Operational risk management in the world of big data

Today, with operational risk emerging as a primary risk threat in all major economies, market players are looking to the potential of big data as a primary driver of next-generation operational risk management. Drawing on current IBM research in the field of big data, this paper shows how operational risk solutions can harness the potential of big data in its four dimensions - volume, velocity, variety and veracity - to inform risk management scenarios and analytics, fostering the development of the risk-aware enterprise to help control loss events, enhance profits and drive long-term growth.

The "high and increasing" threat of operational risk 2012 marked a seminal year in the history of operational risk management. While the 2007 financial crisis focused the attention of world markets and regulators on the interrelated challenges of market, credit and liquidity risk, in 2012 high-profile loss events impacting several major financial institutions has led to a renewed focus among regulators and industry leaders on the challenges of operational risk and corporate governance. For global markets, the significance of these loss events - measured, in some cases, in the billions of dollars-was that operational risk can impact even the strongest and best-run organizations.