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Publication Date: 14 Aug 2024
Publication Site: Treasury Dept
All about risk
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Publication Date: 14 Aug 2024
Publication Site: Treasury Dept
Link: https://www.regulations.gov/document/TREAS-DO-2024-0011-0001/comment
Description:
Publicly available comments on Dept of Treasury’s request for information on AI use, opportunities & risk in financial services sector.
Example: https://www.regulations.gov/comment/TREAS-DO-2024-0011-0010 — comment from ACLI
The NAIC has developed its definition of AI, and the insurance industry has responded with
information in accordance with that definition. Any definition developed by Treasury should
align with, or at a minimum not conflict with, definitions of AI in existing regulatory
frameworks for financial institutions.The Treasury definition of AI should reflect the following:
o Definitions should be tailored to the different types of AI and the use cases and
risks they pose. The definition used in this RFI is similar to an outdated definition put
forth by the Organization for Economic Coordination and Development (OECD),
which could be narrowed for specific use cases (e.g., tiering of risks under the EU
framework).
o There are also distinctions between generative AI used to make decisions, without
ultimately including human input or intervention, and AI used with human decisionmaking being absolute or the usage being solely for internal efficiencies and
therefore not impactful for customers.
o AI covers a broad range of predictive modeling techniques that would otherwise not
be considered Artificial Intelligence. A refinement to the definition that classifies AI
as machine learning systems that utilize artificial neural networks to make
predictions may be more appropriate.
o The definition of AI should exclude simpler computation tasks that companies have
been using for a long time.
Author(s): Various
Publication Date: accessed 9 Aug 2024
Publication Site: Regulations.gov
Link: https://www.cdc.gov/mmwr/volumes/73/wr/mm7331a1.htm?s_cid=mm7331a1_w
Graphic:
FIGURE 1. Provisional* number of COVID-19–associated deaths† and other deaths and percentage of deaths associated with COVID-19, by week of death — National Vital Statistics System, United States, 2023
* National Vital Statistics System provisional data for 2023 are incomplete. Data from December 2023 are less complete because of reporting lags. These data exclude deaths that occurred in the United States among residents of U.S. territories and foreign countries.
† Deaths with confirmed or presumed COVID-19 as an underlying or contributing cause of death, with International Classification of Diseases, Tenth Revision code U07.1.
Excerpt:
Final annual mortality data from the National Vital Statistics System for a given year are typically released 11 months after the end of the calendar year. Provisional data, which are based on preliminary death certificate data, provide an early estimate of deaths before the release of final data. In 2023, a provisional total of 3,090,582 deaths occurred in the United States. The age-adjusted death rate per 100,000 population was 884.2 among males and 632.8 among females; the overall rate, 750.4, was 6.1% lower than in 2022 (798.8). The overall rate decreased for all age groups. Overall age-adjusted death rates in 2023 were lowest among non-Hispanic multiracial (352.1) and highest among non-Hispanic Black or African American persons (924.3). The leading causes of death were heart disease, cancer, and unintentional injury. The number of deaths from COVID-19 (76,446) was 68.9% lower than in 2022 (245,614). Provisional death estimates provide an early signal about shifts in mortality trends. Timely and actionable data can guide public health policies and interventions for populations experiencing higher mortality.
Author(s): Farida B. Ahmad, MPH1; Jodi A. Cisewski, MPH1; Robert N. Anderson, PhD
Publication Date: 8 Aug 2024
Publication Site: CDC, MMWR Morbidity/Mortality Weekly Report
Suggested citation for this article: Ahmad FB, Cisewski JA, Anderson RN. Mortality in the United States — Provisional Data, 2023. MMWR Morb Mortal Wkly Rep 2024;73:677–681. DOI: http://dx.doi.org/10.15585/mmwr.mm7331a1
Excerpt:
The U.S. Department of the Treasury (Treasury) is seeking comment through this request for information (RFI) on the uses, opportunities and risks presented by developments and applications of artificial intelligence (AI) within the financial sector. Treasury is interested in gathering information from a broad set of stakeholders in the financial services ecosystem, including those providing, facilitating, and receiving financial products and services, as well as consumer and small business advocates, academics, nonprofits, and others.
Written comments and information are requested on or before August 12, 2024.
….
The rapid development of emerging AI technologies has created challenges for financial institutions in the oversight of AI. Financial institutions may have an incomplete understanding of where the data used to train certain AI models and tools was acquired and what the data contains, as well as how the algorithms or structures are developed for those AI models and tools. For instance, machine-learning algorithms that internalize data based on relationships that are not easily mapped and understood by financial institution users create questions and concerns regarding explainability, which could lead to difficulty in assessing the conceptual soundness of such AI models and tools.[22]
Financial regulators have issued guidance on model risk management principles, encouraging financial institutions to effectively identify and mitigate risks associated with model development, model use, model validation (including validation of vendor and third-party models), ongoing monitoring, outcome analysis, and model governance and controls.[23] These principles are technology-agnostic but may not be applicable to certain AI models and tools. Due to their inherent complexity, however, AI models and tools may exacerbate certain risks that may warrant further scrutiny and risk mitigation measures. This is particularly true in relation to the use of emerging AI technologies.
Furthermore, the rapid development of emerging AI technologies may create a human capital shortage in financial institutions, where sufficient knowledge about a potential risk or bias of those AI technologies may be lacking such that staff may not be able to effectively manage the development, validation, and application of those AI technologies. Some financial institutions may rely on third-party providers to develop and validate AI models and tools, which may also create challenges in ensuring alignment with relevant risk management guidance.
Challenges in explaining AI-assisted or AI-generated decisions also create questions about transparency generally, and raise concerns about the potential obfuscation of model bias that can negatively affect impacted entities. In the Non-Bank Report, Treasury noted the potential for AI models to perpetuate discrimination by utilizing and learning from data that reflect and reinforce historical biases.[24] These challenges of managing explainability and bias may impede the adoption and use of AI by financial institutions.
Author(s): Department of the Treasury.
Publication Date: 6/12/2024
Publication Site: Federal Register
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Publication Date: 8 Aug 2024
Publication Site: Treasury Dept
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Publication Date: 6 Aug 2024
Publication Site: Treasury Dept
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Publication Date: 5 Aug 2024
Publication Site: Treasury Dept
Link: https://mishtalk.com/economics/big-changes-in-fed-interest-rate-cut-expectations-this-year-and-next/
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Excerpt:
I captured rate cut expectations before and after the Friday jobs reports. Let’s take a look.
The current rate is 5.25%-5.50% effectively 5.37%.
Those odds were smack in the middle of volatility.
The CME website now shows data as of August 1 (no change on Friday), so they have something messed up.
The chart above reflects the huge volatility we saw in bond yields on Friday.
….
Are too many cuts priced in or not enough?
That’s the question. I expect two cuts in September. Looking out to next year, I think too many cuts are priced in.
Author(s): Mike Shedlock
Publication Date: 3 Aug 2024
Publication Site: Mish Talk
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Publication Date: 2 Aug 2024
Publication Site: Treasury Dept
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Publication Date: 31 July 2024
Publication Site: Treasury Dept
Link: https://content.naic.org/sites/default/files/capital-markets-market-buzz-private-credit-plr.pdf
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Excerpt:
The terms private credit and private letter ratings (PLRs) have unintentionally elicited some confusion
about their respective meanings. While there is no standardized definition, and the term may be used
differently by market participants, private credit generally refers to debt, or debt-like, securities that are
not publicly issued or traded. On the other hand, PLRs refer to credit opinions that are assigned to
privately rated securities by credit rating providers and are only communicated to the issuer and a
specified group of investors.
To bring some clarity, at least with respect to how the NAIC views them, these terms can be characterized
in two dimensions: 1) distribution; and 2) transparency.
Publication Date: 30 July 2024
Publication Site: NAIC Capital Markets Bureau Market Buzz
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Excerpt:
Housing affordability continues to soar out of reach of most buyers. Not only are prices at a new record level, mortgage rates remain close to 7.0 percent.
Chart Notes
Author(s): Mike Shedlock (Mish)
Publication Date: 30 July 2024
Publication Site: MishTalk