Guest blog by Robin Doyle, Managing Director, Office of Regulatory Affairs, J.P. Morgan Chase & Co.
In May 2018, J.P. Morgan Chase published an article on the topic of data standardization, “Data Standardization – A Call to Action.” The article called for the financial services industry, global regulators, and other stakeholders to make progress on addressing current deficiencies in financial data and reporting standards that would enhance the usability of the financial data for informational needs and risk management, as well as with innovative technologies like artificial intelligence and machine learning.
The article called for both global and national regulators to review the state of data and reporting standardization, and to take action to make improvements within these areas. Within the United States, the need for such a review is urgent. The U.S. regulatory reporting framework is fragmented and there is a lack of coordination across agencies resulting in reporting requirements that are often duplicative and overlapping. Each agency is focused on collecting data in its own way, with its own definitions. This leads to higher cost for financial institutions to manage compliance and poorer quality/comparability of data for both regulators and firms.
Specifically, whenever new data or a report is requested with slight differences in definitions or granularity, it triggers a new reporting process, including reconciliations to other reports and U.S. GAAP numbers, as well as obtaining corresponding sign-offs and attestations. The lack of common data standards and reporting formats across the agencies make reporting complex and incomparable. Separate supervisory and examination processes occur as a result of the multi-agency, multi-reporting framework. Here are two areas that highlight the issues at hand:
1. Top Counterparty Reporting: There are multiple reports that collect information about a firm’s top counterparties including the Office of the Comptroller of the Currency (OCC) Legal Lending Limit Report, Financial Stability Board (FSB) common data collection of Institution-to-Institution Credit Exposure Data (e.g., Top 50 Counterparty Report), Federal Financial Institutions Examination Council (FFIEC) 031 (i.e., bank “Call Report”), new Fed Single Counterparty Credit Limit Top 50 Report, and others. Each of these reports has a slightly different scope and use different definitions for aggregation of exposures resulting in significant work to produce the overlapping reports and explain the differences in the reported results.1
2. Financial Institutions Classification: There are numerous reporting requirements – regulatory capital deductions (e.g., FFIEC 101 Schedule A & FR Y-9C, Schedule HC-R), risk-weighted assets (e.g., Asset Value Correlation calculation FFIEC 101 Schedule B), systemic risk (e.g., Federal Reserve’s Banking Organization Systemic Risk Report—FR Y-15 Schedule B), and liquidity (e.g., Complex Institution Liquidity Monitoring Report FR 2052a), among others – that aggregate and report data with the classification “Financial Institution,” each using a different definition of “Financial Institution.” While on the surface this may not seem complicated, the reality is firms have full teams of people who parse data across these different definitions to ensure reporting is done correctly and can be reconciled. In a large firm, efforts to create tagging systems to automate the parsing process can take years and multiple, additional headcount to implement.2
The U.S. regulatory community is aware of this – in the commentary from the recent Y-15 information collection rule, the Federal Reserve acknowledges the conflict but does not address the burden:
One commenter noted that the definition of ‘financial institution’ in the FR Y-15 is different from other regulatory reports and recommended aligning the varying definitions. In response, the Board acknowledges that its regulations and reporting sometimes use differing definitions for similar concepts and that this may require firms to track differences among the definitions. Firms should review the definition of ‘financial institution’ in the instructions of the form on which they are reporting and should not look to similar definitions in other forms as dispositive for appropriate reporting on the FR Y-15.
These issues could be addressed through the use of common data and reporting standards across the agencies. The Financial Stability Oversight Council (FSOC) could take steps within its mandate to facilitate coordination among its member agencies towards the standardization of regulatory reporting requirements across the agencies.3
The FSOC could initiate a review of the current state of data and reporting within the U.S. to identify overlapping and duplicative reporting requirements and opportunities to move from proprietary data standards to national and global standards. Based on the review, a roadmap could be established to address the issues and gaps identified. Innovative approaches to data collection, such as using single collections, could be established that are then shared among agencies and global reference data should be implemented in all cases where it exists. Further, mechanisms could be created to ensure better coordination among agencies in the process of rulemaking to avoid duplication and to leverage consistent, established data standards.
The benefits of such improvements would be substantial. Better standardization of regulatory reporting requirements across the agencies would significantly improve the ability of the U.S. public sector to understand and identify the buildup of risk across financial products, institutions, and processes.
Reducing duplication, streamlining reporting, and using data standards would lead to efficiency, saving time, and reducing costs that firms and regulators otherwise expend manually collecting, reconciling, and consolidating data. According to the U.S. Department of the Treasury’s Office of Financial Research (OFR), the estimated cost to the global industry from the lack of data uniformity and common standards runs into the billions of dollars.4
Looking forward, having good quality, standardized data is an important stepping stone to reaping the benefits of the ongoing digitization of financial assets, digitization of markets and growing use of new, cutting-edge technologies, such as artificial intelligence. Many areas of the financial industry will be impacted, in some capacity, by these innovations in the coming years. These areas may include customer service, investment advice, contracts, compliance, anti-money laundering and fraud detection.
We urge the U.S. regulatory community to heed this call to action.
- Links to report references: https://occ.gov/topics/credit/commercial-credit/lending-limits.html; http://www.fsb.org/policy_area/data-gaps/page/3/; http://www.fsb.org/wp-content/uploads/r_140506.pdf; https://www.newyorkfed.org/banking/reportingforms/FFIEC_031.html; https://www.federalreserve.gov/reportforms/formsreview/FR2590_20180620_f_draft.pdf)
- Links to referenced reports: https://www.ffiec.gov/forms101.htm; https://www.federalreserve.gov/reportforms/forms/FR_Y-1520170331_i.pdf; https://www.federalreserve.gov/reportforms/forms/FR_2052a20161231_f.pdf
- Dodd-Frank Wall Street Reform and Consumer Protection Act, Sec. 112 (a)(2)(E)
- Office of Financial Research: Breaking Through Barriers Impeding Financial Data Standards (February, 2017).