Evaluating the Quality Chain

As risk management concerns have driven all the regulation that financial firms have been dealing with over the past two years, data managers have been tasked with identifying, processing, recording and managing more types of securities data and in greater amounts.

With some major initiatives such as IFRS 13 and the legal entity identifier (LEI) in place, or nearly so, and others, such as Solvency II, the Foreign Account Tax Compliance Act and even Basel III well on their way, managers are looking at data quality, aggregating and leveraging data throughout their firms, and setting asset classification standards as ways to better support risk management with data. The Basel Committee on Banking Supervision has also recently set principles addressing risk data aggregation and reporting.

"Many organizations are still trying to become compliant by chasing their own tails without addressing the fundamental issue of everything they do, which is bad quality data," says Vangelis Tsianaxis, managing consultant in the enterprise risk services unit of Deloitte. "There is no compliance data, risk data or marketing data. There are data assets that need to be managed in order to enable running the business and its different functions."

Data Links and Real-Time Delivery

Risk managers' greatest concern is aggregating all their portfolios internally, says Marc Alvarez, senior director of reference data infrastructure at Interactive Data. They have to take steps to verify and validate data-while bound to have a "full universe" of data available, they only need small subsets of that data at any given point in time, he adds.

Many organizations are still trying to become compliant by chasing their own tails without addressing the fundamental issue of everything they do, which is bad quality data -- Vangelis Tsianaxis, Deloitte