IFRS 9 Implementation Methodology Guide - Qtxasset

IFRS 9ImplementationMethodology Guide

Table of ContentsAbout the Author3Rationale for IFRS 94IFRS 9 Impairment Model5Key Challenges in IFRS 9Implementation6IFRS 9 ImplementationKey Considerations- Modeling- Cash Flow Information- Accounting Integration- Models for Computing ECL- Data Management7Recommended Approach andChecklist for IFRS 9 ProgramRollout9Stakeholder Responsibilities &Timeline for IFRS Implementation11Oracle’s Proven Methodology forIFRS 9 Implementation12Oracle’s Consulting Framework forIFRS 9 Implementation13Oracle’s Solution for IFRS 91378888

About the AuthorRajesh VarahanSenior DirectorMiddle East & Africa,Professional Services,Oracle FinancialServices Software LtdRajesh Varahan has more than 20 years of experiencein the banking & financial services industry in variouscapacities – P&L management, client engagement,sales management, delivery management, productmanagement, and risk advisory/domain consulting.Rajesh is a certified risk management professionalwith subject matter expertise in treasury &compliance. He also has a deep understanding of thebusiness and operational side of banking, havingsuccessfully led large programs in the risk andcompliance domain for tier 1 banks globally.As Senior Director & Head of Delivery for Middle East& Africa with Oracle Financial Services, Rajesh hasoversight responsibility for all client projects in thatregion that involve Oracle Financial ServicesAnalytical Applications (OFSAA) implementations.Email: rajesh.varahan@oracle.com

Rationale for IFRS 9IFRS 9 introducesa three-stageimpairment modelfor computingexpected creditlosses on loansthat is moreforward lookingin design.One of the key factors that contributed to the financialcrisis of 2008 was the approach taken by banks todetermine losses on bad loans under the extant IAS 39guidelines. The IAS 39 accounting standard’s incurredloss model had several shortcomings, which included: Loan losses were not recognized until there was anobjective evidence of impairment. The delayedrecognition was cited as a major weakness of theimpairment model (too little too late). The incurred loss model exaggerates the pro-cyclicaleffects of banks’ capital regulation, which had thepotential to trigger systemic risk and impact globalfinancial stability. Typically, credit losses tend to be attheir lowest just before the start of an economicdownturn when actual losses begin to emerge andmount. IAS 39 was also criticized for allowing banks to adoptdifferent approaches for impairment computation forsimilar financial instruments, depending on theirclassifications. The incurred loss approach was backward looking innature and did not take into account changes in themacroeconomic environment in computing theeconomic value of loans.Several high profile bodies including the G20, Baseland Bank Supervisors realized the need to plug thegaps in the loan loss provisioning standardsprescribed by IAS 39. They entrusted the IASB to comeup with a revised standard – IFRS 9. The IASB has beenworking since November 2008 on IFRS 9 andstructured the project under three phases:1. Classification and Measurement2. Impairment3. Hedge AccountingIFRS 9 amends the existing guidance on Classification& Measurement by introducing a new category – FairValue through Other Comprehensive Income (FVOCI) –while dropping existing categories – Available for Sale(AFS), Held to Maturity (HTM) and Loans &Receivables.IFRS 9 introduces a three-stage impairment model forcomputing expected credit losses on loans that ismore forward looking in design. It requires banks toset aside provisions for expected credit losses on theorigination of the loan (a loss is factored in on day 1).The standard also has a new guidance for hedgeaccounting, which will be effective starting January2018, subject to its adoption by the respectivecountries.

IFRS 9 Impairment ModelImpairment requirements under IFRS 9 are applicable to debt instruments and loan commitments that are notmeasured at fair value through profit and loss, financial guarantees, lease receivables and contract assets.Equity investments are not within the scope of impairment computation as they are measured at fair value.Under IFRS 9, banks have to classify all financial instruments in scope for impairment computation into threebuckets – Stage 1, 2 or 3 – depending on the change in credit quality since initial recognition.Stage 1 includes accounts where there is no significant increase in credit risk since initial recognition oraccounts that have low credit risk on reporting date. For accounts in Stage 1, interest is accrued on the grosscarrying amount of the instrument and a 12-month expected credit loss (ECL) is factored into profit and loss(P&L) calculations.Stage 2 comprises accounts with a significant increase in credit risk since initial recognition but which have noobjective evidence of impairment to date. Interest for accounts in Stage 2 is accrued on the gross carryingamount, however, a lifetime ECL is factored into profit & loss calculations.Stage 3 includes accounts that demonstrate evidence of impairment on the reporting date and for such assets,interest is accrued on the net carrying amount (net of provisions) and a lifetime ECL is factored into profit &loss calculations.Change in credit risk since initial recognitionSTAGE 1STAGE 2STAGE 3Impairment Recognition12-monthExpected credit lossesLifetimeExpected credit lossesLifetimeExpected credit lossesWhen significant increase in risk occursInterest RevenueGross Basis:‘Performing’Figure 1: IFRS 9 Impairment Stages?Gross Basis:‘Under-performing’XNet Basis:‘Non-performing’

Key Challenges in IFRS 9 ImplementationIFRS 9 has been in the making for a while, and with the publication of the final guidance in July 2014,regulators, executive management at banks, and investors have been taking a close look at its potentialramifications. The regulation goes beyond mere computation of expected losses or provisions and addressesa much broader gamut of issues needing board and executive management consideration.One direct financial consequence of the regulation for banks is lower operating margin and profitability,stemming from higher provisioning required, as well as impact on a bank’s capital, liquidity and leverage.Banks face pressure on net interest margins on a risk adjusted basis. Given the competitive landscape, theymay not be able to pass on the higher costs of provisioning to customers, thereby taking a hit to their bottomlines. There will also be additional capital requirements that banks will be required to maintain due to the newstandard’s impairment provisioning guidelines, dealing banks with a double whammy in the form of decliningmargins along with a higher capital outlay required to support and grow the business.Expected credit loss (ECL) numbersfrom IFRS 9’s three-stage approachfall in between the IAS 39 incurredloss approach and fair valueaccounting. IFRS 9 tries to capture thechanges in the economic value of aloan by discounting the expected cashflows at the effective interest rate.However, it does not capture thechanges in the interest rate post theloan origination.At the time of origination, IFRS 9overstates the loan loss allowance (asa day 1 loss) and as the credit riskdeteriorates, it understates the lossallowance. However, there is a jumpin loss allowances when the accountmoves from stage 1 to stage 2, due toa significant deterioration in its creditrisk, which is a real concern for banksas this will require additionalprovisioning. This in turn will dentprofitability and the bank’s ability topay dividends.Loss allowance(% of gross carrying amount)Stage 1Stage 2Stage 3SignificantdeteriorationIAS 39 recognition pointof incurred lossesDeterioration in credit qualityfrom initial recognitionEconomic expected credit losses (2009 ED)IFRS 9Figure 2: IFRS 9 loan loss allowances versus IAS 39 incurredloss approachAnother key challenge that banks will have to contend with is the incorporation of forward-lookingmacroeconomic data like GDP, unemployment rate, housing price index, interest rate, inflation, andtechnology. These require banks to build models that take into account idiosyncratic and systemic factors.Banks will need to consider current modeling capabilities, systems and processes in place as well as theavailability of timely data pertaining to macroeconomic indicators.Last but not least, banks will need to put in place an appropriate data governance program to source for theright data that IFRS 9 requires. IFRS 9 expects banking institutions to consider historical, current and forwardlooking forecasts in their ECL computations. Banks will be required to aggregate data owned by risk, financeand treasury functions that are of the right level of granularity and quality so as to make them available forECL processing.

Consequent to the implementation of theBCBS 239 regulation on risk dataaggregation, most banks have establisheda decent data governance programs tosupport risk data reporting at the enterpriselevel. Banks can leverage these existinginvestments in data infrastructure for BCBS239, however, they still need to address theadditional data requirements for IFRS 9outlined in Figure 3. As the deadline forbecoming compliant draws closer, thereare a number of prerequisites that banksshould be paying close attention to, to helpfacilitate a smooth transition to IFRS 9.IFRS 9 ImplementationKey ConsiderationsModelingFigure 3: IFRS 9 Data RequirementsBanks need to build and calibrate models for probability of default (PD), loss given default (LGD) and exposureat default (EAD) for ECL computations. Given the objectives of IFRS 9 accounting vis-à-vis regulatory capitalmanagement (under Basel guidelines), PD, LGD and EAD models used for capital computations can only beused for IFRS 9 ECL computations after incorporating germane adjustments.Key differences between Basel and IFRS modeling related requirements:BASELIFRS 9 90 days past due on a credit obligationand or Borrower unlikely to pay without thebank turning to recourses such as sellingcollateral No formal definition of default, however, banks areexpected to define default in line with existent creditrisk management practices, incorporating qualitativeindicators like breach of covenants. Rebuttable presumption that default does not occurlater than 90 days past due, unless there is reasonableand supportable information to demonstrate that amore lagging indicator is appropriate Long run historical average over aneconomic cycle – TTC 12-month PD estimation for stage 1 andlifetime PD for stages 2 and 3 Considers forward looking information(macroeconomic overlay) on reporting date Regulatory floors Point in time (PIT) estimates reflecting entity’sassessment of current and future economic cycles,covering the life of loan 12-month PD Periodic use of stress testing to recalibrate themodels No prescribed floorsLGD Downturn LGD, reflecting periods of highcredit losses Recoveries discounted using bankweighted average cost of capital Regulatory floors Considers current and future economic cyclescovering the life of loan Cash flows discounted using EIR No prescribed floorsECL PD x LGD x EAD PD x PV of cash shortfalls. For Stage 1 accounts,12-month PD is used and for Stage 2 and 3,life-time PD is usedDefinitionof defaultPDTerminology: EAD – Exposure at default EIR – Effective interest rate LGD – Loss given defaultPD – Probability of default PV – Present value TTC – Through-the-cycle