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www. pwc. ie/banking IFRS 9 Implementation Challenges 22 October 2014

Agenda 1. Background to IFRS 9: The project and timetable for implementation 2. Classification and measurement 3. Overview of Expected credit losses in IFRS 9 4. Implementation Challenges 5. Conclusions IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 2

Background to IFRS 9: The project and timetable for implementation 1 IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 3

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. IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 4

How well are banks positioned currently? IFRS 9 - current status and emerging practice IASB EU / EFRAG • IASB published IFRS 9 on 24 July 2014 • Endorsement process not yet started • IFRS 9 is mandatory from 1 January 2018 • EFRAG/EU are currently constituting the respective bodies • IFRS 9 needs to be applied in entirety, except for the OCI treatment of OCS of financial liabilities in FVO • Endorsement process not expected to start before the end of 2014 • Early application is allowed (endorsement required in the EU) • Endorsement process of comprehensive standards such as IFRS 9 usually takes 12 months or longer Emerging Practice • 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-andsee approach. Having established an effective date for IFRS 9, banks are taking stock on the impact of IFRS 9 and their approach to implementation IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 5

Classification and measurement 2 IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 6

Classification and measurement of financial assets Overview of three categories Amortised cost Fair value – OCI Fair value – P&L • Hold to collect; and • • • Solely payments of principal and interest. Hold to collect and sell; and • Solely payments of principal and interest. Amortised cost FV-OCI Residual category. FV-PL Key question is where these lines are drawn. IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 7

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: Ø The asset is held to collect its contractual cash flows; and Ø 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 Pw. C 22 October 2014 Slide 8

Key challenges for IFRS 9 implementation Challenges • 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) • 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 • 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 • Mock up of disclosures new measurement categories under IFRS 9. • Regular contact with regulators and investors • Additional qualitative and quantitative • Potential for national disclosures and / or information is required to be disclosed. guidelines • Need to communicate clearly to investor base. Business model C&M Considerations Mitigation Contractual cash flows Fair value measurement IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 9

Overview of Expected credit losses in IFRS 9 3 IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 10

IFRS 9 Expected credit loss model Scope Overview • Financial assets at amortised cost • IFRS Expected loss model not same as Regulatory EL model (i. e. not TTC). • Financial assets (debt instruments) at FVOCI • Loan commitments • Financial guarantee contracts • Lease receivables and trade receivables or contract assets • Modified financial assets • 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. IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 11

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 Effective interest on gross carrying amount Effective interest on amortised cost carrying amount (i. e. net of credit allowance) Interest revenue Effective interest on gross carrying amount Stage 1 Performing (Initial recognition*) Stage 2 Underperforming (Assets with significant increase in credit risk since initial recognition*) Stage 3 Non-performing (Credit impaired assets) *Except for purchased or originated credit impaired assets IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 12

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. IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 13

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: Present value of cash flows according to contract Present value of cash flows the entity expects to receive Undrawn loan commitments ECL represent a probability-weighted estimate of the difference over the remaining life of the financial instrument, between: Present value of cash flows if holder draws down IFRS 9 Implementation Challenges Pw. C Present value of cash flows the entity expects to receive if drawn down 22 October 2014 Slide 14

Expected credit losses General model Assessment of a significant increase in credit risk Variation between reporting date and initial recognition Maximum credit risk for a portfolio IFRS 9 Implementation Challenges Pw. C Absolute probabilities are not sufficient 12 months unless lifetime assessment is necessary Probability of Default (‘PD’) Counterparty assessment 22 October 2014 Slide 15

Expected credit losses General model Expected credit losses • 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 However… IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 16

Expected credit losses General model Information to take into account for assessment of increased credit risk Changes in external market indicators Changes in business Changes in internal price indicators Changes in credit ratings Other qualitative inputs Changes in operating results 30 days past due rebuttable presumption However…. IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 17

Expected credit losses General model Regulatory PD vs IFRS 9 PD Regulatory PD Through the cycle (‘TTC’) IFRS 9 Implementation Challenges Pw. C Hard to reconcile both! Point in time (‘Pi. T’) 22 October 2014 Slide 18

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. IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 19

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 Inputs, assumptions and estimation techniques for estimating ECL Write off policies, modification policies and collateral 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 to determine significant increases in credit risk and default Inputs, assumptions and techniques to determine credit impaired IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 20

Implementation Challenges 4 IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 21

Impairment: Implementation challenges Components Portfolio segmentation Transfer criteria Maturity Expected loss modeling Forward looking data Implementation challenges • Determine segmentation criteria. • Consider existing models and data availability for various portfolios • Criteria for low credit risk • Definition of trigger events • Significant deterioration in credit • Contractual term Vs behavioral • Consideration of prepayments and others • Determination of models for 12 month and lifetime expected loss • Discount rate • Economic overlay IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 22

Impairment: Key considerations Governance Technical analysis and interpretation Lack of comparability / benchmarks Modelling assumptions/inputs, validation and outputs Views of regulators Disclosures Others Controls considerations IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 23

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? IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 24

Impairment : Level of modelling 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 2 1 Specific issues Intermediate • Challenging to explain to senior management and investors • Consistence roll out of economic scenarios • Significant overheads Basic 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 ? IFRS 9 Implementation Challenges Pw. C 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 22 October 2014 Slide 25

Impairment : Leveraging existing credit infrastructure Banks will consider leveraging existing infrastructure - Improves efficiency and minimise rework - Align with regulatory model - Leverage internal control framework Transfer criteria • Significant deterioration Specific issues and audit concerns • 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 Economic overlays • Consider economic forecasts based on past events, current conditions and reasonable forecasts of future events IFRS 9 Implementation Challenges Pw. C • 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 ? • How to determine what economic overlays to be applied ? • How do you judge and evidence the “right economic conditions” and forecasts of the future? 22 October 2014 Slide 26

Default ('PD') Default ('LGD') Loss Given Probability of 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-thecycle’ measures • Regulatory overrides • Routine use of stress testing and scenario analysis to calibrate 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 IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 27

Impairment – Data requirements Key considerations • Identify the new data requirements How has firm developed processes to collate data from the other systems? • Which systems will the data come from - existing finance reporting systems and others? Has finance engaged with other business unit to understand the data impact? • • Data sourcing from different systems may not be subject to same level of controls and governance Identification of appropriate data from right systems 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 Pw. C 22 October 2014 Slide 28

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 Pw. C 22 October 2014 Slide 29

Conclusions IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 30

Key challenges for IFRS 9 implementation • Quality of implementation • Systems and data landscape • Resources and timing • Materiality • IFRS 9 impacts the whole group: Group Finance, Risk, GTO, regional finance, legal entities, business units (CB&S, GTB, PBC, AWM, NCOU), senior management • Full transparency of external and internal factors to be able to make the right decisions • Technical overlaps (e. g. with Fin. Rep, BCBS 239, 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 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 • 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” Affected functions Interactions with other projects IAS 39 burdens IFRS 9 Implementation Challenges Pw. C • Early inclusion of all potentially affected functions • Clear responsibilities, communication and understanding of impacts • Project governance • Budgeting & timing (target application date) • Communication and presentation of strategy Strategic decisions Overall Mitigation Project set up Challenges 22 October 2014 Slide 31

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. Pw. C 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. Pw. C 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 Pw. C 22 October 2014 Slide 32

Questions? IFRS 9 Implementation Challenges Pw. C 22 October 2014 Slide 33

Thank you for your attention John Kelly Senior Manager, Banking & Capital Markets T: +353 (1) 792 8903 M: +353 (87) 244 0162 john. j. kelly@ie. pwc. com This publication has been prepared for general guidance on matters of interest only, and does not constitute professional advice. You should not act upon the information contained in this publication without obtaining specific professional advice. No representation or warranty (express or implied) is given as to the accuracy or completeness of the information contained in this publication, and, to the extent permitted by law, Pw. C does not accept or assume any liability, responsibility or duty of care for any consequences of you or anyone else acting, or refraining to act, in reliance on the information contained in this publication or for any decision based on it. © 2014 Pw. C. All rights reserved. Pw. C refers to the Pw. C network and/or one or more of its member firms, each of which is a separate legal entity. Please see www. pwc. com/structure for further details.