Your credit risk management toolkit.

Efficiently evaluate probabilities of default based on S&P Global Ratings' default and ratings migration data covering 17,000+ companies, 130,000+ securities, 120,000+ structured finance issues, and 160+ sovereign entities across the globe.

This robust analytic tool helps you formulate future default and ratings migration scenarios, and validate internal rating systems used for credit risk analysis. Consistently defined, measured, and maintained—CreditPro^® provides comprehensive data sets that support the development, calibration, and backtesting that analytical risk valuation models must meet today.

Each day you face the challenges of monitoring transactions in a constantly evolving, cutting-edge market where no two deals are alike. Managing a Structured Finance portfolio is a complex job with many moving pieces. We can help you monitor and evaluate structured finance securities—with the latest global structured finance research, industry news, and sector trends, to servicer evaluations.

Power your mortgage risk analysis by using residential mortgage loan characteristics, borrower data and regional economic data from S&P Global Ratings’ Loan Evaluation and Estimate of Loss System (LEVELS). Evaluate credit risk and best-execution securitization scenarios with in-depth loan-level analysis and reports with estimates of loan/pool-level performance.

The Public Finance Automated Scoring Tool (PFAST) synthesizes multiple statistically validated probability of default (PD) and loss-given default (LGD) Scorecard methodologies, quantitative and qualitative segment-specific risk factors and market benchmarks into a single, robust internal ratings framework, helping you identify and manage PF credit risk.

The PFAST Scorecard provides a powerful capability to consistently measure credit risks across all the different public finance segments.

• Automated quantitatively derived PFAST Scores for all U.S. cities, counties, school districts and states
• Rigorous, tested and documented approach supported by scoring criteria, user and technical documentation
• A large and continually growing database of municipal entities financials and economic data for the major PF segment
• PFAST enhances consistency and transparency of internal rating systems in an easy to understand approach
• Ability to tap into a detailed source of PF credit risk data and generate automated scores in key segments

Climate change has created a need to evaluate the impact of different climate-related scenarios on counterparties, investments, and portfolios. To support these efforts, S&P Global Market Intelligence and Oliver Wyman present Climate Credit Analytics, a climate scenario analysis and credit analytics model suite. These tools combine S&P Global Market Intelligence’s data resources and credit analytics capabilities with Oliver Wyman’s climate scenario and stress-testing expertise.

This solution is powered by S&P Global Market Intelligence’s proprietary datasets, including:

• Financials and industry-specific data
• Quantitative credit scoring methodologies from Credit Analytics
• Company-level greenhouse gas (GHG) emissions and environmental impact data from Trucost
• Global supply chain and shipping data from Panjiva

Our cutting-edge analytical models and unrivalled data help you quickly and easily measure the credit risk of rated, unrated, public and private companies across the globe.

• PD Model Market Signals provides a point-in-time view of credit risk, and early warning signals of potential default between reporting periods, for 82,000+* public companies. Download the brochure >
• PD Model Fundamentals identifies potential default by assessing financial risk, and business risk. Calibrated on +15 years of defaults, and available for more than 5 million* public and private companies. Download the brochure >
• CreditModel™ is a powerful suite of over 100 statistical models, trained on credit ratings from S&P Global Ratings, help you evaluate the long-term creditworthiness of public and private, rated and unrated companies. Pre-scores available for over 182,000* companies worldwide. Download the brochure >
• The Macro-Scenario Model enables users to gauge how a firm’s credit risk may change by leveraging either user-defined or pre-defined forward-looking macroeconomic scenarios. Download the brochure >

*Pre-score coverage as of August 13, 2021 for recalibrated models.

Having an exposure to a distressed firm, and a potential default is a real possibility. Your concern drives not only from the possibility of that default, but what you can expect to recover, or lose, if default occurs. Understanding potential recovery and a default can be hard to accomplish, with many approaches relying on standardized assumptions. With LossStats Model you have an alternative.

This default and recovery approach helps you estimate the loss and recovery levels of US and European fixed income and lending facilities, taking into account industry and instrument specific characteristics. Calibrated upon a proprietary database covering more than 4,000 US bond and loan recoveries spanning over 30 years, and 1,000 European bond and loan recoveries spanning over 13 years.

The China Credit Analytics platform integrates S&P Global Market Intelligence's localized credit analytics, featuring data from over 20 million Chinese private companies and our quantitative credit models calibrated to local default data.

It offers a one-stop-shop solution for users to search, evaluate, and monitor the credit profiles of Chinese Small and Medium-sized Enterprises (SME).

Generate credit insights on Chinese Small and Medium-sized Enterprises (SME) using differentiated content and localised analytics with outputs that broadly align with credit ratings.

• Search and screen over 20 million Chinese private companies.
• Utilize S&P Global Market Intelligence's Probability of Default Fundamental (PDFN) model calibrated to Chinese default data to analyze local companies in China.
• Leverage the credit workflow tools to perform batch scoring and the credit risk dashboard to visualize a credit profile for a portfolio of entities.
• Access 1 million larger Chinese SME's pre-scored Probability of Defaults with industry and provincial level benchmarks.
• Take advantage of the dual language user interface that supports both Chinese and English languages.

Refine the assessment of your potential exposure to defaults with our Loss Given Default (LGD) models and scorecards for low default asset classes.

Evaluate potential economic losses on a continuous scale with models that employ S&P Global Ratings’ analytical methodologies, proprietary research, and historical data. By incorporating qualitative and quantitative factors, our models and scorecards focus on sectors where default, and therefore recovery data, is scarce. This allows you to:

• Meet Basel regulatory requirements by implementing LGD methodologies.
• Validate and benchmark existing models and methodologies with LGD client data pooling and collection exercises. 
• Produce facility-specific estimates of LGD in the low default environment with internal ratings-based methodology.

International Financial Reporting Standards 9 (IFRS 9) requires firms to take account of future expected credit losses (ECLs) to calculate provisions for their financial instruments, investment portfolios, loan books, and trade receivables. This change requires the use of forward-looking analytics. With deadlines fast approaching, are you prepared for the transition?

IFRS 9 addresses the accounting for financial instruments and contains three main topics:

• Classification and measurement of financial instruments.
• Impairment of financial assets.
• Hedge accounting.

Our approach follows the traditional method of estimating ECL from its base components: Probability of Default (PD), Loss Given Default (LGD, which is the severity of loss in the event of default), and Exposure at Default (EAD).

S&P Global Market Intelligence’s Credit Assessment Scorecards provide a structured framework for assessing credit risk, generating credit scores that are designed to broadly align with credit ratings from S&P Global Ratings.^[1]

Our Scorecards enable ESG factors to be considered in credit risk analysis in a transparent and structured way, while working through the regular credit assessment process.

For each of the three ESG dimensions, we first define the ESG credit risk factors, which are the factors that influence the capacity and willingness of an obligor to meet its financial commitments and that can have negative or positive credit impacts.

We then provide guidance on how to integrate these factors into the credit assessment. This analytical process remains mostly evidence-based, qualitative and, accordingly, rules driven.

You need the right data to make the right decisions, and you need to get it quickly. With RatingsXpress^®, you’ll receive S&P Global Ratings credit ratings in bulk when you need them most.

Power portfolio and enterprise risk functions, represent your portfolio in public, statutory, and regulatory reports, with access to ratings data through S&P Global Market Intelligence, via third-party datafeeds or desktop platforms.

Through our integrated bulk feed management solution, ratings content is organized into packages defined by issuer sectors and contains issuer-and issue-level details, plus extensive descriptive data for each instrument. Our solution also offers delivery of credit ratings from Moody’s Investor Services, Fitch Ratings, Japan Credit Ratings, and Rating and Investment Information Inc.

Easily tap into the ratings and analysis you need to help make informed financial decisions with CreditWire®, available on the Bloomberg Professional™ platform.

CreditWire keeps you connected to the fixed-income market and on top of ratings actions as they occur. Comprehensive analysis brings you an understanding of the underlying credit forces and critical trends in the industries you follow.

Our broad coverage provides access to ratings, credit news, summary analyses, research updates, daily ratings screens, and CreditWatch lists for the Global Issuers, Structured Finance, and U.S. Public Finance sectors.