For trade receivables and contract assets, the ECL model replaces the traditional approach of measuring bad debt reserves. For trade receivables and contract assets with no significant financing component, IFRS 9 allows a simplified approach using a lifetime ECL measurement regardless of whether a significant increase in credit risk has been observed. IFRS 9 requires discounting of expected credit losses, but for trade receivables and contract assets without a significant financing component that are short term, it may be possible to conclude that discounting is not material.
For trade receivables or contract assets with a significant financing component and for lease receivables, companies can elect to apply the ECL simplified approach or the ECL general approach. The simplified approach is less complex, but could result in a higher ECL value under most circumstances. Furthermore, the ECL of such assets should be discounted using the original effective interest rate.
Provision matrix
IFRS 9 provides a credit risk measurement practical expedient in the form of a provision matrix5 that may be appropriate. The provision matrix approach takes historical trade receivable balances over a period of time, disaggregated based on credit risk characteristics, and divides them into delinquency categories – e.g. current, up to 30 days past due, between 31-60 days past due, and so on.
Using the historical data, it is possible to determine the rate at which debtors move into a worse delinquency category as time passes and then determine, using matrix multiplication, a loss rate for each delinquency category.
The loss rate must be adjusted for current conditions and also for 'reasonable and supportable’ forecasts of future economic conditions over the remaining life of the trade receivables. These loss rates are then applied to the reporting date outstanding receivables balance by delinquency category to determine the ECL allowance.
This approach may seem similar to how many corporates historically measured their bad debt provisions. However, because IFRS 9 requires that loss rates reflect relevant, reasonable and supportable information about future expectations, bad debt provisions under IFRS 9 will likely be higher than under the previous incurred loss approach.
Here is an illustrative example of a provision matrix (source: KPMG’s IFRS 9 for Corporates).
Delinquency category | Loss rate | Trade receivables | ECL allowance |
---|
Current
| 0.3%
| 15,000
| 45
|
1-30 days past due
| 1.6%
| 7,500
| 120
|
31-60 days past due
| 3.6%
| 4,000
| 144
|
61-90 days past due
| 6.6%
| 2,500
| 165
|
Over 90 days past due
| 10.6%
| 1,000
| 106
|
Total
|
| 30,000
| 580
|
A provision matrix is an effective way of measuring ECL consistently from period to period. It may prove especially appropriate for corporates with a high volume of sales and cash collections from trade receivables. However, corporates should use appropriate groupings of trade receivables based on credit risk characteristics (e.g. geography or debtor credit rating), and determine loss rates by group of similar risk characteristics.
Corporates with highly seasonal revenue patterns, however, may turn to other methods. This is because cash collections from trade receivables either may not follow a linear pattern or may peak dramatically at certain points during the fiscal year. Using a provision matrix approach in such cases could result in loss rates that are not suitable for ECL measurement.
Arguably the most challenging aspect of applying IFRS 9 ECL to trade receivables is the concept of reasonable and supportable forecasts and how to integrate this into the ECL calculation. This forward-looking estimate should take into account changes in macro-economic conditions that impact the ability of debtors to continue to pay.
KPMG observation
For many corporates, lacking past experience in forecasting or using economic data in loss estimation, meant that there has been a learning curve in incorporating this into ECL measurement. Most do not have the luxury of having an in-house economist, but have instead purchased external subscriptions to obtain forecast economic data. This creates an additional layer of data used in making financial estimates and must be subject to its internal control processes.
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