Exercises: IFRS 9 Deep Practice
In Lessons 3 through 5, you learned IFRS 9 staging, the ECL formula, PD/LGD/EAD components, and macroeconomic scenario weighting. In Lesson 11, you saw how IFRS 9 interacts with Basel capital. Now you apply all of that knowledge to two extended exercises that mirror real-world portfolio assessment work: a UK retail mortgage stage assessment and a GCC corporate ECL model.
These exercises require you to make judgments; not just calculations. Staging decisions involve qualitative assessment of borrower circumstances. ECL models involve parameter choices that change the answer materially. The banking plugin's ifrs9-staging and ifrs9-ecl skills can assist with computation, but you drive the classification decisions and parameter selections.
Exercise 8: IFRS 9 Stage Assessment: Retail Mortgage Portfolio
Jurisdiction: United Kingdom (PRA regulated)
Duration: 35 minutes
Skills used: ifrs9-staging, ifrs9-ecl
Portfolio Data
You are the credit risk analyst for a UK building society. The following 8 mortgage facilities require stage assessment at the reporting date. For each facility, you have the current data and the relevant history.
| Facility | Balance | DPD | Rating at Origination | Current Rating | LTV | Additional Information |
|---|---|---|---|---|---|---|
| A001 | GBP 245K | 0 | A | A | 68% | Performing, no change in circumstances |
| A002 | GBP 380K | 0 | A | BBB | 71% | 2-notch downgrade since origination |
| A003 | GBP 190K | 35 | BBB | BB | 82% | 35 days past due, rating deteriorated |
| A004 | GBP 520K | 0 | A | A | 55% | Borrower recently notified bank of job loss |
| A005 | GBP 155K | 95 | BBB | CC | 88% | 95 days past due, severe deterioration |
| A006 | GBP 290K | 0 | BBB | BBB | 75% | Property value has fallen 15% since origination |
| A007 | GBP 410K | 0 | A | A | 61% | Performing, rate rise stress test shows affordability strain |
| A008 | GBP 175K | 62 | BB | B | 79% | 62 DPD, borrower has notified hardship |
ECL Parameters
| Parameter | Stage 1 | Stage 2 | Stage 3 |
|---|---|---|---|
| PD (12-month) | 0.8% | ( | ) |
| PD (lifetime) | : | 12% | 55% |
| LGD (LTV up to 80%) | 25% | 25% | 25% |
| LGD (LTV above 80%) | 40% | 40% | 40% |
Your Tasks
Step 1: Stage each facility. For each of the 8 facilities, determine whether it belongs in Stage 1, Stage 2, or Stage 3. Document your reasoning: which SICR triggers are present? Consider both quantitative indicators (DPD, PD/rating movement) and qualitative indicators (employment status, property values, hardship notification).
Quantitative triggers for Stage 2:
- Days past due of 30 or more (rebuttable presumption)
- Significant increase in PD since origination (typically 2+ notch downgrade or PD doubling)
Qualitative triggers for Stage 2:
- Significant adverse change in borrower circumstances (job loss, business failure)
- Material decline in collateral value affecting the credit decision
- Forbearance or modification granted
Stage 3 triggers (credit-impaired):
- Days past due of 90 or more
- Borrower in default (per the bank's default definition)
- Significant financial difficulty of the borrower
Step 2: Calculate ECL for each facility. Apply the appropriate ECL measurement:
- Stage 1: 12-month ECL = Balance x PD(12m) x LGD
- Stage 2: Lifetime ECL = Balance x PD(lifetime) x LGD
- Stage 3: Lifetime ECL = Balance x PD(lifetime) x LGD
Select the correct LGD based on the facility's LTV (25% for LTV up to 80%, 40% for LTV above 80%).
Step 3: Sensitivity analysis. If A006's property value falls a further 10% (LTV rises from 75% to approximately 88%), does the staging change? What is the ECL impact?
Step 4: Produce a provision movement summary. Create a stage distribution table showing:
| Stage | Number of Facilities | Total Balance | Total ECL |
|---|---|---|---|
| Stage 1 | ? | ? | ? |
| Stage 2 | ? | ? | ? |
| Stage 3 | ? | ? | ? |
| Total | 8 | ? | ? |
Step 5: Draft an IFRS 7 note. Write a one-paragraph summary suitable for the financial statements disclosure, describing the key credit risk characteristics of the portfolio and the staging distribution.
Exercise 9: Corporate ECL Model: GCC
Jurisdiction: Gulf Cooperation Council (multi-jurisdiction: KSA, UAE, Bahrain)
Duration: 55 minutes
Skills used: ifrs9-ecl, ifrs9-scenarios
Portfolio Data
You are building an ECL model for a GCC-based bank's corporate loan book. The bank operates across Saudi Arabia, UAE, and Bahrain. Six borrowers represent the key segments.
| Borrower | Country | TTC Rating | Drawn (USD M) | Undrawn (USD M) | Collateral | Sector |
|---|---|---|---|---|---|---|
| Al-Jazira Steel | KSA | BB+ | 85 | 25 | 40% plant and machinery | Manufacturing |
| Dubai Towers | UAE | BBB | 165 | 0 | Property LTV 72% | Real Estate |
| Gulf Energy | Bahrain | A- | 210 | 50 | Cash deposit + govt guarantee | Energy |
| Riyadh Retail | KSA | BB | 45 | 30 | Stock and receivables | Retail |
| Emirates Logistics | UAE | BBB- | 120 | 40 | Fleet assets 60% of drawn | Transport |
| Manama Finance | Bahrain | BB- | 60 | 20 | Nil collateral | Financial Services |
Through-the-Cycle PD Table
| Rating | TTC PD |
|---|---|
| A- | 0.4% |
| BBB | 0.9% |
| BBB- | 1.3% |
| BB+ | 1.8% |
| BB | 2.8% |
| BB- | 4.2% |
GCC Macro Adjustment
The GCC region's credit risk is sensitive to oil prices and GDP growth. Apply a base PD multiplier of 1.15 to convert TTC PDs to point-in-time PDs reflecting current GCC conditions.
Credit Conversion Factor (CCF): Apply 75% to all undrawn commitments.
EAD Calculation: EAD = Drawn + (Undrawn x CCF)
Macroeconomic Scenarios
| Scenario | Oil Price | GDP Growth | PD Multiplier | Probability Weight |
|---|---|---|---|---|
| Upside | $95/barrel | 3.5% | 0.85 | 20% |
| Base | $75/barrel | 2.2% | 1.15 | 50% |
| Adverse | $50/barrel | 0.5% | 1.65 | 30% |
LGD Assumptions
| Collateral Type | LGD |
|---|---|
| Cash deposit / govt guarantee | 15% |
| Property (LTV < 80%) | 30% |
| Plant and machinery | 45% |
| Stock and receivables | 55% |
| Fleet assets | 40% |
| Nil collateral | 70% |
Your Tasks
Step 1: Calculate EAD for each borrower. Apply the 75% CCF to undrawn commitments and add to drawn balances.
Step 2: Determine point-in-time PD under each scenario. For each borrower:
- Start with the TTC PD from the rating table
- Apply the scenario-specific PD multiplier
For example, Al-Jazira Steel (BB+, TTC PD 1.8%):
- Upside PD: 1.8% x 0.85 = 1.53%
- Base PD: 1.8% x 1.15 = 2.07%
- Adverse PD: 1.8% x 1.65 = 2.97%
Step 3: Calculate ECL under each scenario. For each borrower under each scenario:
- ECL = EAD x PD(scenario) x LGD
Step 4: Calculate probability-weighted ECL. For each borrower:
- Weighted ECL = (Upside ECL x 20%) + (Base ECL x 50%) + (Adverse ECL x 30%)
Step 5: Aggregate and analyze. Produce a summary table:
| Borrower | EAD | Upside ECL | Base ECL | Adverse ECL | Weighted ECL |
|---|---|---|---|---|---|
| Al-Jazira Steel | ? | ? | ? | ? | ? |
| ... | ... | ... | ... | ... | ... |
| Total | ? | ? | ? | ? | ? |
Step 6: Management discussion questions.
- Which borrower contributes the most ECL? Why?
- How sensitive is the total ECL to the oil price assumption?
- If you were to apply a Post-Model Adjustment (PMA), which sector would you target and why?
Try With AI
Setup: Use these prompts in Cowork or your preferred AI assistant.
Prompt 1: Reproduce
I have completed an IFRS 9 staging exercise for a UK mortgage
portfolio. Now I want to test my staging skills on a different
asset class. Here are 5 UK SME term loans:
B001: GBP 180K, 0 DPD, BBB to BBB, fully secured by equipment,
borrower's revenue fell 40% last quarter
B002: GBP 450K, 42 DPD, A to BBB-, secured by trade receivables,
2-notch downgrade, sector under government review
B003: GBP 95K, 0 DPD, BB to BB, unsecured, performing but
borrower in a sector with 15% default rate
B004: GBP 620K, 120 DPD, BBB to CCC, secured by property LTV 92%,
administrator appointed
B005: GBP 310K, 0 DPD, A to A, cash-secured, performing
For each: assign Stage 1, 2, or 3 with reasoning.
Then compare: how do SME staging decisions differ from mortgage
staging? What qualitative indicators matter more for SME than
for retail mortgage?
What you are learning: Staging principles are the same across asset classes, but the qualitative indicators change. SME lending introduces sector risk, revenue volatility, and complex security types that mortgages do not. By staging a different portfolio, you test whether you understand the SICR framework versus having memorised the mortgage answers.
Prompt 2: Adapt
I have built an ECL model for a GCC corporate portfolio
(Exercise 9). Now I want to stress-test it.
Scenario: Oil drops to $35/barrel and stays there for 18 months.
Regional GDP contracts 2.0%. Unemployment rises to 8%.
For this stress scenario:
1. What PD multiplier would you apply and why? (The base
multiplier is 1.15, the adverse is 1.65 at $50/barrel)
2. Which sectors are most affected: manufacturing, real estate,
energy, retail, transport, or financial services?
3. Should any borrowers migrate from Stage 1 to Stage 2 under
this stress? Apply the SICR framework.
4. How would LGD assumptions change for property-secured loans
if GCC real estate falls 35%?
5. Estimate the total ECL increase as a percentage of the
portfolio and explain the key drivers.
What you are learning: Stress testing reveals whether your ECL model captures tail risk. The oil price shock is the defining stress scenario for GCC banks because it cascades through government revenue, corporate earnings, property values, and consumer spending. By designing the stress yourself (rather than using pre-built parameters), you learn how macroeconomic variables translate into credit risk parameters.
Prompt 3: Apply
Using the GCC corporate ECL model results, answer:
1. Which borrower contributes the most to total ECL and why?
2. If oil drops to $35/barrel (PD multiplier 2.20), what is the
new adverse scenario ECL? How much does the total weighted
ECL increase?
3. Design a Post-Model Adjustment (PMA) for the real estate
sector (Dubai Towers). The model uses a 30% LGD based on
current property values, but GCC real estate has shown
40% price declines in past downturns. What PMA amount
would you recommend and what governance documentation
is required?
What you are learning: Sensitivity analysis reveals concentration risk: which borrower, sector, or scenario drives the most ECL volatility. PMA design bridges the gap between what the model captures and what professional judgment identifies as missing. The governance documentation requirement (approval, time-limiting, back-testing) ensures PMAs are not arbitrary adjustments but disciplined overlays.