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.
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.
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.
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Best Practice Approach for Calculating Portfolio Credit Risk