OFR Deputy Director Crowley Discusses the Benefits for Companies and Regulators of Quality Microdata and Financial Data Standards
Published: July 13, 2016
Well-designed “microdata” can help companies and regulators monitor risks. OFR Deputy Director Con Crowley presented a paper on the topic this week at a European Central Bank conference.
Financial microdata describe entities, instruments, transactions, or products. Microdata contrast with aggregated data. For example, the total assets of a mutual fund are aggregated data. The fund’s holdings of specific stocks and bonds are microdata.
In principle, financial firms and their regulators should use the same microdata to create aggregated data. The companies can use those data to manage their risks, while the regulators can use them for oversight and to monitor financial stability risks. When firms and regulators work together to set standards for data, everyone can win.
The benefits are consequential: Companies can provide accurate data to regulators more easily if they already gather those data in the course of their businesses. Companies also benefit if their back-office systems can easily produce, link, and integrate information. Regulators benefit by using the same data companies use to manage their risks.
To be sure, there are obstacles: Many companies have not updated their information technology after mergers. Legacy systems might not communicate well with other systems. Data are often badly structured, even among the biggest companies. Much of the data available before the 2007-09 financial crisis were opaque or could not be aggregated across companies.
Data standards help overcome those obstacles because they give data users a common language and definitions that promote data quality. The OFR works closely with both companies and regulators to develop and improve data standards. This kind of collaboration is essential to get the most out of data.
Regulators and companies have improved the quality of financial data since the crisis. One example is the legal entity identifier (LEI), which identifies the parties in a trade, provides information about positions, and promotes risk management. The paper discusses the OFR’s work advancing the LEI and other data standards. The LEI case study shows how public-private cooperation leads to better standards.
A second case study about derivatives data shows how lack of mutually agreed standards reduces data quality. A third case study of an OFR data collection pilot shows how data become hard to use when they do not apply available standards or when company systems do not support such standards.
Richard Berner is Director of the Office of Financial Research.