1. IFRS 9 Implementation Challenges
IFRS 9 Implementation Challenges
22 October 2014
The presentation summarises the key provisions of the new IFRS 9. The Standard was issued in July 2014 and is effective for annual periods commencing on or after 1 January 2018.

2. Agenda
Background to IFRS 9: The project and timetable for implementation
Classification and measurement
Overview of Expected credit losses in IFRS 9
Implementation Challenges
Conclusions
This slide deck is intended to help engagement teams to discuss the IFRS 9 requirements with their clients. Please note that this slide deck covers Classification and Measurement of debt instruments and Expected credit losses. It will not include aspects of IFRS 9 that have not changed such as equity instruments. A separate slide deck is available on PwC Inform for the hedging section in IFRS 9. The own credit requirements for financial liabilities that were issued with the Hedging section are also included in this guidance at the end of the classification and measurement section.
In Depth publications are available on PwC Inform which address the three sections of IFRS 9:
Classification and measurement (
Expected credit losses ( and
Hedging (
IFRS 9 Implementation Challenges
22 October 2014

3. Background to IFRS 9: The project and timetable for implementation1
IFRS 9 Implementation Challenges
22 October 2014

4. Effective date and transition Overview
The effective date will be for annual periods starting on or after 1 January 2018.
Retrospective application is required except:
If on transition application requires undue cost or effort, operational simplifications are provided.
No requirement to restate comparatives.
The effective date will be annual periods starting on or after 1 January 2018.
The Standard requires retrospective application:
a) At the date of initial application an entity has to assess whether a financial asset meets the conditions to be classified as amortised cost or as at FVOCI on the basis of the facts and circumstances that exist at that date. The resulting classification shall be applied retrospectively irrespective of the entity’s business model in prior reporting periods.
b) An entity should use the credit risk at initial recognition for existing financial assets when initially applying the ECL model, unless obtaining such credit quality information requires undue cost of effort.
The Standard provides some operational simplifications in case the requirements set above cannot be met:
Operational simplifications for ECL model
An entity may apply the low credit risk simplification to identify financial instruments for which the credit risk has not significantly increased. An entity could approximate the credit risk on initial recognition by considering the best available information that is available without undue cost or effort. The best available information is information that is:
Reasonably available and does not require the entity to undertake an exhaustive search for information; and
Relevant in determining or approximating the credit risk at initial recognition.
When approximating the credit risk on initial recognition, an entity could:
Apply the rebuttable presumption for contractual payments that are more than 30 days past due, if the entity identifies increases in credit risk according to days past due; or
Operational simplifications for C&M
If requirements to apply the provisions related to assessing the modified time value of money element based on the facts and circumstances that existed at the initial recognition of the financial asset require undue cost or effort, an entity shall assess the contractual cash flow characteristics of that financial asset based on the facts and circumstances that existed at initial recognition without taking into account the requirements related to the modified time value of money.
If assessing whether the fair value of a prepayment feature was insignificant at the date of initial application requires undue cost or effort, an entity shall assess the contractual cash flow characteristics of that financial asset based on the facts and circumstances that existed at the initial recognition without taking into account the exception for prepayment features.
Restatement of comparatives is not required but entities are permitted to restate comparatives if they can do so without the use of hindsight. If an entity does not restate comparatives, it should adjust the opening balance of its retained earnings to take account of the effect of applying the new standard in the year of initial application.
IFRS 9 Implementation Challenges
22 October 2014

5. How well are banks positioned currently
How well are banks positioned currently? IFRS 9 - current status and emerging practice
IASB
EU / EFRAG
Emerging Practice
IASB published IFRS 9 on 24 July 2014
IFRS 9 is mandatory from 1 January 2018
IFRS 9 needs to be applied in entirety, except for the OCI treatment of OCS of financial liabilities in FVO
Early application is allowed (endorsement required in the EU)
Endorsement process not yet started
EFRAG/EU are currently constituting the respective bodies
Endorsement process not expected to start before the end of 2014
Endorsement process of comprehensive standards such as IFRS 9 usually takes 12 months or longer
The level of effort to date has been mixed. Most banks have closely followed the development of IFRS 9
Many banks, particularly in Germany, have already conducted high-level impact assessments on IFRS 9 Classification & Measurement and ECL. Many banks are now starting implementation projects.
Others are adopting a wait-and- see approach.
Having established an effective date for IFRS 9, banks are taking stock on the impact of IFRS 9 and their approach to implementation
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6. Classification and measurement2
IFRS 9 Implementation Challenges
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7. Classification and measurement of financial assets
Overview of three categories
Amortised cost
Hold to collect; and
Solely payments of principal and interest.
Fair value – OCI
Hold to collect and sell; and
Solely payments of principal and interest.
Fair value – P&L
Residual category.
Amortised cost
FV-OCI
FV-PL
The above table compares the key factors that define each category that were covered in the slide before. The objective of the slide is to stress the fact that determining the category for each financial asset requires judgement and in some cases the category may not be clear.
The key issue is to determine the business model properly. A single entity may have more than one business model for managing its financial instruments. For example, an entity may hold a portfolio of investments that it manages in order to collect contractual cash flows and another portfolio of investments that it manages in order to trade to realise fair value changes. Similarly, in some circumstances, it may be appropriate to split a portfolio of financial assets into sub-portfolios to reflect how an entity manages those financial assets. For example, that may be the case if an entity originates or purchases a portfolio of mortgage loans and manages some of the loans with an objective of collecting contractual cash flows and manages the other loans with an objective of selling them.
It is important to understand which factors to consider when assessing the business model in order to understand at which level this assessment should be made and understand the differences between categories. More information is provided on the next slide.
Key question is where these lines are drawn.
IFRS 9 Implementation Challenges
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8. Why is classification & measurement important to Expected Credit Loss determination?
Classification under IFRS 9 for investments in debt instruments is driven by the entity’s business model for managing financial assets and their contractual cash flow characteristics.
A financial asset is measured at amortised cost if both of the following criteria are met:
The asset is held to collect its contractual cash flows; and
The asset’s contractual cash flows represent ‘solely payments of principal and interest’ (‘SPPI’)
Key issues impacting on ECL:
Reclassifications of assets and/or portfolios are highly likely to occur, as the criterial for classification & measurement are very different.
A single entity can have more than one business model for managing similar financial instruments.
For example, an entity can hold one portfolio of mortgages in order to collect contractual cash flows and another portfolio of mortgages (with similar characteristics) that it manages in order to sell/or to realise fair value changes.
Classification changes, especially from AC to FVOCI or FVTPL will directly impact on the determination ECL and thus impact regulatory capital.
IFRS 9 Implementation Challenges
22 October 2014

9. Key challenges for IFRS 9 implementation
Mitigation
C&M Considerations
Business model
Definition of BM by senior management
Selling decisions with impact on accounting
Processes and systems required to document BM and reasons for sales
Use of existing BM documentation and portfolio structures as starting point
Informing SM about requirements and strategic options (e.g. on transition date)
Contractual cash flows
SPPI assessment at instrument level
Required information not available
Business units to be included
Improvement /implementation of systems
Clustering & use of efficient questionnaires
Training of business units
Fair value measurement
High quality FV needed for (structured) loans
FV needed for modified loans
May result in P&L and Equity volatility
Implementation of FV models for loans
Improvement of existing IT systems
Transitional impacts
Availability of data on transition
Determining opening position impacts
FV may be needed for loans currently at amortised cost
Identify data gaps and capacity of existing IT systems
Deploy simulation tools to identify and quantify impacts
Develop, build and test FV models for loans
Disclosures
Reconciliation between IAS 39 measurement and new measurement categories under IFRS 9.
Additional qualitative and quantitative information is required to be disclosed.
Need to communicate clearly to investor base.
Mock up of disclosures
Regular contact with regulators and investors
Potential for national disclosures and / or guidelines
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10. Overview of Expected credit losses in IFRS 93
IFRS 9 Implementation Challenges
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11. IFRS 9 Expected credit loss model
Scope
Financial assets at amortised cost
Financial assets (debt instruments) at FVOCI
Loan commitments
Financial guarantee contracts
Lease receivables and trade receivables or contract assets
Modified financial assets
Overview
IFRS Expected loss model not same as Regulatory EL model (i.e. not TTC).
Responsive to changes in information that impact credit expectations.
It is inappropriate to recognise full lifetime expected credit losses on initial recognition of financial instruments, except for the simplified approach for trade and lease receivables.
Significant increase in credit risk leads to recognition of lifetime losses.
IFRS 9 EL model is data intensive.
Convergence between US GAAP and IFRS has not been achieved.
Financial assets that are subject to ECL calculations are:
Financial assets that are measured at amortised cost in accordance with IFRS 9 Financial Instruments;
Financial assets that are mandatorily measured at fair value through other comprehensive income (FVOCI);
All loan commitments (except those measured at FVPL or that constitute derivative financial instruments in accordance with IFRS 9);
Financial guarantee contracts to which IFRS 9 is applied and that are not accounted for at fair value through profit or loss; and
Lease receivables that are within the scope of IAS 17 Leases and trade receivables or contract assets within the scope of IFRS 15 that give rise to an unconditional right to consideration.
Note: The standard has removed the distinction that existed between loan commitments in the scope of IFRS 9 and those in the scope of IAS 37. An issuer of loan commitments should apply the impairment requirements of IFRS 9 to loan commitments that are not otherwise within the scope of the standard.
IFRS 9 Implementation Challenges
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12. Expected credit losses General model
Change in credit quality since initial recognition
Recognition of expected credit losses
12 month expected credit losses
Lifetime expected credit losses
Lifetime expected credit losses
Interest revenue
Effective interest on gross carrying amount
Effective interest on gross carrying amount
Effective interest on amortised cost carrying amount (i.e. net of credit allowance)
Stage 1
Stage 2
Stage 3
The slides illustrates the key provisions of the model.
There are three stages in the Standard to reflect the general pattern of credit deterioration of a financial instrument. The differences in accounting relate to the recognition of expected credit losses and, for financial assets, the calculation and presentation of interest revenue.
Stage 1: includes financial instruments that have not had a significant increase in credit risk since initial recognition or that have low credit risk at the reporting date. For these assets, 12-month expected credit losses (‘ECL’) are recognised and interest revenue is calculated on the gross carrying amount of the asset (that is, without deduction for credit allowance). 12-month ECL are the expected credit losses that result from default events that are possible within 12 months after the reporting date. It is not the expected cash shortfalls over the 12-month period but the entire credit loss on an asset weighted by the probability that the loss will occur in the next 12 months.
Stage 2: includes financial instruments that have had a significant increase in credit risk since initial recognition (unless they have low credit risk at the reporting date) but that do not have objective evidence of impairment. For these assets, lifetime ECL are recognised, but interest revenue is still calculated on the gross carrying amount of the asset. Lifetime ECL are the expected credit losses that result from all possible default events over the expected life of the financial instrument. Expected credit losses are the weighted average credit losses with the probability of default (‘PD’) as the weight.
Stage 3: 3 includes financial assets that have objective evidence of impairment at the reporting date. For these assets, lifetime ECL are recognised and interest revenue is calculated on the net carrying amount (that is, net of credit allowance).
Financial assets that meet the definition of purchased or originated credit impaired assets are covered on the following slides.
12- month expected credit losses and lifetime expected credit losses are defined on the next slide.
An entity would generally present and calculate interest revenue using the effective interest method on the gross carrying amount. However, the way in which that interest revenue is calculated and presented changes if objective evidence of impairment (Stage 3). An entity would then present and calculate interest revenue using the effective interest method on the net carrying amount (i.e. the gross carrying amount less allowance for the ECL).
*CLICK*
This analysis can be done on an individual or portfolio basis. Financial assets should bear similar risks in order to group them in a portfolio. Examples of financial assets that would bear similar risks would be:
(a) instrument type;
(b) credit risk ratings;
(c) collateral type;
(d) date of origination;
(e) remaining term to maturity;
(f) industry;
(g) geographical location of the borrower; and
(h) the value of collateral relative to the commitment if it has an impact on the probability of a default occurring (for example, non-recourse loans in some jurisdictions or loan-to-value ratios).
Performing
(Initial recognition*)
Underperforming
(Assets with significant increase in credit risk since initial recognition*)
Non-performing
(Credit impaired assets)
*Except for purchased or originated credit impaired assets
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13. Expected credit losses General model
Definitions
12-month expected credit losses
Are a portion of the lifetime expected credit losses and represent the amount of expected credit losses that result from default events that are possible within 12 months after the reporting date.
Lifetime expected credit losses
The expected credit losses that result from all possible default events over the life of the financial instrument.
Credit loss
The difference between all principal and interest cash flows that are due to an entity in accordance with the contract and all the cash flows the entity expects to receive discounted at the original EIR.
Expected credit losses
The weighted average of credit losses.
The above terminology is used on the previous slide and is referred to throughout this presentation. The definitions are set out in Appendix A of the Standard.
12-month ECL are a portion of the lifetime expected credit losses and represent the amount of expected credit losses that would result from a default in the 12 months after the reporting date. The losses are therefore not:
Lifetime ECL that an entity will incur on financial instruments that it predicts will default in the next 12 months; or
The cash shortfalls that are predicted over the next 12 months.
At each reporting period the entity would re-measure the 12-month ECL for financial instruments that have not had a significant increase in credit risk since initial recognition, to reflect the entity’s current expectations about expected credit losses.
The difference between all contractual cash flows that are due to an entity in accordance with the contract and all the cash flows that the entity expects to receive (i.e. all cash shortfalls), discounted at the original effective interest rate (or credit-adjusted effective interest rate for purchased or originated credit-impaired financial assets). An entity shall estimate cash flows by considering all contractual terms of the financial instrument (for example, prepayment, extension, call and similar options) through the expected life of that financial instrument. The cash flows that are considered shall include cash flows from the sale of collateral held or other credit enhancements that are integral to the contractual terms. There is a presumption that the expected life of a financial instrument can be estimated reliably. However, in those rare cases when it is not possible to reliably estimate the expected life of a financial instrument, the entity shall use the remaining contractual term of the financial instrument.
ECL are the weighted average of credit losses with the respective risks of a default occurring as the weights
IFRS 9 Implementation Challenges
22 October 2014

14. Expected credit losses General model
Expected credit losses Financial assets ECL represent a probability-weighted estimate of the difference over the remaining life of the financial instrument, between: Undrawn loan commitments
Present value of cash flows according to contract
Present value of cash flows the entity expects to receive 
Expected credit losses are the weighted average of credit losses over the remaining life of the financial instrument.
For financial assets, a credit loss is the present value of the difference between:
the contractual cash flows that are due to an entity under the contract; and
the cash flows that the entity expects to receive.
For undrawn loan commitments, a credit loss is the present value of the difference between:
the contractual cash flows that are due to the entity if the holder of the loan commitment draws down the loan; and
the cash flows that the entity expects to receive if the loan is drawn down.
An entity’s estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, i.e. it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.
Present value of cash flows if holder draws down
Present value of cash flows the entity expects to receive if drawn down 
IFRS 9 Implementation Challenges
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15. Expected credit losses General model
Assessment of a significant increase in credit risk
Absolute probabilities are not sufficient
Variation between reporting date and initial recognition
12 months unless lifetime assessment is necessary
Probability of Default
(‘PD’)
When assessing whether the credit risk on a financial instrument has increased significantly since initial recognition, an entity shall use the change in the risk of default occurring on the financial instrument rather than the change in the expected credit losses or in loss given default (‘LGD’). To make that assessment, an entity shall compare the risk of a default occurring over the remaining life of the financial instrument as at the reporting date with the risk of a default occurring on the financial instrument over its remaining life as at initial recognition.
If an entity choses to make the assessment by using probability of default (‘PD’) information, generally a lifetime probability of a default (over the remaining life of the instrument) would be used. But, as a practical expedient, a 12-month probability of a default can be used if it is not expected to give a different result to using lifetime PD.
A simple or absolute comparison of probabilities of a default at initial recognition and at the reporting date is not appropriate. All other things staying constant, the probability of a default of a financial instrument should reduce with the passage of time. So, an entity needs to consider the relative maturities of a financial instrument at inception and at the reporting date when comparing probabilities of a default.
Example of ways in which the assessment of significant increases in credit risk could be implemented more simply, include:
Establishing the initial maximum credit risk for a particular portfolio (by product type and/or region)(the ‘origination credit risk’) and comparing that to the credit risk at the reporting date. This would only be possible for portfolios of financial instruments with similar credit risk on initial recognition;
Assessing increases in credit risk through a counterparty assessment as long as such assessment achieves the objectives of the proposed model;
An actual or expected significant change in the financial instrument’s external credit rating.
Paragraph [B5.5.17] of the Standard provides more examples.
Generally a financial instrument would have a significant increase in credit risk before there is objective evidence of impairment or before a default occurs.
Lifetime ECL are expected to be recognised before a financial statement becomes delinquent. If forward-looking information is reasonably available, an entity cannot rely solely on delinquency information when determining whether credit risk has increased significantly since initial recognition. An entity also needs to consider forward-looking information on a portfolio level that is indicative of significant increases in credit risk.
Maximum credit risk for a portfolio
Counterparty assessment
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16. Expected credit losses General model
An entity’s estimate of expected credit losses must reflect:
the best available information.
an unbiased and probability-weighted estimate of cash flows associated with a range of possible outcomes (including at least the possibility that a credit loss occurs and the possibility that no credit loss occurs).
the time value of money.
Various approaches can be used.
An entity should apply a default definition that is consistent with internal credit risk management purposes and take into account qualitative indicators of default when appropriate.
90 days past due rebuttable presumption
When estimating expected credit loss an entity shall consider information that is reasonably available, including information about past events, current conditions and reasonable and supportable forecasts of future events and economic conditions. The degree of judgement that is required for the estimate depends on the availability of detailed information.
For periods beyond ‘reasonable and supportable forecasts’ an entity should consider how best to reflect its expectations by considering information at the reporting date about the current conditions, as well as forecasts of future events and economic conditions.
As the forecast horizon increases, the availability of detailed information decreases and the degree of judgement to estimate ECL increases. The estimate of ECL does not require a detailed estimate for periods that are far in the future – for such periods, an entity may extrapolate projections from available, detailed information.
How to extrapolate projections is a key area of judgment. There is no guidance in the Standard on how to perform this assessment.
The Standard requires the estimate of expected credit losses to reflect an unbiased and probability-weighted amount that is determined by evaluating a range of possible outcomes. In practice, this may not need to be a complex analysis. In some cases, relatively simple modelling may be sufficient, without the need for a large number of detailed simulations of scenarios. For example, the average credit losses of a large group of financial instruments with shared risk characteristics may be a reasonable estimate of the probability-weighted amount. In other situations, the identification of scenarios that specify the amount and timing of the cash flows for particular outcomes and the estimated probability of those outcomes are likely to be needed. In those situations, the expected credit losses shall reflect at least two outcomes.
Expected credit losses shall be discounted to the reporting date. The appropriate discount rate will be covered on the following slides.
An entity should apply a default definition that is consistent with internal credit risk management purposes and take into account qualitative indicators of default when appropriate.
There is a rebuttable presumption that default does not occur later than 90 days past due unless an entity has reasonable and supportable information to support a more lagging default definition.
However…
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17. Expected credit losses General model
Information to take into account for assessment of increased credit risk
Changes in external market indicators
Changes in business
Other qualitative inputs
Changes in internal price indicators
Changes in credit ratings
Changes in operating results
30 days past due rebuttable presumption
Credit risk analysis is a multifactor and holistic analysis, whether a specific factor is relevant and its weight compared to other factors will depend on the type of product, characteristics of the financial instrument and borrower as well as the geographic region. We have included in the Slide some of the factors that could be taken into account, additional examples are included in paragraph [B5.5.17] of the Standard.
This information may include:
Changes in external market indicators of credit risk (e.g. the credit spread, the credit default swap prices for the borrower etc);
Changes in credit ratings (external or internal);
Changes in internal price indicators of credit risk (e.g. credit spread);
Existing or forecast changes in the business, financial or economic conditions that are expected to cause a significant change in the borrower’s ability to meet its debt obligations (such as actual or expected increase in interest rates or unemployment rates);
Changes in operating results of the borrower (e.g. actual or expected decline in revenues or margins, increasing operating risks, working capital deficiencies etc); and
Other qualitative inputs.
However, if information (either on an individual or portfolio level) that is more forward-looking than past due status is not available for particular groups of financial assets (i.e. particular products, regions or borrower-types), there is a rebuttable presumption that credit risk has increased significantly since initial recognition no later than when contractual payments are more than 30 days past due.
However….
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18. Expected credit losses General model
Regulatory PD vs IFRS 9 PD
Regulatory PD
IFRS 9 PD
Through the cycle
(‘TTC’)
Hard to reconcile both!
Point in time
(‘PiT’)
The standard allows entities to make the assessment of changes in credit risk by using a 12-month PD where it would not be expected to give a different result to using lifetime PDs. This does not mean that the 12-month PD used for regulatory purposes can be used without adjustment.
Twelve-month expected credit losses used for regulatory purposes are often based on ‘through the cycle’ (‘TTC’) probabilities of a default (that is, probability of default in cycle-neutral economic conditions) and can include an adjustment for prudence.
PD used for IFRS 9 should be ‘point in time’ (’PiT’) probabilities (that is, probability of default in current economic conditions) and do not contain adjustment for prudence.
However, regulatory PDs might be a good starting point, provided they can be reconciled to IFRS 9 PDs. The standard does not provide any guidance on how to adjust TTC PD to PiT PD. The process is complex and will require the use of judgement.
Note: Under IFRS 9, estimates of PD will change as an entity moves through the economic cycle. Under many regulatory models, as PD is calculated through the cycle, estimates are less sensitive to changes in economic conditions. Therefore, regulatory PDs reflect longer-term trends in PD behaviour as opposed to PiT PDs. As a consequence, during a benign credit environment, IFRS 9 PD (PiT) will be lower than regulatory PD (TTC), while the adjustment will be the opposite during a financial crisis.
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19. Expected credit losses General model
Discount rate and operational simplifications
Discount rate for calculating the expected credit losses
Effective interest rate or an approximation thereof.
Operational simplifications
Low credit risk: the loss allowance for financial instruments that are deemed low credit risk at the reporting date would continue to be recognised at 12-month ECL.
Simplified approach for lease and trade receivables
For trade receivables or contract assets that do not contain a significant financing component: Relief from calculating 12-month ECL and to assess when a significant increase in credit risk occurred. Lifetime ECL throughout the trade receivable’s life.
For lease receivables and trade receivables or contract assets that contain a significant financing component: Accounting policy choice to apply simplified approach to measure loss allowance at lifetime ECL on initial recognition.
Expected credit losses shall be discounted to the reporting date, not to the expected default or some other date, using the effective interest rate determined at initial recognition or an approximation thereof.
Operational simplifications – Low credit risk
The Standard includes an operational simplification that may be used for instruments with low credit risk.
A financial instrument is deemed to be low credit risk when:
It has a low risk of default
The borrower is considered, in the near term, to have a strong capacity to meet its obligations; and
The lender expects, in the longer term, that adverse changes in economic and business conditions might, but will not necessarily, reduce the ability of the borrower to fulfil its obligations.
Financial instruments are not required to be externally rated; an entity may use its internal credit ratings, but those should equate to a global credit rating definition of ‘investment grade’.
It is expected that this operational simplification will provide relief to entities especially financial institutions, such as insurers, who hold large portfolios of securities with high credit ratings. This expedient will avoid having to assess whether there are significant increases in credit risk for financial assets with low credit risk.
The low credit risk simplification is not meant to be a bright-line trigger for the recognition of lifetime ECL. Instead, when credit risk is no longer low, management should assess whether there has been a significant increase in credit risk to determine whether lifetime ECL should be recognised. This means that just because an instrument’s credit risk has increased such that it no longer qualifies as low credit risk, it does not automatically mean that it has to be included in Stage 2 Management needs to assess if a significant increase in credit risk has occurred before calculating lifetime ECL for the instrument.
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20. Expected credit losses Disclosures
Quantitative
Qualitative
Reconciliation of opening to closing amounts of loss allowance showing key drivers of change
Write off, recovers and modifications
Reconciliation of opening to closing amounts of gross carrying amounts showing key drivers of change
Gross carrying amounts per credit risk grade
Inputs, assumptions and estimation techniques for estimating ECL
Write off policies, modification policies and collateral
Inputs, assumptions and estimation techniques to determine significant increases in credit risk and default
Inputs, assumptions and techniques to determine credit impaired
The Standard includes robust disclosure requirements. An entity shall disclose information that identifies and explains:
the amounts arising from expected credit losses
the effect of the deterioration and improvement in the credit risk of financial instruments.
To meet these requirements, an entity should disclose:
Reconciliation of the gross carrying amounts and allowance balances;
Disclosures on credit risk grading
Disclosures on techniques, assumptions and policies (e.g. write off policy)
This is a summary of the overall disclosures, nevertheless extensive disclosures are proposed to identify and explain the amounts in the financial statements that arise from expected credit losses and the effect of deterioration and improvement in credit risk. Sufficient information should be provided to allow users to reconcile line items that are presented in the statement of financial position. For disclosure purposes, financial instruments should be grouped into classes that facilitate the understanding for users. Examples of the disclosures that could be provided are included in the Standard.
On the date of initial application of IFRS 9 the entity should disclose a reconciliation of the ending impairment allowances under IAS 39 and IAS 37 to the opening impairment allowances under IFRS 9 by measurement category, showing separately the effect of reclassifications on the allowance balance at that date.
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21. Implementation Challenges4
IFRS 9 Implementation Challenges
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22. Impairment: Implementation challenges
Components
Implementation challenges
Portfolio segmentation
Determine segmentation criteria.
Consider existing models and data availability for various portfolios
Criteria for low credit risk
Transfer criteria
Definition of trigger events
Significant deterioration in credit
Maturity
Contractual term Vs behavioral
Consideration of prepayments and others
Expected loss modeling
Determination of models for 12 month and lifetime expected loss
Discount rate
Forward looking data
Economic overlay
Audit trail
Complexity
Complexity vs senior management understandability vs investor needs
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23. Impairment: Key considerations
Governance
Impairment: Key considerations
Technical analysis and interpretation
Lack of comparability / benchmarks
Modelling assumptions/inputs, validation and outputs
Views of regulators
Controls considerations
Disclosures
Others
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24. Impairment : Models to be developed
Portfolio coverage (by model)
Expected loss – 12 months EL, lifetime EL
Significant deterioration of credit
Important questions
Has the entity appropriately segmented its portfolios?
How is it determined that the various models are appropriate?
How strong is the model governance framework?
Is there a consistent basis for model development, validation and documentation?
Is there an appropriate benchmark?
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25. Impairment : Level of modelling
Basic
Intermediate
Advanced 2 3 1 3
Advanced approach
Robust models to incorporate forecasts of macroeconomic conditions used to adjust loss curves.
Loss curves exist for PD, LGD and EAD and are updated both by internal and external data
Specific issues
Challenging to explain to senior management and investors
Consistence roll out of economic scenarios
Significant overheads 1
Basic approach (?)
A simplified approach to ECL by using management judgment to determine provision rates
Specific issues
How to evaluate that management judgment is accurate and correlated to historical data
Is it acceptable under the standards and with the regulators ? 2
Intermediate approach (?)
Model PD using simple statistical averages.
LGD assumptions are flat
Loss curves are generated using external benchmarks
Economic forecasts included as a management overlay
Specific issues
Substantiate economic overlays
Insufficient details in development of PD
Common issues
Supporting the output of the modelling with data will be challenging for all firms.
The ability to audit the firm’s view of future economic conditions and links to losses
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26. Impairment : Leveraging existing credit infrastructure
Banks will consider leveraging existing infrastructure
Improves efficiency and minimise rework
Align with regulatory model
Leverage internal control framework
Specific issues and audit concerns
Transfer criteria
Significant deterioration
What is considered as significant credit deterioration ?
How can you demonstrate consistency?
What are the controls over application of significant deterioration?
Term structures
Development of lifetime EL, term structure for PD, LGD and correlation
How to model life time PD and LGD leveraging on existing regulatory and credit models?
How to perform back testing with limited availability of data ?
Economic overlays
Consider economic forecasts based on past events, current conditions and reasonable forecasts of future events
How to determine what economic overlays to be applied ?
How do you judge and evidence the “right economic conditions” and forecasts of the future?
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27. Impairment - Leveraging existing Basel methodologies
IFRS 9
Basel III
PD estimated over 12-month horizon for Stage 1; Lifetime loss calculation for Stages 2 and 3
PD estimates are ‘point-in-time’ measures
Definition of default - may adopt regulatory definitions
Considers forward looking estimates at balance sheet date
12-month PD estimation
PD estimates is mostly based on ‘through-the-cycle’ measures
Regulatory overrides
Routine use of stress testing and scenario analysis to calibrate
Probability of
Default ('PD')
IFRS 9
Basel III
Current LGD
Discount rate should be at effective interest rate
Collateral valuation and disclosures for financial instruments with inherent objective evidence of impairment.
Downturn LGD estimates
Consideration of certain costs and LGD floors
Discount rate based upon weighted average cost of capital or risk-free rate
Treatment of collateral is subject to detailed rules, haircuts etc
Default ('LGD')
Loss Given
IFRS 9 Implementation Challenges
22 October 2014

28. Impairment – Data requirements
Identify the new data requirements
Which systems will the data come from - existing finance reporting systems and others?
Data sourcing from different systems may not be subject to same level of controls and governance
Identification of appropriate data from right systems
Key considerations
How has firm developed processes to collate data from the other systems?
Has finance engaged with other business unit to understand the data impact?
Has the firm determined the level of automation required to produce the required disclosures in the financial statements ?
Has the firm considered the controls over systems typically outside the statutory audit ?
How to develop process to maintain and update the newly required qualitative/assumption disclosures ?
How comfortable is the firm with the completeness and accuracy of loan level data?
IFRS 9 Implementation Challenges
22 October 2014

29. Impairment - Control and governance considerations
Business model
Business models reflect the impact of the IFRS 9
ECL models feedback into other strategic processes (e.g. capital management, pricing, stress testing, etc).
Systems
Alignment of risk and finance systems?
Remapping of lines and accounts within the general and sub ledgers
Common chart of accounts and data definitions across all parts of the business.
Data quality
Single data source at required granularity, with full drill down capability and validation of data
Frequent testing and maintenance of new data models
Automation of data controls
Process
Fully defined processes for identifying the provisions and how they relate to the business units, product pricing and strategy.
New credit risk monitoring processes to incorporate system solution to the generation of accounting information.
Controls and Governance
Circulation of management reports in a timely manner
Governance and controls over areas not currently subject to statutory audit (e.g. Risk and regulatory data)
IFRS 9 Implementation Challenges
22 October 2014

30. Conclusions
IFRS 9 Implementation Challenges
22 October 2014

31. Key challenges for IFRS 9 implementation
Mitigation
Overall
Strategic decisions
Quality of implementation
Systems and data landscape
Resources and timing
Materiality
Full transparency of external and internal factors to be able to make the right decisions
Affected functions
IFRS 9 impacts the whole group: Group Finance, Risk, GTO, regional finance, legal entities, business units (CB&S, GTB, PBC, AWM, NCOU), senior management
Early inclusion of all potentially affected functions
Clear responsibilities, communication and understanding of impacts
Interactions with other projects
Technical overlaps (e.g. with FinRep, BCBS239, CRD IV, IT projects)
Potential resource conflicts
Unaligned project time lines
Identification of all technical and content overlaps
Integrated project set up
Early decisions on interdependencies and leverage
Budgeting & timing (target application date)
Communication and presentation of strategy
Project governance
Project set up
Data
Availability and collection of data
Data definitions
Control and assurance environment
Early data gap and quality analysis
Ability to leverage existing data and processes
Capital impacts
IFRS 9 impacts the accounting and regulatory capital
Simulations and strategic policy and business choices
IAS 39 burdens
IFRS 9 phrases certain requirements more clearly than IAS 39 (e.g. modifications)
IFRS 9 implementation could be used to solve issues existing under IAS 39
Identification of requirements and chances to improve accounting
Solving overlaps with other requirements (e.g. forbearance, post AQR topics)
Manage “scope creep”
IFRS 9 Implementation Challenges
22 October 2014

32. Key lessons learned from on-going engagements with our clients
Lessons learned from the implementation projects completed to date:
Simulation of the quantitative impacts is complex but necessary. The data required to run a fully compliant IFRS 9 EL model is considerable. PwC have experience of running our diagnostic Simulation Tool in over 35 banks of different environmental complexity with varying levels of available data.
The transfer between buckets is highly judgmental. Banks need to develop practical policies and guidelines to inform these judgements.
Identification of data gaps is critical. The EL model is data intensive. Early effort is needed to identify data gaps and then consider practical solutions to collect and control the necessary data;
IFRS 9 impacts are pervasive. IFRS 9 impacts on lending, underwriting and pricing, accounting and reporting, capital and return on equity.
Potential to release synergies and efficiencies. It may be possible to leverage existing credit risk methodologies and processes to comply with IFRS 9 requirements without incurring undue cost or effort.
Implementation needs to be controlled. PwC has in-depth IFRS 9 project management experience and skills, including role allocation and issue resolution experience. We can help you ensure implementation is controlled and achieved in an orderly and efficient manner.
IFRS 9 is of strategic importance. The strategic impacts of IFRS 9 can be considerable and therefore it is important to understand the impact on the banks business and plan potential responses.
IFRS 9 Implementation Challenges
22 October 2014

33. Questions?
Questions?
IFRS 9 Implementation Challenges
22 October 2014

34. Thank you for your attention
John Kelly
Senior Manager, Banking & Capital Markets
T: +353 (1) M: +353 (87)
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