Remarks by Under Secretary for Domestic Finance Nellie Liang at the Brookings Institution
A key lesson from the global financial crisis is that opacity about critical markets and institutions resulting from lack of high-quality data can contribute to financial instability. And, because different financial regulators have visibility into different market segments, detecting and addressing financial stability vulnerabilities requires close coordination and information sharing among regulators. Simply put, in a dynamic, interconnected economy such as ours, regulators cannot effectively safeguard financial stability or respond to crises if they do not have good data and are not talking to one another.
In my remarks today, I will talk about how
Last month, the Council issued its new Analytic Framework which explains to the public how it uses regulatory data and data from other sources to monitor risks to financial stability.1 The Framework details key vulnerabilities and transmission channels that most commonly contribute to risks to financial stability, as well as sample quantitative metrics.
Vulnerabilities include, of course, leverage and liquidity and maturity mismatch, complexity and opacity, as well as others, all of which have been well studied. The Framework's discussion highlights how data gaps, such as those from lack of regulatory or public disclosures or difficulties in determining interactions of market participants, may exacerbate complexity and opacity. More broadly, the Framework makes clear that filling significant data gaps in order to better evaluate vulnerabilities is an integral part of the Council's risk identification and assessment process.
To be sure, in the 13 years since the Dodd-Frank Act became law, financial regulators, on their own and working with the Council and OFR, have improved the quantity and quality of data, increasing visibility into some previously opaque market segments. To list a few examples, the
Clearly, reliable data are a necessary input into our assessment of financial stability risks and lack of transparency may exacerbate risks. But we know that data production is not costless, both for the entities who report it and the regulators who maintain it. So how can we ensure we get the greatest "bang for the buck" for the data that we rely on? I believe we can most effectively leverage our resources when we adopt a holistic, end-to-end, approach to data collection and standardization.
This approach starts with a rigorous process for identifying data gaps and unmet needs to monitor vulnerabilities, such as described in the FSOC Framework. Having identified a gap that needs to be filled, regulators or OFR actively consult with relevant stakeholders to develop a data collection process that addresses regulators' objectives in a way that is efficient and avoids unnecessary burdens on reporting entities. By being careful in the way we design data collections, for example by relying on open standards for data reporting formats and variable definitions, we can often improve the efficiency of data sharing and interoperability among regulators.
Once we've determined what must be reported, we need to deploy robust infrastructure to onboard, maintain, warehouse and analyze the data. This infrastructure includes not only physical data storage and server capacity, but also data governance structures that enable us to protect confidential data while also facilitating information sharing among regulators with a "need to know". Finally, to the extent feasible, I believe there is great value in making as much data as possible available to the public subject to the need to protect privacy and intellectual property, prevent market distortions, and other constraints.
Providing data to the public has a variety of benefits. I am perhaps "preaching to the choir" but academics and practitioners outside the regulatory community have much to contribute to the discourse on financial stability, and access to better data raises the quality of that discourse. And it's been my experience that the more people who use a particular dataset, the more quickly its quality tends to progress over time, as users identify weaknesses and suggest improvements. Of course, there is also a vast academic literature on the effects of public transparency. This literature has documented many benefits including lower costs, improved liquidity, and better price discovery, but there may be unintended consequences as well, and we need to be cognizant of these possible consequences in determining what and how much information to disclose.
To illustrate this holistic approach in practice, I'll turn now to two current data initiatives,
The
During the
Earlier this year, the
We have also made significant progress in improving regulators' visibility into the
The
The OFR turned its attention to closing this gap and conducted a pilot collection in 2022. In January of this year the OFR proposed a rule to begin collecting NCCBR data on an ongoing basis. The proposed collection would provide daily transaction-level information from an estimated forty financial companies. These data would allow regulators to monitor the NCCBR market in near-real time [which would help them to identify emerging market vulnerabilities and track developments in repo markets that might indicate stresses elsewhere in the financial system]. The OFR received over 30 comments on its proposed rule [representing a range of stakeholders from industry associations to individual household investors]. Public feedback is being used to refine the Final Rule, which OFR expects to publish in the coming months.
The NCCBR data collection will require that the OFR manage data submissions from reporters on a daily basis. To support the proposed NCCBR data collection and other projects, the OFR has developed a Data Collection Utility (DCU). The
A second area where
For regulators and researchers accustomed to analyzing more standardized financial data, the size, complexity, and format of many climate datasets makes them difficult to work with. In 2022, the OFR launched a pilot program to assess the feasibility of a collaborative research environment with data and analytical tools for assessing climate-related financial risks for FSOC member agencies. Following the successful completion of the pilot, the project permanently launched as the Joint Analysis Data Environment, or JADE.
JADE is a high-performance computing platform that will enable collaborative, interdisciplinary research by providing FSOC member agencies access to analysis-ready data and analytical software in a secure, cloud-based environment. JADE integrates processes and protocols to ensure data privacy based on those it has developed and refined over the years. These processes and protocols ensure only those with the proper permissions, in agreement with the providing agency, are allowed access to the data on the platform. Currently, JADE hosts a mix of publicly available climate and financial data. For example, it includes information on the geography of flood and wildfire hazards, as well as information on the geographic distribution of mortgage loans exposed to those hazards. Providing these resources in a collaborative space enables FSOC member agencies to focus on the research, rather than individually obtaining the necessary resources to conduct their work.
Currently, in addition to the two pilot participants, the Fed NY and the
We are also working to expand the data we collect to fill an important gap in our ability to evaluate and monitor the impact of climate-related hazards on households and real estate markets, and risks to financial stability.
We've all seen the headlines about spiking homeowners' insurance premiums or limited insurance availability in places like
To address this gap, in
Last month, FIO announced that it would seek formal OMB approval to begin collecting insurance data at a ZIP Code level on a consistent, granular, and comparable basis from the largest homeowners' insurance providers that collectively underwrite around 70% of homeowners insurance premiums nationwide. These data will help regulators and analysts to better understand how physical climate risks influence insurance coverage and availability for homeowners, and potential knock-on effects for mortgage lenders and real estate markets, and financial stability risks.
To conclude, let me emphasize that we at
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1 The Council unanimously voted to issue its new Analytic Framework for Financial Stability Risk Identification, Assessment, and Response (the Framework) https://home.treasury.gov/system/files/261/Analytic-Framework-for-Financial%20Stability-Risk-Identification-Assessment-and-Response.pdf
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Original text here: https://home.treasury.gov//news/press-releases/jy1992
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