciones) and are working hard to analyse and use vast troves of information, they are still having trouble applying the results to improve risk management, says the SAP-sponsored study.

Currently, just 42% of respondents have the ability to integrate, manipulate and query big data when creating risk profiles, although 47% plan to invest in these tools over the next three years. The proportions are slightly lower for advanced big data tools, such as predictive analytics and data visualisation: 41% use them now and 44% expect to obtain them during the next three years.

Liquidity and credit risks remains a central concern, reflecting the increased risk exposures that banks face in the wake of the financial crisis. Among the 208 execs at retail, commercial and investment banks around the world who were quizzed for the report, 46% say that the most promising big data opportunity is being able to link seemingly unconnected external events in real time. In a related finding, 44% cite the ability to predict the amount and cost of capital required in stressful market situations.

The most useful current application for big data is risk management activities aimed at preventing credit fraud, with 45% of survey respondents saying it can facilitate near-instantaneous customer contact to verify suspicious transactions. The second most useful big data application, according to respondents, is guarding against loan defaults, and 45% said the best opportunity lies in monitoring borrower behaviour to anticipate and respond to this type of risk.

Erica Klein, report editor, says: "Our survey demonstrates that banks are embracing big data and then investing in related analytic tools. But there are still face challenges in applying the results to deliver superior risk management performance—particularly in relation to liquidity and credit risk."