Big data is big news. George Osborne's announcement of the London ‘smart cities' project and the recent McKinsey report have thrust big data into the limelight.

While certain sectors have only just begun to address the issue, the financial services industry has been analysing massive datasets for years. However, while financial institutions have arguably made progress in exploiting data for improving CRM, maximising operational efficiency and detecting fraud, the same perhaps cannot be said for managing risk.

While a select few are manipulating data effectively for risk management - HSBC, for example, is now deploying advanced business analytics to help enable a firm-wide approach to risk- I would argue that more than two years on from the collapse of Lehman Brothers, the industry as a whole still has a long way to go.

The Basel III framework is a good example of understanding risk through better use of data, but it's difficult to apply this uniformly across all types of institutions. In the first instance, regulators need to understand how a bank's business model works in order to account for the structure of each institution; the type of business it conducts; the counterparties it does business with; and the level of transparency in its operations. However, for regulators to do this banks need to be able to gain a comprehensive view of data in order to empower intelligent decision making.

Ultimately, there needs to be a ‘Big Rethink' about how the data deluge is dealt with right across the industry. Arguably this is only possible by getting banks, regulators and the relevant associations to sit around the same table in order to iron out a common approach and to define clear standards for data.