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Robustness, Efficiency, and Transparency: Essentials for IFRS 9 Impairment Calculations


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).

Evaluate PD:

Many insurers continue to rely heavily on credit ratings and related data from recognized rating agencies, such as S&P Global Ratings. We use credit ratings in the first step of our IFRS 9 methodology for estimating ECLs.

We associate a long-term average default rate term structure (often labeled through-the-cycle) to each rating based on historical default data contained in our CreditPro product offering. This captures default data from over 40 years of credit ratings information from S&P Global Ratings1.

These historical default rate term structures are adjusted to point-in-time (PiT) PDs using the S&P Global Credit Cycle Projection Overlay, which adjusts PDs based on country-specific, forward-looking macroeconomic expectations and a broad array of asset classes. Factors include (but are not limited to):
  • GDP Growth
  • Unemployment
  • Equity index data
  • World Bank Energy Index
  • Portfolio stress (modelled via changes in downgrades)
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Evaluating LGD:

S&P Global Market Intelligence's LGD scorecards are used to estimate LGD term structures. These Scorecards are judgment-driven and identify the PiT estimates of loss. The Scorecards are back-tested to evaluate their predictive power on over 2,000 defaulted bonds.

The Corporate, Insurance, Bank, and Sovereign LGD Scorecards are linked to our fundamental databases, meaning no information is required from users for all listed companies and for a large number of private companies.

Final LGD term structures are based on macroeconomic expectations for countries to which these issuers are exposed.

Fundamental and macroeconomic data is provided by S&P Global Market Intelligence, but users can again easily utilize internal estimates.


Source: S&P Global Market Intelligence; for illustrative purposes only.
Evaluating ECL:

ECL is then estimated for each investment. The final calculation brings together the PiT PD, PiT LGD, EAD, and effective interest rate (EIR) to estimate the present value of the discounted cash shortfalls (i.e., ECL).

Source: S&P Global Market Intelligence; for illustrative purposes only.

Technology & Delivery:

We offer a fully flexible approach to the delivery of our solutions to meet your specific needs. All solutions are offered in Microsoft Excel® to facilitate an easy implementation into your internal capabilities. Should you require a software solution, we also provide end-to-end computational and reporting engines, which can help streamline the calculation and reporting processes for the entire IFRS 9 standard.

Watch what S&P Global Market Intelligence’s thought leaders have to say about IFRS 9 impairment and join a perspective you can trust.



Contact us to enquire about our IFRS 9 Solutions
1S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD credit model scores from the credit ratings issued by S&P Global Ratings.
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