blog Market Intelligence /marketintelligence/en/news-insights/blog/best-practice-approach-for-calculating-portfolio-credit-risk content esgSubNav

In This List
Case Study

Best Practice Approach for Calculating Portfolio Credit Risk

Blog

Broadcast deal market recap, Q2'22

Blog

Balance Sheet Strategy in an Unusual Rate Environment

Blog

Investors' Views of the Industry Today & the Outlook for Tomorrow

Blog

Japan M&A By the Numbers: Q1 2022


Best Practice Approach for Calculating Portfolio Credit Risk

As a global independent asset manager specializing in private debt strategies, the firm originates asset-backed investment opportunities by financing real-economy businesses, such as trade financing solutions, largely in commodities and natural resources.

Looking to win additional mandates, the Risk team wanted to implement a more transparent approach to credit risk. They felt an “expected credit loss” (ECL) framework similar to the International Accounting Standards Board’s (IASB) IFRS 9 for banks would be ideal. IFRS 9 requires banks to recognize potential impairment sooner than in the past, and introduce forward-looking macroeconomic scenarios to more reliably capture losses.

The Risk team needed to adjust its internal models to reflect the IFRS 9 approach, and convert historical probabilities of default (PDs) to ones that were point-in-time (PiT) and capture macroeconomic variables. The Chief Risk Manager contacted S&P Global Market Intelligence (“Market Intelligence”) to discuss the type of information and support that was available.

The Solution:

Market Intelligence discussed a framework that could provide a globally-accepted methodology to transparently and effectively communicate underlying credit risk to investors. The approach uses Market Intelligence’s Credit Assessment Scorecards, which are Excel®-based tools that use forward-looking qualitative factors, converging trends and relationships between key drivers to derive a standalone PD score. The scores are broadly aligned to S&P Global Ratings criteria, and are further supported by historical default data back to 1981.

An IFRS 9 and ECL impairment overlay incorporates macroeconomic conditions, as well as market information, to adjust the Scorecard PD output. The adjustments consider reasonable and supportable current and forward-looking information to ensure that the Scorecards can produce one-year and lifetime PiT PD estimates.

Key Benefits:

The Scorecards provide a number of important benefits that the Risk team liked:

  • Useful for low default portfolios: Scorecards can be used when there is a lack of internal data available to construct statistical models that can be calibrated and validated.
  • Global sector-specific coverage: The Scorecards provide globally applicable sector and geographic coverage for all major asset classes.
  • Automated: Users can automate the spreading of financial data with an Excel Plug-In feature to eliminate time-consuming data entry and model adjustments.
  • Seamless updates: Market Intelligence’s rigorous annual review process validates the Scorecard methodologies and that the scoring criteria and User Guide are up-to-date.
  • Transparent: In-depth model development and maintenance documentation helps meet regulatory requirements by identifying how the Scorecard was developed, any limitations, use of data and overall performance.
  • Quickly deployed: Scorecards are an out-of-the-box solution, enabling users to free up resources for other value-added activities.
Learn More About Market Intelligence
Request Demo

Best Practice Approach for Calculating Portfolio Credit Risk

Click Here