IFRS 9 SCENARIO FRAMEWORK REQUIREMENTS
IFRS 9.5.5.17 requires: reasonable and supportable information about future economic conditions, including forward-looking information. This is not optional. Single-scenario ECL is non-compliant with IFRS 9.
SCENARIO STRUCTURE — MINIMUM AND BEST PRACTICE
Minimum (IFRS 9): base + 1 upside + 1 adverse Best practice: 4–5 scenarios with explicit probability weights
| Scenario | Typical Weight | Key Feature | | -------- | -------------- | -------------------------------------------- | | Upside | 10–20% | Above-trend growth, falling unemployment | | Base | 35–50% | Central forecast, moderate conditions | | Adverse | 25–35% | Mild recession, rising unemployment | | Severe | 10–20% | Deep recession, sharply falling asset prices |
Weights must: sum to 1.0; reflect management's genuine probability assessment; be documented and approved by the IFRS 9 Governance Committee. Equal weighting (25% each) is RARELY defensible and will be challenged by auditors.
KEY MACROECONOMIC VARIABLES BY ASSET CLASS
Retail mortgages: House Price Index (HPI), unemployment rate, base rate Consumer loans: Unemployment rate, disposable income index, base rate SME loans: GDP growth, SME default index, unemployment rate Corporate loans: GDP growth, corporate default rates, sector-specific indices Commercial Real Estate: CRE capital value index, vacancy rates, GDP growth
CREDIT CYCLE ADJUSTMENT (CCA) — CONVERTING TTC TO PIT PD
PIT PD = TTC PD x CCA CCA is estimated from a satellite model. Typical satellite model form: ln(CCA) = a + b1(GDP_growth) + b2(Unemployment) + b3(HPI_growth) + e
Example CCA values: Severe recession: CCA = 1.8–2.5 (PDs 80–150% above long-run average) Adverse: CCA = 1.2–1.5 Base: CCA ~ 1.0 (by definition — TTC PD already reflects long-run average) Upside: CCA = 0.7–0.9 (PDs below long-run average)
SATELLITE MODEL DETAIL
Model Structure
The satellite model links macroeconomic variables to credit risk parameters. Typical specification for a UK mortgage portfolio:
ln(Default Rate*t) = a + b1 Unemployment_t + b2 HPI_growth_t + b3 Base_Rate_t + b4 ln(Default Rate*{t-1}) + e_t
Key requirements for the satellite model:
- Estimated on a sufficiently long time series (minimum 1 full cycle, ideally 2+)
- Must include at least one recession period in calibration data
- Coefficients must have economically intuitive signs (e.g., higher unemployment
increases default rates)
- Out-of-sample validation required (typically holdout the most recent 2–3 years)
- R-squared typically 0.6–0.85 for well-specified models
Model Validation Requirements
- Annual independent validation by Model Risk Management
- Backtesting: compare predicted vs actual default rates over rolling windows
- Sensitivity testing: how much does ECL change for a 1pp change in each variable?
- Benchmarking: compare against external provider models (Moody's, Oxford Economics)
WEIGHTED ECL CALCULATION
Step 1: Calculate PIT PD for each scenario using scenario-specific CCA Step 2: Calculate ECL for each scenario: ECL_s = PD_PIT_s x LGD x EAD (Stage 1) or ECL_s = Sum_t [PD_marginal_t_s x LGD_t x EAD_t x DF_t] (Stage 2/3) Step 3: Weighted ECL = Sum_s (Weight_s x ECL_s)
NON-LINEAR EFFECTS
Weighted ECL != ECL at weighted-average PD (due to non-linearity in ECL formula). Always calculate ECL for each scenario separately, then probability-weight the results. The difference between these approaches (non-linear adjustment) is material for portfolios with high LGD or long remaining maturities.
Non-Linearity Worked Example
Portfolio: 1,000M gross carrying amount, LGD = 40%
| Scenario | Weight | PIT PD | ECL (PD x LGD x EAD) | | -------- | ------ | ------ | -------------------- | | Upside | 15% | 0.8% | 3.2M | | Base | 40% | 1.5% | 6.0M | | Adverse | 30% | 3.0% | 12.0M | | Severe | 15% | 6.0% | 24.0M |
Correct: Weighted ECL = 0.15 x 3.2 + 0.40 x 6.0 + 0.30 x 12.0 + 0.15 x 24.0 = 10.08M Wrong: Weighted PD = 0.15 x 0.8 + 0.40 x 1.5 + 0.30 x 3.0 + 0.15 x 6.0 = 2.52% ECL at weighted PD = 2.52% x 40% x 1,000 = 10.08M (linear case — same)
For lifetime ECL with compounding and discounting, the non-linear effect becomes material (typically 5–15% higher ECL when correctly scenario-weighted).
SCENARIO EXPLAINABILITY FOR GOVERNANCE COMMITTEE
For each quarterly scenario update, prepare:
- Scenario name and narrative description
- Key macroeconomic variables for each scenario (3-year forward path)
- Scenario weights and rationale for any weight changes from prior quarter
- ECL under each scenario individually
- Probability-weighted ECL (reported figure)
- Sensitivity: ECL if severe scenario were weighted 100% (IFRS 7 required)
- Changes from prior quarter: which scenarios/weights/variables changed and why
FORWARD-LOOKING HORIZON
Explicit forecast horizon: typically 2–5 years (period with supportable forecasts) Mean reversion: beyond explicit horizon, variables revert to long-run average over a reversion period (typically 2–5 additional years) Perpetuity: beyond reversion period, variables held at long-run average
GOVERNANCE OF SCENARIOS
Scenarios must be:
- Approved by the IFRS 9 Governance Committee before each calculation
- Sourced from a credible economic forecaster (internal Economics team or
external provider: Oxford Economics, Moody's Analytics, Bloomberg)
- Documented in detail in the IFRS 9 Governance Pack
- Disclosed (key variables and weights) in the IFRS 7 notes
Governance Calendar — Typical Quarterly Cycle
| Week | Activity | Owner | | ------- | ---------------------------------------------------- | --------------------- | | Week 1 | Economics team produces draft scenarios | Chief Economist | | Week 2 | Model Risk reviews satellite model outputs | Model Risk Management | | Week 3 | IFRS 9 Governance Committee reviews and approves | CRO / CFO | | Week 4 | ECL calculation run with approved scenarios | Finance / Credit Risk | | Week 4+ | Results reviewed, PMAs assessed, disclosures drafted | Finance |
OUTPUT FORMAT — SCENARIO SUMMARY
IFRS 9 SCENARIO SUMMARY
Reporting Date: [YYYY-MM-DD]
Entity: [Bank / Group name]
Approved By: [IFRS 9 Governance Committee, date]
SCENARIO DEFINITIONS:
| Scenario | Weight | GDP (Y1/Y2/Y3) | Unemployment (Y1/Y2/Y3) | HPI (Y1/Y2/Y3) |
|----------|--------|-----------------|--------------------------|-----------------|
| Upside | [%] | [%/%/%] | [%/%/%] | [%/%/%] |
| Base | [%] | [%/%/%] | [%/%/%] | [%/%/%] |
| Adverse | [%] | [%/%/%] | [%/%/%] | [%/%/%] |
| Severe | [%] | [%/%/%] | [%/%/%] | [%/%/%] |
ECL BY SCENARIO:
| Scenario | ECL (M) | vs Prior Quarter |
|----------|---------|------------------|
| Upside | [X] | [+/- Y] |
| Base | [X] | [+/- Y] |
| Adverse | [X] | [+/- Y] |
| Severe | [X] | [+/- Y] |
| Weighted | [X] | [+/- Y] |
SENSITIVITY (IFRS 7.35G):
100% Severe scenario ECL: [Amount] ([+X%] vs reported)
100% Upside scenario ECL: [Amount] ([-X%] vs reported)NEVER DO THESE
- NEVER use a single macroeconomic scenario for IFRS 9 ECL — this is non-compliant with IFRS 9.5.5.17 and will result in a qualified audit opinion
- NEVER apply equal scenario weights (25% each) without documented justification — auditors treat equal weighting as a rebuttable presumption of inadequate governance
- NEVER calculate ECL at the weighted-average PD instead of weighting scenario-level ECLs —