Best Risk Data Aggregation Provider: S&P Global Market Intelligence

A multitude of factors can quickly change the credit health of counterparties and investments, from global slowdowns to supply-chain disruptions and new regulations. In today’s complex markets, vendors that offer deep views of credit risk and sophisticated analytics models and workflow tools have become invaluable. S&P Global Market Intelligence has made great strides with its Credit Analytics solution for global counterparty credit risk analysis and wins Best Risk Data Aggregation Initiative. 

Credit Analytics brings together financial and market data with credit scores, modelling tools and credit-specific data to deliver a powerful platform for users looking to run risk analysis on rated, unrated, public and private companies. The service is used by buy- and sell-side firms, as well as lending institutions, insurers and corporations. 

According to Whit McGraw, managing director of credit solutions, one of the most demanding challenges credit risk analysts face is a lack of globally consistent and universally comparable analytics. Credit Analytics helps by providing access to both fundamental and alternative data to assess credit risk where fundamental data is missing.

Over the past 12 to 18 months, the company has developed a raft of enhancements to the service to help companies better manage and aggregate risk. These include an aggregate dashboard that analyzes risk factors across a custom list of counterparties. These risk scores are visually displayed across global heat maps, as well as industry drill-downs and risk score distributions. Aggregate statistics are provided to understand the overall risk of a portfolio, and an alert functionality lets users monitor deteriorations in credit quality and be notified according to their preferences. 

Other recently added features include a Macro Scenario Analysis tool, with stress-testing capabilities on several macro factors, such as GDP growth, unemployment rates and index levels, which users can adjust to see the impact on the creditworthiness of a company. Users can also run ‘what-if’ scenarios—including Brexit-like simulations—to understand how each scenario may impact their focus companies. 

Earlier this year, the company increased coverage to more than 2.8 million companies through its Expanded Probability of Default (PD) methodology. Alongside the imputation methodology for partial financial statements, Expanded PD forms part of S&P Global’s Universal PD framework, which helps users produce risk assessments for counterparties based on limited financial data. 

Looking ahead, McGraw says the company will add “small and medium-sized enterprise fundamental data and alternative datasets to strengthen our coverage, new analytics on alternative data to provide key insights and early warnings, and we will continue to build tools that drive greater efficiencies into the workflows of our clients”. 

Read more about the Inside Market Data & Inside Reference Data Awards 2019 winners