我们的数据

公司违约率 (PD)

NUS-CRI 违约概率 (NUS-CRI PD) 是一个前瞻性的、按时间点计算的违约概率指标，每日更新。

关键事实

NUS-CRI PD涵盖全球超过90,000家交易所上市公司，预测周期从未来1个月起可高达未来5年。
NUS-CRI PD 采用完全透明且定期更新的方法计算，提供基于最新信用风险研究的衡量标准，并受到世界各地组织的信赖，用于风险管理、监管合规和预警系统等用途。

示例数据

公司ID	1-month PD 1个月内违约的可能性有多大？	2-month PD 2个月内违约的可能性有多大？	...	60-month PD 60个月内违约的可能性有多大？
1	0.00012	0.00015	...	0.00030
...	...	...	...	...

获取数据

用途	更新频率	选项
非商业用途，可在网页上查看/下载 CSV 文件	每月更新	查看数据
RESTful API 集成及其他商业用途	每日更新	联系我们

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行业违约率

NUS-CRI Aggregate PD 允许您通过自下而上（中位数）的信用风险衡量方法，评估任何感兴趣的地区、国家或行业的信用状况。

关键事实

NUS-CRI Aggregate PD 涵盖所有主要地区的国家，包括北美、欧洲、亚洲和拉丁美洲，并可按行业子类别进行细分。

示例数据

国家/行业	1-month PD 1个月内违约的可能性有多大？	...	60-month PD 60个月内违约的可能性有多大？
US	0.00012	...	0.00030
US - Manufacturing	0.00012	...	0.00030
US - Manufacturing - Automobile	0.00012	...	0.00030
...	...	...	...

获取数据

用途	更新频率	选项
非商业用途，可在网页上查看/下载 CSV 文件	每月更新	查看数据
RESTful API 集成及其他商业用途	每日更新	联系我们

阅读更多

CRI 中小微企业信用风险数据

~ 中小微企业风险评估与信用评价工具包 (TRACE) ~

微型、小型和中型企业 (MSME) 面临持续的融资缺口，因为金融机构被迫在透明但简单的评分卡和高性能但不透明的“黑箱”人工智能之间做出选择。CRI 的中小微企业风险评估和信用评价工具包 (TRACE) 解决了这一难题，将我们全球公认的方法论扩展到了中小微企业领域。

关键事实

TRACE 被设计成一个“透明平台”，将计量经济学可解释模型与先进的机器学习技术相结合。这在提供高性能 AI 预测的同时，确保了监管机构和风险管理人员所需的审计性、稳定性和监管便利性，最终实现了性能与透明度的平衡。

主要功能

智能数据集成：融合传统财务数据与替代信号（例如电信、宏观数据），以克服数据稀疏性问题。
“透明平台”建模：在确保完全可审计性和稳定性的同时，提供高性能 AI 预测。
监管合规：部署 GenAI 驱动的场景实验室，针对“极端情况”对模型进行压力测试，以实现负责任的 AI 治理。
经实践验证的影响：在东南亚地区经过实战检验，在不影响风险管理的前提下，有效促进了中小微企业贷款业务的发展。

获取数据

用途	可用性	选项
新加坡餐饮企业的样例数据	每年更新	查看数据
框架咨询和定制	应要求	联系我们

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TRACE 白皮书

自下而上的违约分析（BuDA）工具包

自下而上的违约分析（BuDA）工具包是与国际货币基金组织（IMF）联合开发的，它有助于进行全面的信用压力测试和情景分析，以评估投资组合的风险。

关键事实

BuDA 将宏观经济冲击转化为单个公司层面的PD影响，然后使用可定制的压力情景将这些影响汇总到有针对性的经济体、行业或投资组合评估中。

压力测试情景示例

Scenario	GDP Growth (1 quarter ahead)	GDP Growth (2 quarters ahead)	...	Fed Interest Rate (1 quarter ahead)	Fed Interest Rate (2 quarters ahead)	...
Baseline	2.5%	3.0%	...	-0.25%	-0.5%	...
Adverse	-1.5%	5.5%	...	0%	0%	...
Severe Adverse	-4.0%	7.0%	...	0.5%	0.5%	...

获取数据

用途	可用性	选项
工具安装和培训	应要求	联系我们

阅读更多

BuDA 白皮书

实际应用案例

以下列出的是可公开核实的引用，表明我们的数据已被国际组织和监管机构用于研究和出版物中。由于合同和合规保密义务，我们不会披露使用我们数据的商业金融机构的名称。

以下来自 International Monetary Fund 的出版物引用了CRI数据

Corporate Quarterly Model. This paper details on IMF quarterly corporate risk model, which examines systemic non-financial corporate sector distress using firm-level probabilities of default (PD), covering 55 economies, and spanning the last three decades.
Chan-Lau, J.A. et al., 2017, Bottom-Up Default Analysis of Corporate Solvecy Risk: An Application to Latin America. IMF Working Paper 17/133.
Chan-Lau, J.A., 2021, Scenario Analysis with the DD-PD Mapping Approach: Stock Market Shocks and U.S. Corporate Default Risk. IMF Working Paper 2021/143.
IMF, 2021a, 2021 Financial Sector Assessment Program Review = Background Paper on Quantitative Analysis, IMF Policy Paper, Washington, D.C.
2021b, People’s Republic of China – Hong Kong Special Administrative Region, Financial Sector Assessment Program, Technical Note – Stress Testing the Banking Sector and Systemic Risk Analysis, June, Washington, D.C. Available at
2021c, How to Assess Country Risk: the Vulnerability Exercise Approach Using Machine Learning. Technical Notes and Manuals.
2020a, Republic of Korea, Financial Sector Assessment Program, Technical Note – Non-financial Balance Sheet Vulnerabilities and Risks to Financial Stability, September, Washington, D.C.
2020b, Regional Economic Outlook, October 2020, Middle East and Central Asia, Chapter 2.
2020c, Regional Economic Outlook, October 2020, Middle East and Central Asia. Technical Annex.
2019, Singapore, Financial Sector Assessment Program, Technical Note –Financial Stability Analysis and Stress Testing, July, Washington, D.C.
2017a, Japan, Financial Sector Assessment Program, Technical Note – Systemic Risk Analysis and Stress Testing the Financial Sector, September, Washington, D.C.
2017b, Indonesia, Financial System Stability Assessment – Press Release and Statement by the Executive Director for Indonesia, Washington, D.C.
2016a, Chile: 2016 Article IV Consultation – Press Release; Staff Report; and Statement by the Executive Director for Chile.
2016b, Canada: 2016 Article IV Consultation – Press Release; and Staff Report.
2016c, United Arab Emirates: Selected Issues.
2016d, Regional Economic Outlook, April 2016, Western Hemisphere, Chapter 3.
Iossifov, P.K., and T. Dutra-Schmidt, 2021, Cyclical Patterns of Systemic Risk Metrics: Cross-Country Analysis. IMF Working Paper 2021/028.
Loukoianova, E. et al., 2018, Managing Macro-Financial Linkages. Chapter 12 in L. Breuer, J. Guajardo, and T. Kinda, Realizing Indonesia’s Economic Potential. International Monetary Fund.
Miyajima, K., J. A.Chan-Lau, W. Miao, J. Shin, 2017, Assessing Corporate Vulnerabilities in Indonesia: a Bottom-Up Default Analysis. Asia-Pacific Financial Markets 24, 269–289.

以下来自 Monetary Authority of Singapore 的出版物引用了CRI数据

Moody's Analytics: MAS Report Reviews Stability of Financial Sector in Singapore, Dec 06, 2021
Macroeconomic Surveillance Dept. (2021). Financial Stability Review 2021 (No. 2021; Financial Stability Review, pp. 88–98). Monetary Authority of Singapore.
Macroeconomic Surveillance Dept. (2022). Financial Stability Review 2022 (No. 2022; Financial Stability Review, pp. 22–23). Monetary Authority of Singapore.

Publications from ASEAN+3 Macroeconomic Research Office 的出版物引用了CRI数据

Ong, L. L., Siu, M. F. Y., & Laura Grace Gabriella. (2022). Capital Flow Management and Macroprudential Policy Measures in the ASEAN+3: Initial Recommendations ((PPP/22–01); Policy Position Paper). ASEAN+3 Macroeconomic Research Office.
The Winds of War: Spillovers from the Russia-Ukraine Conflict to ASEAN+3 Banking Systems (Analytical Note). (2022). ASEAN+3 Macroeconomic Research Office.
The Failure of Archegos Capital Management: Estimating Potential Spillovers to ASEAN+3 Financial Systems (Analytical Note). (2021). ASEAN+3 Macroeconomic Research Office.
AMRO Annual Consultation Report China—2020 (AMRO Annual Consultation Report). (2021). ASEAN+3 Macroeconomic Research Office.
Sun, W. (2020). Covid, Credit, and Contagion Risks to ASEAN+3 Financial Systems (Analytical Note). ASEAN+3 Macroeconomic Research Office.
- Slides: https://www.amro-asia.org/wp-content/uploads/2020/12/Covid-Credit-and-Contagion_4th-RFA-Research-Seminar.pdf
AMRO Annual Consultation Report China—2019 (AMRO Annual Consultation Report). (2020). ASEAN+3 Macroeconomic Research Office.

以下来自 World Bank 的出版物引用了CRI数据

Feyen, E., & Zuccardi, I. (2019). The Sovereign-Bank Nexus in EMDEs: What Is It, Is It Rising, and What Are the Policy Implications? [Working Paper]. World Bank.

以下来自 European Systemic Risk Board 的出版物引用了CRI数据

Zheng, H., & Schwenkler, G. (2020). The network of firms implied by the news (2586097211; Working Paper No. 108; ESRB Working Paper Series). European Systemic Risk Board; ABI/INFORM Collection; Publicly Available Content Database.

以下来自 American Academy of Actuaries 的出版物引用了CRI数据

The Probability of Default Model for Insurance Companies in the United States of America, Canada, and France (Full Text) American Academy of Actuaries, May 18, 2023.

公司违约率 (PD)

关键事实

示例数据

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行业违约率

关键事实

示例数据

获取数据

CRI 中小微企业信用风险数据

~ 中小微企业风险评估与信用评价工具包 (TRACE) ~

关键事实

获取数据

自下而上的违约分析（BuDA）工具包

关键事实

压力测试情景示例

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