What are the various models to calculate expected credit loss? We provide illustrations to help Natural Resources companies decide what suits their portfolio best.
IFRS 9 governs the classification, measurement, impairment, and hedge accounting of financial instruments. It includes a forward-looking expected credit loss (ECL) model, applicable to various financial assets such as loans, trade receivables, and lease receivables. This approach is particularly relevant for the Natural Resources industry, where market volatility and long-term contracts pose unique credit risks.
What are the key provisions of IFRS 9?
1. Classification and measurement of financial instruments
Financial assets are divided into three categories:
- Amortised cost: Assets held to collect contractual cash flows, where those cash flows represent solely payments of principal and interest.
- Fair value through other comprehensive income (FVOCI): Assets held both to collect contractual cash flows and for sale.
- Fair value through profit or loss (FVTPL): Assets that do not meet the criteria for the other two categories or are designated as FVTPL at initial recognition.
Liabilities, on the other hand, remain largely unchanged from IAS 39, except for the treatment of changes in credit risk for liabilities designated as FVTPL, which now affects other comprehensive income (OCI) instead of statements of profit or loss.
2. Expected credit loss (ECL) model
The ECL model is applied to debt instruments measured at amortised cost or FVOCI, as well as to loan commitments, financial guarantee contracts, trade receivables, lease receivables, and contract assets. Its key aim is to provide a more predictive approach to credit loss provisioning. It requires companies to recognise credit losses based on expected future conditions, rather than waiting for a loss event to occur.
The ECL model operates in three stages:
Stage 1: This stage includes assets that have not experienced a significant increase in credit risk since initial recognition. For example, trade receivables from customers that have a strong credit rating, with no history of defaults or indications of financial distress. In this case, companies recognise a 12-month ECL representing the portion of the lifetime ECLs that are attributable to default events that could occur within the next 12 months. The 12-month ECL is calculated even if no default is expected.
Stage 2: Financial assets move from stage 1 to stage 2 if there is a significant increase in credit risk since initial recognition but the asset is not yet in default. An increase in credit risk is identified by factors such as deterioration in the customer’s credit rating, a missed payment, or changes in market conditions that may impact the customer’s ability to pay. In stage 2, companies recognise lifetime ECL by estimating the expected losses over the remaining life of the asset. These take into account both the likelihood of default and the potential loss should default occur.
Stage 3: This includes financial assets that are credit-impaired, where one or more credit events indicating default have already occurred. This could be if the customer or the borrower has missed several payments or entered bankruptcy. In this stage, a lifetime ECL is recognised, reflecting the reduced expectation of recovery.
ECL models used in practice
Companies determine the provision for ECL using a forward-looking approach that involves historical data, current conditions, and future forecasts. IFRS 9 principles expect them to use reasonable and supportable information (including forward-looking data) to estimate the likelihood of defaults and the amount of loss they are likely to incur. We explain some of the widely used ECL models below.
1. Probability of default (PD) approach
The PD approach is widely used by financial institutions but can be adapted to other sectors, such as Natural Resources. In this model, ECL is calculated by estimating the PD, loss given default (LGD), and exposure at default (EAD).
Probability of default (PD)
This is the likelihood that a borrower or counterparty will default over a specific period (12 months or the asset’s lifetime, depending on the stage). Companies estimate this based on historical default rates, credit ratings or other risk indicators.
Loss given default (LGD)
This represents the percentage of the exposure the company expects to lose if the borrower defaults, after accounting for any collateral or recovery. For example, if a loan is secured by a mine or equipment, the loss might be lower because the company can recover some value from the collateral.
Exposure at default (EAD)
This is the total amount the company expects to be owed if default occurs. For a trade receivable, the exposure is generally the unpaid invoice amount.
| Example: A UK-based mining company supplies iron ore to a steel manufacturer under a long-term contract. The receivable amounts to £1m and is due in five years. Stage 1: Initially, the steel manufacturer has a good credit rating and the company calculates a 12-month ECL: – PD: 2% chance of default within the next 12 months. – LGD: 40% recovery if default occurs. – EAD: £1m. ECL calculation: £1m × 2% × 40% = £8,000. Stage 2: After two years, the steel manufacturer shows financial distress due to increased competition and a downturn in the steel market. The company now calculates a lifetime ECL: – PD: 20% over the remaining life of the receivable. – LGD: 40% recovery. – EAD: £800,000 after partial payments. ECL calculation: £800,000 × 20% × 40% = £64,000. Stage 3: By the fourth year, the steel manufacturer defaults. The mining company reassesses and recognises a lifetime ECL based on actual default: – PD: 100% (full default). – LGD: 90% loss (minimal recovery expected). – EAD: £500,000. ECL calculation: £500,000 × 100% × 90% = £450,000. This model is used for complex financial assets and is not common within mining companies. |
2. Loss rate approach
The loss rate approach is another commonly used method for simpler portfolios, such as trade receivables. Under this method, loss rate statistics are developed based on the amount historically written off over the life of financial assets. This is particularly relevant for companies dealing with large volumes of short-term receivables in volatile markets, such as oil and gas producers selling to numerous small suppliers.
| Example: Loss rate approach for trade receivables A mining company, RockCo, has a portfolio of trade receivables worth £2m from various international buyers. Based on historical data, the company calculates a loss rate of 0.3% for its trade receivables. After adjusting for forward-looking conditions (such as a decline in demand for raw materials), the company expects the loss rate to rise to 0.5%. ECL calculation: £2m × 0.5% = £10,000 |
3. Simplified approach
For trade receivables and lease receivables, IFRS 9 allows companies to apply the simplified approach, which requires recognition of lifetime ECLs from the outset, without tracking credit deterioration.
| Example: Simplified approach for long-term contracts A UK-based oil extraction company, EnergyCo, sells crude oil under a long-term contract to a refinery, extending £1.5m in receivables. Under the simplified approach, EnergyCo recognises lifetime ECLs on day one. Given the historical default rate in the industry, the company estimates a 4% ECL. ECL calculation (simplified approach): £1.5m × 4% = £60,000 |
Example: A common arrangement in the mining industry is where a parent company grants a loan to a subsidiary, the repayment of which will begin when the subsidiary’s operations move from exploration to mining and subsequently, to production. The parent company must assess whether the loan, in substance, is to finance the exploration activities and therefore, a capital contribution. Such loans will be out of scope of IFRS 9 and be accounted for as a net investment under IAS 27. In cases where the parent company expects the loan to be repaid upon production, the parent company must assess ECL based on factors such as credit risk, timing of expected production, and jurisdiction of the subsidiary company.
What are the main considerations in an ECL model?
In the Natural Resources sector, the ECL model poses specific challenges due to the inherent risks associated with commodity prices, long-term contracts, and environmental regulations.
Below are some of the key factors and examples to consider while assessing ECL specifically for this industry.
1. Long-term supply contracts and trade receivables
Mining companies often have long-term supply contracts with customers. These can lead to significant trade receivables that need careful assessment under the ECL model. For example, a mining company that supplies iron ore to global steel manufacturers may have a high concentration of trade receivables from a few key customers. In this scenario, the company must assess the credit risk of each customer and recognise a 12-month or lifetime ECL based on their credit profile and market conditions.
2. Commodity price volatility and credit risk
Commodity prices are inherently volatile, which can impact the creditworthiness of counterparties in the supply chain. For example, if the price of copper were to fall significantly, a copper mining company might face increased credit risk from its customers, as their ability to pay could be compromised. In this case, the mining company would need to adjust its ECL model to reflect the increased risk, potentially moving receivables from stage 1 (12-month ECL) to stage 2 (lifetime ECL).
3. Loans to subsidiaries and related parties commitments
Companies often operate through foreign subsidiaries that engage in the mining and extraction process. The working capital required for these activities is provided by intercompany loans from the parent company. Under IFRS 9, these loan commitments and financial guarantees must also be assessed for ECL. For example, an oil and gas parent company with an offshore drilling subsidiary would need to estimate potential future losses on its loan commitments if the subsidiary becomes financially unstable due to fluctuating oil prices or operational risks.
4. Environmental and regulatory risks
The Natural Resources sector is subject to stringent environmental regulations, which can lead to operational and financial risks.
For instance, regulations on streamline energy and net zero commitments may mean a coal mining company supplying large quantities of coal to European power plants, under long-term contracts, faces difficulties in recovering its debts. Several countries in Europe are accelerating their transition to renewable energy, which may result in power plants to either shut down or invest heavily in cleaner technology. These regulatory shifts may increase the risk that power plants will be unable to honour their contracts for coal supply. The coal company must therefore reassess the creditworthiness of these customers, taking into account both environmental regulations and the likelihood of customers exiting the market or restructuring their operations.
If you would like further support on any of the issues raised in this article, please contact Nick Joel or Lakshmi Upadhyaya.
