With economic conditions shifting and audit season in full swing, it’s time to reassess where we sit in the economic cycle—and what that means for your IFRS 9 scenario weights.
In our latest Open Analytics webinar, Managing Director James O’Donnell and Senior Data Scientist Joshua Caboche unpacked the key question: Are our downside provisioning weights still appropriate?
Here’s what we learnt.
Do Economic Cycles Really Exist?
Sort of, but not in the textbook way we expect. Economic cycles are theoretically defined as periods of expansion and contraction in key indicators like GDP, unemployment, interest rates, and inflation. But real-world data can be messy. For example, Australia’s GDP data since 1985 shows only a few obvious contractions, with COVID-19 standing out as a clear but atypical disruption.
In lending, cycle effects are often more visible in arrears data. US data shows that property-secured lending experiences sharper swings in delinquency rates than consumer loans, and that downturn impacts can be highly industry-specific.
What Is the “Point in Cycle”?
“Point in cycle” is a term often used to describe how today’s economic conditions compare to historical norms.
Here is a methodical list of indicators used to identify the point in cycle using long-term distributions of economic indicators. For example:
- GDP is currently in the ~25th percentile, indicating a softer economic period.
- Unemployment and interest rates are better than average.
- Inflation has recently dropped back to near-target levels (2.1% at time of writing).
- House prices and default rates are hovering near long-term averages.
The upshot? Most indicators are average or better, with GDP as the main outlier.
How Often Do Downturns Actually Occur?
Looking at nearly 40 years of US data, moderate downturns occur roughly once every 10–15 years. Truly severe downturns, think GFC or Great Depression, are more like once-in-50-year events.
That frequency matters. If downturns are infrequent, it raises a key question: how much weight should we be assigning to downturn scenarios in our provisioning models?
How Bad Do Losses Get in a Downturn?
Losses vary significantly by asset class and scenario severity. For example:
| Asset Type | Long-Run Loss Rate | Severe Downturn | Scale Up |
| Residential Mortgages | 0.05% | ~1.0% | 20X |
| Asset Finance | 2% | ~9% | 4.5X |
| Unsecured High Interest Business Lending | 10% | ~35% | 3.5X |
| Credit Cards | 3% | ~7.5% | 2.5X |
These multipliers highlight how provisioning assumptions can dramatically change in stress conditions. Some Australian portfolios, particularly in commercial real estate during the GFC, experienced 20–30x loss multipliers.
Adjusting Scenario Weights: A Practical Approach
Here is a clear-eyed approach recommended by our experts:
- Keep your scenario definitions stable (e.g., 1-in-15-year moderate downturn; 1-in-50-year severe downturn).
- Adjust weights based on point-in-cycle evidence.
- Avoid over-reliance on econometric models. They require more data than most lenders have and can add noise rather than clarity.
So, where should scenario weights be today?
Given that most economic indicators are close to or better than average (except GDP), it’s reasonable to reduce weightings on downside scenarios. For example:
- A lender that previously had 30–40% weight on downturns might now dial that back to 10–15%.
- Hospitality lending is an exception. The sector continues to experience stress due to cumulative inflation impacts and should be treated separately.
Summary: A Return to the Long Run
Twelve months ago, higher downside weights made sense. But the data now suggests a return to a more neutral setting is appropriate. Most portfolios aren’t in stress, and downturns are rare.
Josh summed it up well: “We think that weighting should be heavily skewed to the long run, with stress scenario weightings significantly less than 12 months ago.”
Watch the Full Webinar
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