Michael Shashoua: Identification, Linkage and Risk

The links, or lack thereof, between risk management and data management, have been the focus for some recent pieces of reporting and analysis in Waters’ sibling publication, Inside Reference Data. Each item on the growing list of regulations—Solvency II, Fatca, IFRS 13, Basel III and the legal entity identifier (LEI) standard—was designed with some kind of risk prevention or mitigation in mind. These rules have made financial industry data managers think about the need to improve data quality and data hierarchies, along with the construction of single, comprehensive views of data—single authoritative sources, to be more precise.

The identification piece certainly is a key to achieving this desired quality. One service provider, Alacra, which offers workflow tools, has produced a model that could be used with LEIs—a database called the Alacra Authority File. This database already includes agency-issue identifiers, International Securities Identification Numbers (ISINs), Stock Exchange Daily Official List (Sedol) identifiers, ticker symbols, Markit Red Codes, and other identifiers. But adding the LEI to the Authority File would be a capstone addressing regulatory status changes driven by corporate changes. Those are the events that create the very risks that drove the creation of the new rules to begin with.

Beyond the Obvious
Being able to track those changes would complement improvements in data quality, hierarchies, verification, validation, and linkage. The importance of good organization of reference data certainly is apparent at JPMorgan, which is realizing a data management improvement project as part of a merger of its securities services and investment bank operations into one group. The project, according to Ludwig D’Angelo, New York-based executive director of JPMorgan Corporate and Investment Bank (CIB), is expected to be complete by early 2014. It will yield benefits in higher data quality and easier data management operations.

JPMorgan recognized that having the right data hierarchies in place is a “fundamental building block for effective risk management,” says D’Angelo. In fact, effective risk management requires a single, comprehensive view of data, he adds.

In keeping with the significance of LEIs that Alacra identifies, D’Angelo also says that the LEI is a good starting point, even though more standardization is needed. Getting the LEI in sync with all the other identifiers already out there has to be part of achieving a firm-wide, consistent and reliable single view of all data.

There is a range of data management concerns that have to be compared and weighed up as part of a bigger reference data picture.

The Big Picture of Data
Standardization also stretches beyond just entities, into asset classification, according to D’Angelo. Any comprehensive risk analysis also has to include accurate asset classification, as well. When linking data, risk managers must know the pricing on listings, and whether those listings are used in options contracts, according to Marc Alvarez, senior director of reference data infrastructure at Interactive Data. That’s an example of making sure asset classifications are correct.

Getting those classifications correct in turn supports a better assessment of likely returns over time. So, aside from eliminating the risk of holding securities that are being affected by corporate changes that attract greater regulatory scrutiny and oversight, this more subtle form of data management is also indispensable to risk management.

Identifiers, asset classifications, data quality and consolidated views are all inextricably linked—to each other, to risk management, and to regulatory compliance. It’s not just the LEI that has numerous considerations still to be dealt with—there is a range of data management concerns that have to be compared and weighed up as part of a bigger reference data picture.