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12/14/2023

Remarks by Under Secretary for Domestic Finance Nellie Liang at the Brookings Institution | U.S. Department of the …

Remarks by Under Secretary for Domestic Finance Nellie Liang
at the Brookings Institution
December 14, 2023

INT RODUCT ION
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 di erent financial regulators have visibility into di erent 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 e ectively safeguard financial stability or respond to crises if they
do not have good data and are not talking to one another.
Congress took this lesson to heart when it passed the landmark Dodd-Frank Wall Street
Reform and Consumer Protection Act in the summer of 2010. Among many important reforms,
the Act created the Financial Stability Oversight Council (FSOC or Council) to identify risks to
U.S. financial stability, and established the O ice of Financial Research (OFR) to support the
Council and member agencies in collecting and standardizing data collections.
In my remarks today, I will talk about how Treasury, with FSOC and OFR, have been
approaching data collection, standardization, and risk measurement for safeguarding
financial stability. Iʼll use ongoing work in two important areas – Treasury market resilience
and the financial sectorʼs climate risks – to illustrate. The financial regulatory community has
made tremendous progress to reduce opacity since the financial crisis and is poised to
advance further due to investments in data and analytic infrastructure. The progress helps
regulators and the regulated firms themselves, and more broadly the public.

DATA AND T HE FSOCʼS NEW ANALY T IC F RAMEW ORK
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

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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 Frameworkʼs
discussion highlights how data gaps, such as those from lack of regulatory or public
disclosures or di iculties 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 Councilʼs 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 Federal Reserve is now collecting for the largest banks highly granular loan-level data and
resolution plans with key inter-linkage data ; the SEC has significantly expanded the detail on
assets in money market mutual funds and open-end funds, and is collecting more timely data
for private funds from Form PF; and the CFTC and SEC now have access to transaction-level
data on swaps trades reported into registered trade repositories.
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
e ectively 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 regulatorsʼ objectives in a way that is
e icient 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 o en improve the e iciency of data sharing and
interoperability among regulators.
Once weʼve determined what must be reported, we need to deploy robust infrastructure to
onboard, maintain, warehouse and analyze the data. This infrastructure includes not only
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Remarks by Under Secretary for Domestic Finance Nellie Liang at the Brookings Institution | U.S. Department of the …

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 itʼs 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 e ects 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, Iʼll turn now to two current data initiatives,
Treasury market resilience and climate-related financial risks.

CURRENT DATA INIT IAT IVES:
Treasury Markets
The $26 trillion U.S. Treasury market is the deepest and most liquid market it the world, and is
the foundation for global financial markets. Ensuring that it functions well, particularly during
times of stress, is fundamental to safeguarding financial stability. Greater data transparency
and new data collections are critical parts of our e orts to improve Treasury market
resilience.

Secondary Market Transparency
During the March 2020 “dash for cash” episode, when Treasury markets became disrupted at
the onset of the COVID pandemic, data on Treasury market trading volumes available to the
public were very limited. Only weekly data on trading volumes was publicly disclosed, and this
was done with a one-week lag. Itʼs hard to assess how well a market is functioning during
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stress periods if you cannot match price data to contemporaneous quantity data, so this lack
of transparency was a serious gap.
Earlier this year, the Financial Industry Regulatory Authority (FINRA), working with Treasury,
replaced the weekly reports on secondary market trading with daily reports. These reports
also provide information on trade counts and volume-weighted average prices for on-the-run
nominal coupon securities. Coincidentally, this greater transparency became available just
weeks before the regional banking turmoil in March, allowing market participants to benefit
from the enhanced information about the Treasury securities market activity during that
di icult time.
The Treasury Department has been working further with FINRA to enable public dissemination
of secondary market trading at the transaction-level. We have consulted closely with market
participants and other stakeholders on what data could be disclosed without compromising
market functioning. We have proposed to begin by disclosing transaction-level data for onthe-run nominal coupon securities. The disclosures would put caps on trade sizes and a
modest time delay to prevent strategic front-running and other distortionary behavior that
might reduce market integrity. Last month, FINRA submitted their proposed rule filing to the
SEC to move forward with transaction-level dissemination. If the rule goes forward, we will
then assess over time the e ects of these disclosures for on-the-run securities and consider
possible steps to provide additional transparency.

Non-Centrally Cleared Bilateral Repo Markets
We have also made significant progress in improving regulatorsʼ visibility into the Treasury
repo market. A vibrant Treasury repo market is an important prerequisite for a deep and liquid
Treasury securities market. But as we saw during the global financial crisis, repo markets can
be subject to run dynamics. Financial regulators have done much to improve regulatorsʼ
visibility into this market since then, but gaps remain and we are working to fill them.
The Federal Reserve now collects data on tri-party repo transactions and the OFR collects
data on centrally-cleared repo transactions, but currently no one systematically collects data
on the non-centrally cleared bilateral repo (NCCBR) market. This market is roughly a $2 trillion
market. and is the largest segment of the Treasury repo market. It represents dealer-client
transactions, which may feature significant borrowing by leveraged actors such as hedge
funds.

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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 DCU is an e icient, cost-e ective tool for
data collections, which will allow the OFR to securely collect and store business confidential
data or large-scale bespoke collections. This utility will provide flexibility for financial industry
participants and other data reporters, allowing for both automated or manual submissions.
Looking beyond the NCCBR data collection, the utility also positions the OFR to respond
quickly to the FSOCʼs evolving data needs through pilots, surveys, and other ongoing
collections. The OFRʼs Data Collection Utility will become operational in early 2024.

Climate Risk Data Initiatives
A second area where Treasury is working to improve financial data and analysis is risks to the
financial sector from climate change. Some climate data needed to measure risks – such as
information on acute physical risks like hurricanes and wildfires and more chronic physical risks
like protracted excessive heat or sea-level rise – already exist. Other data, such as granular
emissions information of borrowers used to help identify financial firmsʼ exposures to climate
transition risks, are still being developed.

Joint Analysis Data Environment (JADE)
For regulators and researchers accustomed to analyzing more standardized financial data,
the size, complexity, and format of many climate datasets makes them di icult 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
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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 so ware 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 Federal Reserve Board,
FSOC and the O ice of the Comptroller of the Currency have access to the platform, and there
are plans for additional FSOC member agencies to join in the near future. In addition, OFR is
planning for JADE to accommodate other data and analytical so ware and support research
on other financial stability topics as well.

Federal Insurance O ice Data Collection
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.
Weʼve all seen the headlines about spiking homeownersʼ insurance premiums or limited
insurance availability in places like California and the gulf coast that are struggling to cope
with the rising economic costs of wildfires, hurricanes and other climate-related hazards.
Many physical climate hazards tend to have highly localized e ects, and the risks from these
hazards depend on local geography, as well as migration and development patterns. To
understand how physical climate risks a ect property insurance markets, regulators and
researchers need to know how the availability, price and loss claims on insurance policies vary
across local geographies, but current data are typically available only at the state level.

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To address this gap, in October 2022 the Treasury Departmentʼs Federal Insurance O ice (FIO)
sought public comment on a proposal to collect geographically granular data on multi-peril
homeownersʼ insurance. Since then, FIO has carefully reviewed comments received and
engaged with numerous stakeholders, including the National Association of Insurance
Commissioners (NAIC), state insurance regulators, insurance companies, and consumer
groups. Based on these discussions, FIO streamlined and refined its data collection request
to facilitate a more e ective implementation of this first-ever data collection.
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 homeownersʼ 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 e ects for mortgage lenders and real estate markets,
and financial stability risks.

CONCLUSION
To conclude, let me emphasize that we at Treasury and in the broader financial regulatory
community understand the critical importance of data to our financial stability mission.
Collecting and maintaining data for analysis is a critical part of that work because we canʼt
manage risks if we canʼt e ectively measure them. The examples Iʼve presented today of ways
weʼre using data and infrastructure to improve the resilience of Treasury markets and better
understand climate-related financial risks demonstrate our holistic approach to data
management: we identify data gaps; consult closely with stakeholders to develop data
collections; build infrastructure to collect, secure, and analyze data; and work to share data
among regulators and, where practical, with the public. In this way, we are working to improve
both the extensive margin – by expanding the data we collect – and the intensive margin – by
using our data more e iciently – to advance our financial stability mission.
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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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