IFRS 9 is a reporting standard for financial instruments that replaces IAS39 (the previous incurred loss standard) with the introduction of provisions for expected credit losses (ECLs) on all financial assets, such as those held to collect contractual cash flows, or held with the possibility of being sold.

The date for adoption was January 1, 2018 and is mandatory for public non-financial corporations (and financial institutions) across a number of jurisdictions outside the United States, including many European countries.

The two key changes introduced by the IFRS 9 accounting standard are:

• Calculation and provisions must be performed on all affected financial assets, not just the impaired ones, as per the standard it replaces
• New expected credit loss calculations

Additional challenges will be presented when making assessments for low default asset classes, and companies may find it difficult to access models and sufficient data history.

Impact for non-financial corporations

Non-financial corporations will have some material exposure to many of the financial assets that are defined under IFRS 9. These include investment portfolios, intercompany loans, lease receivables, contract assets, and trade receivables, as illustrated below and further explained in our webinar on IFRS 9 for non-financial corporates.

This, together with the need to assess losses on performing and non-performing assets, might have a material impact on the profit and loss (P&L) of such companies.

ECL calculations under IFRS 9

The IFRS 9 accounting standard introduces new expected credit loss (ECL) calculations that require more data and new models. The key requirements are:

• Significant increase in credit risk (SICR): Expected loss needs to be assessed at each reporting period to identify a SICR since initial recognition
• Explicit macro-economic forecasts need to be considered using factors such as the relevant GDP growth, unemployment rate, and stock market index growth figures
• Credit risk metrics such as probability of default (PD), credit rating, credit score, and loss given default (LGD) need to be adjusted to point in time (PiT), versus through the cycle (TTC)
• Calculations need to be extended over the lifetime of the assets for underperforming exposures, or in standardized calculations

General versus simplified approach

When performing ECL calculations for trade receivables, the company can choose to take a general or simplified approach (the company is presented with a choice between the two depending on the type of exposure).

• The general approach uses the 12-month ECL calculation for performing assets (Stage 1 assets) and lifetime calculation for the assets whose creditworthiness has deteriorated since recognition (Stage 2 assets)
• The simplified approach uses the lifetime ECL calculation for all performing and non-performing assets

The simplified approach can have a bigger impact on P&L expense, as all losses are calculated over the lifetime of the asset, while the general approach can have more impact on P&L volatility, as assets might move between stages incurring 12-month and lifetime calculations.

How S&P Global Market Intelligence can help

A best practice approach used by many financial institutions, which non-financial corporations can also use to comply with the new provision, is to use the existing TTC metrics and convert them into PiT metrics to reflect the current credit cycle, as well as include the required future macroeconomic considerations.

S&P Global Market Intelligence has developed models and tools to help your business undertake the relevant ECL calculations. These models can also be used to assess the creditworthiness of your counterparties and recovery of your exposure in the context of your core business process such as customer credit, supply chain risk, vendor management, and selection and transfer pricing.

The calculation method involves four steps:

1. We calculate the TTC metric, i.e. the S&P Global Market Intelligence Fundamental PD, CreditModel™ score, for the concerned entity.
2. We apply our macro-economic model, which weights user defined macro-economic scenarios to produce weighted average forecasted PDs.
3. We apply a credit cycle adjustment, which converts the TTC risk metric into a PiT PD, leveraging the difference between observed default rates from S&P Global Ratings’ rated universe over last year versus over the past 30+ years.
4. In addition, as a best practice, we also offer the option to incorporate market-based forward looking information. This is done by further adjusting the PD with the analysis of PD Market Signals country and industry benchmark trends over the past three months versus the past year.

In addition to this quantitative approach available on the Credit Analytics platform, we also offer scorecards that cover low default asset classes for PD, LGD, and point in time adjustments.