IFRS 9 Impairment Calculation Challenges During The .
IFRS 9 Impairment Calculation Challenges duringthe Pandemic – an Updated Benchmark StudyOctober 2020
Agenda1.2.3.4.Overview of Benchmarking MethodologyChallenges and a Potential Solution when Applying Extreme ScenariosAlign Point-in-Time Credit Assessments and Baseline Scenario ForecastPractical Implementation Challenges (Product Showcase)IFRS 9 Benchmark Study, October 20202
SpeakersYashan Wang, Senior Director, Quantitative ResearchSean Evans, Associate Director and Senior Product ManagerJoint work with May Jeng and Warren XuIFRS 9 Benchmark Study, October 20203
Evolving Macroeconomic Environment and OutlookUK GDP (March 2020 Scenarios)UK GDP (December 2019 Scenarios)240024002200220020002000BaselineMar 21Dec 20Sep 20Jun 20Dec 19Dec 22Sep 22Jun 22Mar 22Dec 21Sep 21Jun 21Mar 21Dec 20Sep 20Jun 20Mar 201600S1S3Dec 221600Dec 19Dec 22Dec 20Sep 201800S3Sep 22S1Reporting Date 30 September 2020Jun 22BaselineJun 20UK GDP (September 2020 Scenarios)Reporting Date 30 June 20201800S3Mar 222400Mar 20Dec 19Dec 22Sep 22Jun 22Mar 22Dec 21Sep 21Jun 21Mar 21Dec 20Sep 20Jun 20Mar 20UK GDP (June 2020 Scenarios)S1Sep 22Baseline1600Dec 191600Jun 221800S3Dec 21S1Sep 21BaselineJun 211800Mar 222000Dec 212000Sep 212200Jun 212200Reporting Date 31 March 2020Mar 21Reporting Date 31 December 2019Mar 202400IFRS 9 Benchmark Study, October 20204
Modeling FrameworkMacroeconomic Scenario ForecastsScenario Probability WeightsGCorrTM Macro 2019 to Calculate ScenarioConditioned PD & LGD Staging DecisionsMoody’s Analytics Through-the-Cycle (TTC) toPoint-in-Time (PIT) PD ConverterDefault and Recovery Risk Measures» Forecasts of GDP growth, unemployment rate, equity priceindex, oil price, etc.» Multiple scenarios including: baseline, upside (S1), anddownside (S3)» Moody’s preset (Baseline-40%, S1-30%, S3-30% inthis study) or client inputXExposureat DefaultXDiscountFactor ExpectedCredit Loss» Produce PIT PD term structures; the underlying PIT PDs arefrom the Moody’s Analytics CreditEdgeTM EDF (ExpectedDefault Frequency) model» Through-the-Cycle PD, or external or internal rating» LGD (assumed 40%)IFRS 9 Benchmark Study, October 20205
C&I Benchmark Portfolios and Their CharacteristicsPortfolioBalance PercentageInvestment GradeHigh YieldYear to Maturity(years)Main Industries(% of balance)Bank and Savings & Loans (44%)Europe76%24%2.75Business Services (14%)Agriculture (4%)Bank and Savings & Loans (18%)Middle East52%48%2.50Construction (16%)Consumer Services (9%)Bank and Savings & Loans (21%)North America52%48%2.50Oil Refining (6%)Telephone (5%)» Three C&I portfolios are constructed and used in the study, reflecting the footprints of clients’ portfolios» Portfolio characteristics (such as time to maturity) are held unchanged in all the runs» The Middle East and North America portfolios include exposures to countries in those regions, respectively. Most of theexposures in the Europe portfolio are in European countries. However, the Europe portfolio also includes exposures tocountries outside Europe, including Asia Pacific (China, Japan, Australia, Korea, India, etc.) and South America (Brazil,Chile, Argentina, etc.)» Due to the lack of information of credit quality at origination, a simple absolute threshold is used in stage allocation:Probability weighted PDs are mapped to a Moody’s rating, and B1 rated or worse credits are assigned to Stage 2IFRS 9 Benchmark Study, October 20206
Recent Macroeconomic Dynamics Are Different from the PastUK GDP Level in Moody’s Analytics June 2020 Baseline Scenario as an ExampleUK GDP LevelLog Return of UK GDP Level24000.122000.0502000-0.051800Mar 26Mar 24Mar 22Mar 20Mar 18Mar 16Mar 14Mar 12Mar 10Mar 08Mar 06Mar 04Mar 02Mar 26Mar 24Mar 22Mar 20Mar 18Mar 16Mar 14Mar 12Mar 10Mar 08Mar 06-0.2Mar 041400Mar 02-0.15Mar 001600Mar 00-0.1» In addition to the extremely low level reached in Q2-2020, the pace of the changes and the huge swing of the UK GDP inQ2-2020 and Q3-2020 (shown in the right chart above) are truly unprecedented in many decades. Care must be givenwhen applying these scenarios on the GCorr Macro model that was estimated with data up to 2019IFRS 9 Benchmark Study, October 20207
How MEVs are used in Scenario ConditioningLog Return of UK GDP Level – June BaselineUK GDP Level – June Q15Q14Q13Q12Q11Q10Q9Q8Q7Q6Q5Q4Q3Q2-0.2Q1Dec 23Sep 23Jun 23Mar 23Dec 22Sep 22Jun 22Mar 22Dec 21Sep 21Jun 21Mar 21Dec 20Sep 20Jun 20Mar 201400Forecast Quarter» Similar to other scenario conditioning models, GCorr Macro calculates the log return in an MEV (such as UK GDP) in each currentquarter from the previous one to represent the negative or positive macroeconomic effect in that quarter. The upper right chartshows the log returns in the forecast quarters, starting from the first one corresponding to Q3-2020» As of 30 June 2020, the UK GDP shows a large positive return (i.e., positive impact to the economy) based purely on its path in Q2and Q3-2020. This return signals a significant improvement in the economic environment, which few people would find intuitive.Such a return calculation for Q3-2020 does not take into account the sudden and large drop of the UK GDP in Q2-2020 that stillaffects the economy in Q3-2020 and beyondIFRS 9 Benchmark Study, October 20208
A Potential Solution to Q2 ECL CalculationLog Return of UK GDP Level – June BaselineUK GDP Level – June d ScenarioUnmodified Scenario1600-0.15Modified ScenarioModified c 23Sep 23Jun 23Mar 23Dec 22Sep 22Jun 22Mar 22Dec 21Sep 21Jun 21Mar 21Dec 20Sep 20Jun 20Mar 201400Forecast Quarter» To overcome the challenges in applying the GCorr Macro model on macroeconomic scenarios where MEV values exhibittruly unprecedented magnitude of change and oscillation in Q2-2020 and Q3-2020, one can incorporate the lasting impact ofthe severe negative shock in Q2-2020 by replacing the MEVs in Q2-2020 with their Q1-2020 values» For example, the UK GDP of 2020Q1 is 2053. The forecasts of 2020Q2 and 2020Q3 are 1762 and 1912, respectively. Themodified log return for 2020Q3 is calculated as ln(1912/2053) -0.07 instead of ln(1912/1762) 0.08* The technique of replacing 2020Q2 MEVs with their values of 2020Q1 is also applied in a separate study of default risk reporting and projection by Moody’s Investors Service. See “DefaultTrends – Global: May 2020 Default Report,” available on moodys.com after registration.IFRS 9 Benchmark Study, October 20209
IFRS 9 Impairment Benchmark ResultsPortfolioIFRS 9 ECL RateAnalysis RunS1EuropeMiddle EastNorthAmericaQ2-2020 without Scenario ConditioningQ2-2020 – Unmodified June ScenariosQ2-2020 – Modified June ScenariosQ2-2020 without Scenario ConditioningQ2-2020 – Unmodified June ScenariosQ2-2020 – Modified June ScenariosQ2-2020 without Scenario ConditioningQ2-2020 – Unmodified June ScenariosQ2-2020 – Modified June .28%3.05%4.73%1.29%4.30%One-YearECL 6%2.21%» Without scenario modification, Q2-2020 ECL rate under the June Baseline scenario is significantly lowerthan that before scenario conditioning» With the simple scenario modification, the Baseline ECL rate is mildly higher than that before scenarioconditioning, reflecting the common perception of economic outlook at the end of Q2-2020» The behavior is similar in the Middle East and North AmericaIFRS 9 Benchmark Study, October 202010
Scenario Patterns in Sept Are More Involved than those in JuneWith more variation across countries and MEVs than Q2» Different from Q2 reporting, where virtually all macroeconomic variables portray a similar pattern, September scenarios callfor additional ruminations in Q3 reporting» Depending on the country and MEV set, different scenario treatments might be appropriate to true economic environmentand outlook; management overlay is often necessaryUK GDP Level – September ScenarioDenmark Equity Index Level – September Scenario240018002200150020001200Unmodified Scenario1800Modified Scenario1600Unmodified Scenario900Modified Scenario600Dec 23Sep 23Jun 23Mar 23Dec 22Sep 22Jun 22Mar 22Dec 21Sep 21Jun 21Mar 21Dec 20Sep 20Jun 20Mar 20Dec 23Sep 23Jun 23Mar 23Dec 22Sep 22Jun 22Mar 22Dec 21Sep 21Jun 21Mar 21Dec 20Sep 20Jun 20300Mar 201400IFRS 9 Benchmark Study, October 202011
Align PIT Credit Assessments with Baseline Scenario ForecastUS unemployment rate at the June 2020 launch-off date as an exampleBaseline - Median ScenarioThe approach aligns the conditional PDs with theassumption that the Baseline scenario is theS1 - Upside, 10th Percentilecurrent market’s central forward-lookingprojectionS3 - Downside, 90th PercentileHistorical DataNegative shockrelative to BaselinePercentage15105ScenarioDistributionfrom June 2020Positive shockrelative to BaselinePIT PD as of the Launch-off dateassumes that the Baseline Scenario isthe median macroeconomic scenario.0June 2020Launch-off dateIFRS 9 Benchmark Study, October 202012
Summary and Take-away» COVID-19 has led to unprecedented macroeconomic environment and outlook that are often out ofthe expected range of model inputs» Scenario-conditioning models that are calibrated with pre-COVID data may not be able to producesensible results when they are applied to macroeconomic forecasts showing huge changes andswings» In some situations, a relatively simple adjustment on the timing of economic variables may helpcapture the sensitivities to macroeconomic factors representative of the credit environment» The same treatment may not work as well in other situations. Aligning Point-in-Time creditassessments with Baseline scenario forecast has the potential of producing sensible and stableresults even under extreme scenariosIFRS 9 Benchmark Study, October 202013
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IFRS 9 Benchmark Study, October 2020 9 A Potential Solution to Q2 ECL Calculation » To overcome the challenges in applying the GCorr Macro model on macroeconomic scenarios where MEV values exhibit truly unprecedented magnitude of change and oscillation in Q2-2020 and Q3-2020, one can incorporate the lasting impact of
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