Data Quality's Regulatory Vulnerability

What facet of data operations is most vulnerable to regulatory compliance issues?

Data quality management. There is now an unprecedented need to collect, evaluate, categorize, compile and report information to regulators. The January 2014 report by the Senior Supervisors Group of the New York Federal Reserve Bank highlighted ongoing issues within banks related to the need for both timeliness and quality in the underlying reporting data. The nexus of data virtue and the need for speed remains the single-most at-risk aspect of data operations today.

How prepared is the industry to comply with new regulations addressing derivatives data management issues, such as AIFMD and CFTC rules?

Across the industry-hedge funds, investment banks, broker-dealers and exchanges-the level of preparedness with respect to data quality, operating model development and technological capability remains misaligned. This is due to firms having started from dissimilar baselines. More practically, different firms have demonstrated divergent levels of organizational flexibility needed to meet the host of challenges presented by the ever-evolving regulatory context.

Has the proliferation of transaction and customer identifiers proved beneficial to data management?
It has. The legal entity identifier, unique swap identifier, unique product identifier and unique trade identifier are all unique, unambiguous and universal codes for use in financial transactions. These are aimed at enabling data aggregation across different business units of multiple financial firms, globally. They have not yet provided the transparency panacea regulators hoped for, but data managers now have a data "genome" with which they have at least commenced trying to meet mapping and aggregation goals.