## Dataset overview

## Source details

**Canonical URL:** [Dataset overview](https://www.imf.org/-/media/files/publications/gfsr/2024/april/data/ch3data.xlsx)

## Other formats

- [Markdown version](/-/media/files/publications/gfsr/2024/april/data/ch3data.xlsx.md)
- [Structured JSON version](/-/media/files/publications/gfsr/2024/april/data/ch3data.xlsx.json)

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### Dataset description
- Workbook name: "ch3data"
- Publication type: dataset (XLSX or CSV)
- Primary worksheet: "GFSR Chapter 3 Apr. 2024"
- The workbook contains figure-level data and labels for Chapter 3 of the Global Financial Stability Report: "Chapter 3. Cyber Risk: A Growing Concern for Macrofinancial Stability".
- Worksheets include a "Table of Contents" and multiple figure worksheets (example names: "Figure 3.1.", "Figure 3.2.", "Figure 3.3.", "Figure 3.4.", "Figure 3.5.", "Figure 3.6.", "Figure 3.7.", "Figure 3.8.", "Figure 3.9.", "Figure 3.10.", "Figure 3.1.1", "Figure 3.2.1").

### Major themes and figure titles (as labeled in the workbook)
- "Figure 3.1. Cyber Risks Are Increasing"
- "Figure 3.2. The Financial Sector Is Highly Exposed to Cyber Risk"
- "Figure 3.3. Cyber Risks Are Receiving Increasing Attention"
- "Figure 3.4. Cybersecurity and Macrofinancial Stability: Channels of Transmission"
- "Figure 3.5. Reported Direct Losses Due to Cyber Incidents"
- "Figure 3.6. Total Losses from Cyber Incidents"
- "Figure 3.7. Drivers of Cyber Incidents"
- "Figure 3.8. Cyber Risk in the Financial Sector"
- "Figure 3.9. Cyber Incidents and Deposit Flows"
- "Figure 3.10. Emerging Market and Developing Economies Have Gaps in Their Cybersecurity Preparedness"
- "Figure 3.1.1. Size and Interconnectedness of Financial Market Infrastructures"
- "Figure 3.2.1. Cyberattacks on Crypto Assets and Cyber Run Risk of Stablecoins"

### Key sample data points and labels (preserved verbatim)
- Worksheet timestamp cells contain "2024-04-01T00:00:00.000Z".
- Figure 3.3 panel labels and variables:
  - "(Mentions per 10,000 sentences)"
  - "(Rate per million of insurance coverage in thousands of US dollars, left scale; percent, right scale)"
  - "(Percent, left scale; number, right scale)"
  - Example time-series rows: "2002:Q4", "2003:Q1", "2003:Q2" with numeric entries such as 0.191689183361312 and 0.9268871422215624 for "2002:Q4", 0.24555297329969175 and 1.1102388107217458 for "2003:Q1", 0.23852535809010425 and 1.1102388107217458 for "2003:Q2".
  - Cyber insurance panel entries include years 2013, 2014, 2015 and values like 13.8, 28.4, 12.8, 32.3, 13, 41.6.
  - Policy-document count examples: 2014 → 0.23529411764705882; 2015 → 0.5; 2016 → 0.5789473684210527 and 3.
- Figure 3.5 reported-loss quantiles and sample values (Millions of US dollars and densities):
  - First quartile entries: 0.1796898025, 0.03632825, 0.15971039, 0.05, 0.01, 0.0583796, 0.0374641575.
  - Median entries: 0.648305, 0.865784, 0.99, 0.725, 0.08846242, 0.55886871, 0.422815 and quantile labels showing "Quantiles".
  - Country-level and year markers: 2017, 2021 with numeric examples such as 16.307172127135857 and -63.000301446447786.
  - Selected quantile probabilities: 0.1 → 23.196760481257307; 0.15 → 25.813324871900978.
- Figure 3.6 abnormal return estimates (Percentage points) following cyber incidents:
  - "t+0" values: -0.0122488495759744 (all incidents), -0.0718880848313346 (malicious incidents), -0.303321556700308 (malicious, small firms).
  - "t+1" values: -0.0848885069437262; -0.150680345324583; -0.482867737569144.
  - "t+2" values: -0.0357896334192712; -0.143971714106015; -0.51496727371847.
- Figure 3.7 driver coefficients and governance indicators:
  - "Telecommunications infrastructure index" entries: 1.62619; 0.0209435; 0.0046816.
  - "Cyber legislation index" entries: -1.51818; 0.0152037; 0.0303855.
  - "Geopolitical risk index" entry: 1.02999; driver coefficients 0.0211701; 0.0108702.
  - "Size" coefficient: 3.26676; sample effects 0.0350167; 0.0023491.
  - Governance and policy scores: "Privacy data management score (right scale)" 3.155383; 3.271693; 2.988571; 3.611892; 4.166116; 5.02682.
  - Impact estimates on likelihood of another attack: -1.32 and on increasing board members with cyber experience: 3.16.
- Figure 3.8 cyber ratings and concentration:
  - "Distribution of BitSight Cyber Security Ratings, January 2024" quartiles: First quartile 710; Median 740; Third quartile 770 for "Banks (total)" and variations for "Banks (G-SIBs)" and "Insurers".
  - Country-level concentration example: Asset size 67.729805; 84.19868.
  - Global concentration/payment activity examples: 14.154416511298972; 22.3239082792875; 29.127588689691112; 38.11690754270577.
  - Sectoral incident counts (initially affected sectors examples): 385; 785; 3456.
- Figure 3.9 deposit-flow estimates (Deviation from the baseline, percent):
  - Wholesale-deposit estimates sample row: -0.48; -1.7999999999999998; -1.9900000000000002; -2.06; -2.25; -3.56; -3.19; -3.17; -3.0300000000000002.
  - Retail-deposit estimates sample row: -0.35300000000000004; -1.04; -2.3; -2.22; -2.7; -2.85; -2.21; -2.75; -1.13.
  - Confidence intervals and "Estimates" blocks include multiple exact numeric values such as 0.17800000000000005; -0.6139549999999998; -0.3450000000000002; 0.04560000000000031; -0.09504999999999963.
  - Reverse outflow sample distributions: "Unsecured wholesale deposits" 21.59090909090909; 26.136363636363637; 17.045454545454543; 35.22727272727273.
  - Percent distribution example for retail deposits: 57.95454545454546; 29.545454545454547; 4.545454545454546; 7.954545454545454.
- Figure 3.10 cybersecurity preparedness and indices:
  - Maplecroft/ITU index examples by year: 2016 values 3.9455541 (AEs) and 2.9226562 (EMDEs).
  - Global Cybersecurity Index examples: 2019 values 9.81 (AEs) and 6.45 (EMDEs); 2023 values 9.67 (AEs) and 7.14 (EMDEs).
  - MSCI privacy/data security management score examples: 2016 median 0.51658974 (AEs) and 0.22638462 (EMDEs); 2020 median 0.8929973 and 0.42850382.
  - IMF survey responses on national cyber strategy: "No / Ongoing discussion" 36 (2021), 26 (2023); "Within next 12 months" 21 (2021), 27 (2023); "Yes" 43 (2021), 47 (2023).
  - Cyber Preparedness Index quantiles: First quartile 2.2; Median 3.075; Third quartile 3.95.
- Figure 3.1.1 financial market infrastructures:
  - Transaction amount indicators (examples): PSs 0.4035607361519373; CCPs 0.10672553524823264; CSDs 0.11186058439435796.
  - Participant counts and transaction metrics: PSs participants 54.9; CCPs 41.5; CSDs 63.6; SWIFT sample years 2013→2017 show values such as 5.065668423; 5.61272385; 5.065668423+ increments.
- Figure 3.2.1 crypto and stablecoins:
  - Crypto market capitalization distribution: "Total ($1.8 trillion)"; "Stablecoins ($130 billion)".
  - Specific asset market shares and reserve compositions: Bitcoin 46.60351089111868; Ethereum 15.544427011900206; Stablecoins 7.365708368918035; "US Treasury bills" 65.0234558297811; "Cash and bank deposits" 0.4068696502487969; "Repo" 0; "Reverse repo" 10.486893268741904.

### Notes on structure and intended use
- The workbook is organized by figure worksheets, each containing chart labels, panel captions, axis descriptions, and underlying numeric arrays (time series, quantiles, coefficients, counts).
- Numeric fidelity is preserved in the workbook across time-indexed series, quantiles, coefficients, and categorical counts; users should extract numeric arrays directly from each figure worksheet for replication or further analysis.
- Labels include text descriptions used in charts such as axis units (e.g., "(Percentage points)", "(Millions of US dollars)", "(Index)"), facilitating correct interpretation of numeric columns.

*Source: ch3data — https://www.imf.org/-/media/files/publications/gfsr/2024/april/data/ch3data.xlsx*

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_Source: https://www.imf.org/-/media/files/publications/gfsr/2024/april/data/ch3data.xlsx_