Public Finance Automated Scoring Tool (PFAST)
PFAST is an automated scoring and data solution to measure the credit quality and risks of State & Local Governments and Enterprise-driven segments, such as Water & Sewer, Not-For-Profit-Higher Education, Transportation, and Not-For-Profit Healthcare.
Market Intelligence
At S&P Global Market Intelligence, we understand the importance of accurate, deep and insightful information. Our team of experts delivers unrivaled insights and leading data and technology solutions, partnering with customers to expand their perspective, operate with confidence, and make decisions with conviction.
The Public Finance Automated Scoring (PFAST) dataset provides timely financial, economic and environmental information to help you streamline your credit scoring process. By providing both overall credit scores and specific credit risk indicators, you have access to a layered approach to help understand your overall credit risk and help clarify which risk factors are driving credit quality. More specifically, the PFAST dataset provides a granular, transparent, and consistent framework for the measurement and assessment of credit risk, getting immediate understanding of the changes in the credit quality of your municipal exposures as new financial results are released. The credit models (scorecards) deliver probability of default (PD) credit scores that are broadly aligned with S&P Global Ratings criteria. PFAST has more than 30,000 municipal rated and unrated entities and coverage of the major public finance segments including:
- U.S. Local and Regional Governments
- Water and Sewer Utilities
- Not-For Profit Healthcare
- Not-For-Profit Higher Education
- Transportation Infrastructure
PFAST automates your credit scoring process with access to financial, economic and environmental data from 2016 until today, and allows scoring thousands of entities in minutes by simply inputting an identifier. PFAST data gets updated monthly, ensuring you get access to the latest financial reports and economic information available on the market.
- Frequency
- Monthly
- Latency
- Ad Hoc
- Coverage Type
- Other
- Coverage
- 30000
- History
- 2016
- Earliest Significant Coverage
- 2016
- Point In Time
- Yes
- Point In Time Description
- Historical financial, economic, environmental and social data back to 2016. Credit Scores can be derived from 2016 to present.
- Data Source
- Financial Data - Electronic Municipal Market Access (EMMA). Economic Data - United States Census Bureau, Bureau of Economic Analysis (BEA) and Bureau of Labor Statistics. Credit Scores - Credit Assessment Scorecard Public Finance Automated Scoring Tool.
- Field Count
- 100s
- Estimated Size
- 0
- Added
- 2022-04-06
Geographic Coverage
- United States and Canada
Delivery
- API