Across the government, policymakers are realizing what financial markets have known for decades: data are vital. Yet many essential government functions rely on outdated, paper-based processes—including financial regulation. Laws like the Digital Accountability and Transparency Act of 2014, the Foundations for Evidence-Based Policymaking Act of 2018, and the Grant Reporting Efficiency and Agreements Transparency Act of 2019 demonstrate recent moves by policymakers to address these existing, outdated processes. What all these bills have in common is that they ask that the information the government already collects be standardized. Data standardization means better methods of reporting to regulators and capital markets. It also enables the use of automation to improve analytics, reduce inefficiency, and enable better transparency.
The Financial Data Transparency Act (FDTA) (S. 4295) continues the movement towards standardized data by asking financial regulators to adopt industry-accepted consensus data standards, transforming the information they collect into an accessible machine-readable format. In fact, the FDTA was drafted in response to recommendations provided by the U.S. Treasury Department in a 2017 report regarding reduction of regulatory overlap and duplication for banks and credit unions. The report, in response to an Executive Order on principles for regulating the financial system (E.O. 13772), calls for improved data sharing and reductions in reporting burdens and duplication.
The Federal Deposit Insurance Corporation (FDIC) was the first federal financial regulator to implement a large-scale modernization project, that is, move from documents and tables of numbers to machine-readable semantic data.
The research about the FDIC affirms statistically relevant increases in efficiency and improvements in data quality. This project is more than a decade old, evidence that mature technology exists to meet the disclosure modernization requirements of the FDTA.
The findings speak for themselves: mathematical errors used to plague 33% of the data points in the FDIC Bank Call Reports. Now, they are nearly entirely eliminated before submission. Specifically:
Statistical correctness in the data moved from 66% to 100% correct.
Data is available to capital markets within hours rather than days (or weeks if corrections were necessary).
Analysts completed their workload in 15% less time and thus were able to increase the number of cases they could close.
What is important to note about the FDIC’s approach to data modernization is that they achieved all of these gains without changing the data they were collecting; rather, they mapped a way for the data they were already collecting to be machine-readable. The result is that they reduced the need to ask for corrections—companies don't have to be burdened with making and resubmitting corrections, and investors don't have to wait to get access to trustworthy data.
The FDIC is just one of the financial regulators around the world who are modernizing their reporting regimes by moving away from document-based reporting and adopting structured data formats and standardized data fields for the information they already collect instead.
The Municipal Securities Rulemaking Board (MSRB) is also working to modernize its data systems, with an explicit reference in its new quadrennial Strategic Plan to “support market-led initiatives to establish uniform data … standards in the municipal securities market that facilitate better disclosure and analysis of market information.” The FDTA helps MSRB establish and advance those standards.
The FDTA asks that additional federal regulators similarly modernize and make the information they already collect, or wish to collect in the future, available as machine-readable data using non-proprietary or royalty-free methods for encoding data. By passing this bill, Congress can ensure that this important modernization project will be a priority for regulators.
Importantly, the FDTA does not ask regulators to change any of the information they collect or publish, nor does it alter any statutory authority of the regulators to decide what information they collect. Rather, this legislation asks that appropriate, flexible data standards be developed based on the already-existing regulatory and reporting standards.
Data modernization is a common sense solution to many challenges for our financial regulators, but it is not something that can be done overnight. That is why the FDTA provides flexibility to agencies as they implement the provisions of the bill. The U.S. Treasury and the other agencies have two years from the date of enactment to develop and publish the required data standards through a joint rule. Covered agencies then have two years to implement the data standards into their respective regulatory compliance reporting, giving them a total of four years.
Further, in order to reduce the burden on smaller regulated entities, the FDTA allows agencies to scale data reporting requirements in order to reduce unjustified burden on smaller regulated entities and minimize disruptive changes to those affected by regulations. What’s more, the one-time upfront costs are likely to be offset in the longer term by advances enabled by new technologies.
By law, regulated entities must produce data for regulators. But they can also benefit by using the public, regulatory data. Adopting standardized data can reduce the cost of both these activities by transforming an opaque, hard to understand system into a transparent, level playing field. In 2018, the Association of International Certified Professional Accountants found that it cost roughly 70% of companies $5,500 or less to comply with a Securities and Exchange Commission (SEC) rule which required public companies to report their financials in the XBRL (eXtensible Business Reporting Language) data standard format. This process of standardization makes market-critical data available as machine readable data. With these data standards, stakeholders, like market lenders, borrowers and small investors, can start using off-the-shelf technology solutions, meaning that small entities can compete with larger firms for data insights.
As the data reported into the regulators becomes standardized, small entities without the resources for massive data analytics shops can focus on how to use the data for maximum benefit rather than ingesting data sets on ad hoc basis, allowing them to participate more strategically in the market.
The Financial Data Transparency Act establishes a framework that can be used to improve regulatory reporting efficiency in coming years and decades, reducing compliance overhead, and the level of effort required for submitting financial reports. It also sets the stage for financial regulators to have access to higher quality data so regulators can spend their time focused on enforcement rather than tracking down inadvertent errors in reports. Streamlining regulatory reporting frees up valuable time and energy that can support private sector innovation and productivity growth. This is a win for capital markets, for reporting entities, and for data transparency.
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