ifrs 9 seminar deloitte

8/19/2019 IFRS 9 Seminar Deloitte

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1© 2014 Deloitte Belgium

IFRS 9: FinancialInstruments

November 2014

Overview of the new requirements


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Fourth Global IFRS Banking Survey


The survey includes the views of 54banks from Europe, the Middle East & Africa, Asia Pacific and the Americas.

We received responses from 14 of the29 global systemically importantfinancial institutions (G-SIFIs) and 25 of

the top 50 global banking groupsmeasured by total assets listed in theBanker Top 1000 World Banks 2013.

Key survey findings About the survey

Some key findings as a starter


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How much time do you require to implement the standard?

© 2014 Deloitte Belgium 3



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Assuming today’s credit environment were to apply, how is your bank’s total

impairment provision likely to change on transition to IFRS 9?


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Overview


The IASB has issued the final version of IFRS 9 Financial Instruments

on 24 July 2014 – Mandatory retrospective application 2018

Classification and Measurement

Impairment

General Hedge Accounting

Macro Hedge Accounting Separate project


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Overview


Changes compared to IAS 39?

Scope None

Recognition & derecognition None

Classifi cation andmeasurement of financialassets

New model regarding the classification and measurement based on :• The entity’s business model (portfolio perspective) and• The contractual cash flow characteristics (CCC criterion) of the individual

financial asset

Classification and measurementof financial liabilities

• No amendments regarding classification• New requirements for the accounting of changes in the fair value of an

entity’s own debt where the FVO has been applied („own credit issue“)

Embedded derivatives

Bifurcation of embedded derivatives needs to be assessed for hybrid contractscontaining a host that is a financial liability or a host that is not an asset within thescope of IFRS 9 (hybrid contracts with a financial asset as a host contract areclassified in their entirety based on the CCC criterion)

Amortised cost measurement None

Impairment Change to expected loss model

Hedge Account ing (HA)

• New model more closely aligns HA with risk management activities• Accounting policy choice to apply the hedge accounting model in

IAS 39 in its entirety or the accounting for portfolio fair value hedges underIAS 39 if applying IFRS 9 hedge accounting

• Separate active project on accounting for macro hedging activities (currentlynot part of IFRS 9)

Major changes introduced by IFRS 9


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Classification and

Measurement ofFinancial Assets

© 2014 Deloitte Belgium


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Classification of financial assets


Contractual Cash Flow Characteristics

PrincipalInterest on the principal

amount outstanding

Business Model

Held to collect contractual cash flows

Held to collect contractual cash flowsand for sale

Timevalue ofmoney

Creditrisk

Other basiclending risks or

costs

Fair Value( OCI)

AmortisedCost

Fair Value

( P&L)

Effectiveinterest method

Impairment

Foreignexchange

gains/losses

(other)

Fair valuechanges

=

Fair valuechanges

Fair value

changes

Fair Value Optionin case of an accounting

mismatch

FVTOCI-Optionfor investments in equityinstruments that are not

held for trading

P&L OCI


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Management ofgroups offinancial assetsto achieve a

particularbusinessmodel

Business model


Business model is determined by the entity‘skey management personnel (as defined in IAS 24)

Evaluation of performance of thebusiness model and internal reporting

Risk that affect the performance of the

business model and management ofthose risks

How managers are compensated (e.g.based on fair value)

Businessmodel

assessmentaccording toIFRS 9

A business model can typically be observed throughthe activities that an entity undertakes to achieve its

business objective, e.g.


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Consequences of inconsistent sales:

Business model fornew financialinstruments mayhave changed

No reclassification without a change inbusiness model of the existing financial assetsNo error according to IAS 8

Business model “Held to collect”


Objective of the business model is

to hold assets in order to col lect contractualcash flows

Sales are not an integral part of the AC business model but maybe consistent with it if:

Insignificant even iffrequent

Infrequent even ifsignificant in value

Close to maturity Due to an increasein credit risk

(or other reason consistentwith the business model)

Regardless of whether caused internally or externally


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Both collecting contractual

cash flows and selling financialassets are integral toachieving the objective of thebusiness model

Consideration of frequency,value and reason of sales not

necessary

Typically involves greaterfrequency and value of salescompared to a „Held to collect“business model

Business model “Held to collect and sell”


Objective is achieved by both collectingcontractual cash flows and sellingfinancial assets

Exampleliquidity portfolio

Frequent sales to actively

manage the return on theportfolio which consists ofcollecting contractual payments

as well as gains and lossesfrom sales


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Contractual cash flow characteristics



amount outstanding

Time valueof money

Credit riskOther basic lending

risks or costs

Fair Value atinitial

recognition

Considerationfor the

passage oftime

For example

• Liquidity risk

• Adminis trativecosts

• Profit margin

• Etc.


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Modified time value of money element


Financialassetwith

modification

Benchmarkinstrumentwithout

modification

Comparison of the contractual cash flowsregarding the modified time value of money

element (cumulative and periodic)

Significantlydifferent

Significantlydifferent

CCC criterion fulfilled?

6M Euribor,reset

monthly1M Euribor,reset

monthly


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Interest rates set by regulatory authorities

© 2014 Deloitte Belgkum 14

Financing

Loan

Regulatoryauthority/government

sets interest rates


amount outstanding

Timevalue ofmoney

Creditrisk


costs

Acceptable proxy for the timevalue of money element if it its

broadly consistent with thepassage of time


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Extension option

Resultingcontractual cashflows:

Prepaymentoption

Prepayment and extension options


Date ofagreement

Latesttermination

Contractual cash flows are solely:• Payments of principal

• Interest on the principal amountoutstanding

• Reasonable additionalcompensation for early termination

Financial asset is acquired ororiginated at a premium ordiscount

Additional criterion:

Fair value of the prepaymentfeature on initial recognition is

insignificant

No distinctionbetween

contingent andnon-contingent

options (likeunder ‘old’

IFRS 9)


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Not genuine

Characteristic affects thecontractual cash flows only on theoccurrence of an event that is extremely

rare, highly abnormal and very unlikelyto occur

De minimis

Characteristic has only ‘de minimis’effect on the contractual cash flows

De Minimis and Not Genuine Characteristics


PrincipalInterest on the

principal amount outstanding

Timevalue ofmoney

Creditrisk


costsCharacteristics which are not principal orinterest


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Analysis of the underlying pool

Is it possible toidentify the

underlying poolof instruments

that are creatingthe cash flows(look through)?

Do the

contractualterms of thetranche fulfill theCCC criterion?

Does theunderlying pool

contain at leastone instrumentwhich fulfills theCCC criterion?

Do all otherinstruments in

the pool reducethe cash flow

variability oralign the cash

flows of thetranche with thecash flows of the

pool ofunderlying

instruments?

Is the exposureto credit risk of

the tranche

equal to or lowerthan that of theunderlying pool

of financialinstruments?

Contractually linked instruments


Contractual cash flow characterist ics (CCC) criterion fulfil led?

Yes

No

Detailed instrument-by-instrument analysis may

not be necessary

Collateralization of the pool doesnot influence the assessmentunless the entity acquired the

tranche with the intention ofcontrolling the collateral


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Entity’s seniormanagement

changes business model

Reclassification


2

Reclassification of financialassets prospectively from the

reclassification date

3

The first day of

the firstreporting period

following thechange in

business model

External or internalchanges which aresignificant to the

entity’s operations

1

Demonstrable to external parties


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Attention PointsClassification and Measurement of Financial AssetsCritical changes (particularly for financial institutions)

Most preliminary studies are based on IFRS 9 as issued in 2010. Critical changes from there on require further amendmentsregarding:

• Further guidance regarding the classification to the Amortised Cost Category

• Introduction of the FVTOCI category

• Amendments regarding the CCC criterion especially regarding extension and prepayment options as well as modified timevalue of money elements

Sales out of the AC business modelSales may be consistent with an AC business model if they are infrequent or insignificant in value (bothindividually and in aggregate). Also sales required by external parties (e.g. regulators) need to beassessed on this basis

Classification of the liquidi ty reserveDepending on frequency, value and timing of sales, classification of the liquidity reserveinto the FVTOCI or FVTPL category may be necessary

Contingent prepayment optionsIf certain criteria are fulfilled, also contingent prepayments options maynow be in line with the CCC criterion

Modified time value of money elementIdentification of instruments with relevant elements (e.g.3-M-EURIBOR reset monthly) and operationalization ofthe Benchmark-Tests

12

3 4


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Transition and

Effective Date



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• New ‘own credit risk’requirements can be earlyadopted in isolation

• No need to restate priorperiods (no hindsight)

• Application of allrequirements ofIFRS 9 (2014)

Transition and Effective Date

01.01.2018retrospectively

IFRS 9 shall be applied forannual periods beginning on orafter

Early applicationpermitted(if EU endorsed...)



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Transition - Classification and Measurement


New requirements w ill generally apply retrospectively…

... with some exceptions and practicability accommodations

Business modelassessment

• Made on Date of Initial Application (DIA)

SPPI criterionassessment

• Based on facts & circumstances at time of initialrecognition

Equityinstruments

FVTOCI

• Election made based on facts & circumstances at

DIA

Fair Value Option • Re-opened in some cases based on facts &circumstances at DIA

22


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Transition – Expected loss impairment model




Significantincrease in credit

risk

• Assessed at Date of Initial Application (DIA) sincedate of initial recognition

• Using reasonable and supportable informationavailable without undue cost or effort

Not available

without unduecost or effort

• Recognise lifetime expected credit losses untilderecognised

• Unless low credit risk at reporting date

23


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Transition from IAS 39 to IFRS 9 hedge accounting


New requirements w ill apply prospectively…..

With specific exceptions with regard to time value and forward elements…

Qualified hedgingrelationships under IAS 39at the date of initialapplication

Qualified hedgingrelationships under IFRS 9from the date of initialapplication

Transition requirements atthe date of ini tialapplication

Continuing hedging relationships(after rebalancing on transition)

X

A new hedge relationship could bedocumented prospectively

XMandatory discontinuation of thehedge relationship on transition

But... accounting policy options when adopting IFRS 9:

• apply the IAS 39 hedge accounting requirements for Portfolio Fair Value Hedges of InterestRate Risk (only); or

• continue to apply IAS 39 hedge accounting requirements for all hedges.

24


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Impairment


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AC FVTOCIFVTPL/

FVTOCI Option forcertain equity instruments

Within the scope of the impairment model

Outside the scope ofthe impairment model

Financial assets in the scope of IFRS 9

Loancommit-ments

(unless @FVTPL)

Financialguarantees

(unless @FVTPL)

Leasereceivables

(IAS 17)

Contractassets

(IFRS 15)

Scope

Subsequent measurement …



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Impairment stock anticipated to

increase upon transition

Impairment volatility also tosignificantly increase post transition

Changes require early and ongoingquantitative impact assessment to:• Prepare communication of

change to key stakeholders and• Inform key design choices

including:o Model methodology

o Stage 2 and 3 cut-offs

Impairment Focus Areas

Models

Data

IT

Controls

Reports

People

• Scoring, pricing• PD, LGD EAD• Behavioral lifetime

• Data history• Operational data

• Source systems• Datamarts• Calculators

• Governance• Model governance

• Process controls

• Internal & external• Quantitative &

qualitative

• Risk & Finance roles &responsibilities

• Skills and resources

3. Implementation complexities

Complex implications across multiple

dimensions of the Operating Model.

2. Financial Impact1. Impairment Requirements

New general impairment model

create the biggest challenge

IAS 39 IFRS 9

Impairment stock

Q1 2014 Q2 2014 Q3 2014

Volatility

IAS 39 IFRS 9

Stage 3Objective

Evidence ofImpairment

Stage 2Significantincrease incredit risk

Stage 1Initial

recognition

Change in credit risk

1 year EL Lifetime EL

Gross basis Net basis

Loss Allowance

Interest revenue

Credit risk management• Assumptions, methodologies,inputs, techniques and policies

Expected credit loss evaluations• Movements between stages• ReconciliationsCredit risk profile• Increased granularity

Accounting Treatment & Disc losure

Multiple challenges



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General impairment model

Expected Loss Model

Lossallowance

Apply effectiveinterest rate to…

Initialrecognition Stage 2

Lifetime expectedcredit losses

Gross carryingamount

Stage 3

Lifetime expectedcredit losses

Net carryingamount

Stage 1

12-month expectedcredit loss

Gross carryingamount

Objectiveevidence forimpairment?

Significantincrease incredit risk?

Change of credit risk since initial recognition



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Significant increase in credit risk - Transfer out of Stage 1

Impairment Requirements: Change in credit risk

Relative model

Credit risk at initialrecognition

Current credit risk

Initial recognition Reporting date

Stage 2Stage 1

Significant

increase incredit risk?

compare

29

General princ iples

• Comparison of lifetime PDs (not Expected loss)

• Absolute comparisons only are not appropriate. Mustconsider both initial credit risk and time to maturity

• Principle based approach (no precise definition ofincrease in credit risk)

• Consider, reasonable and supportable information thatis available without undue cost or effort“

o Indicators (multifactor and holistic analysis)

o Forward looking and past due information

o At individual level or collectively


Probability ofdefault (PD)

Definition: default

• An entity shall apply a default definition that is consistent with thedefinition used for internal credit risk management purposes for therelevant financial instrument

• Rebuttable presumption that default does not occur later than when afinancial asset is 90 days past due

Significantincrease incredit risk?


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Example indicators

Changes in termsif the instrumentwould be newlyoriginated

Downgrade of the

internal or externalrating

Adverse changes

in business,financial oreconomicconditions

Changes in theentity‘s creditmanagement

(e.g. watch listmonitoring)


risk on otherinstruments of the

same borrower

Changes inexternal marketindicators

(e.g. creditdefault swapsprices for theborrower)

30

Past due

information

No transferas long as“low credit

risk”


Significant increase in credit risk - Transfer out of Stage 1



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Policy choice

Stage 2Stage 1

Significant increase in credit risk?

Approximation

Low credit riskMore than 30days past due

12-month-PD

Rebuttableassumption

Assessment on borrowerlevel

Consistent thresholds onportfolio level Latest point of

transfer to stage 2e.g. investment grade


Significant increase in credit risk - Assumptions and approximations



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„ Bottom up“ - Approach

„ Top down“ - Approach

t0 t1

Significant increase incredit risk

Transfer of asubportfolio

Stage2

Stage1

t0 t1

Significant increase incredit risk

Transfer of apercentage Stage

2Stage

1

25%


Significant increase in credit risk - Collective Assessment options


Transfer out of stage 1 should be identified on a timely basis with options to consider

collective assessment information on portfolio or sub-portfolio level


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Lenders grant a

concession relating tothe borrower’s financial

difficulty

Probablebankruptcy or other

financialreorganisation

Breach of contract(e.g. past due or default)

Credit-impaired

= IAS 39

Significant financialdifficulty of theborrower

Disappearance of anactive market for thatfinancial asset because offinancial difficulties

Purchase or origination of afinancial asset at a deep

discount that reflects theincurred credit losses


Objective Evidence of Impairment - Transfer out of Stage 2



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Measurement atindividual instrumentor on portfolio level

Level

Discounted to thereporting date using theeffective interest rate atinitial recognition or anapproximation thereof

Time value of money The estimate shall always reflect:• The possibility that a credit loss occurs• The possibility that no credit loss occurs

Expected value

Shortfalls of principal and

interest as well as latepayment withoutcompensation

Cash shor tfalls

Maximum contractualperiod under consideration(incl. extension options)

Period

All reasonable andsupportable informationwhich is available

without undue cost oreffort includinginformation about pastevents, currentconditions and forecastsof future economicconditions

Information

Measurement of expected credit losses (EL)

Impairment Requirements: Loss Allowance



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Bond

Time (years) 1 2 3 4 5

coupon 50 50 50 50 50

capital repayment 1000

cash flows 50 50 50 50 1050

Effective interest rate 5% 5% 5% 5% 5%

DF (EIR) 0,95 0,91 0,86 0,82 0,78

EAD 1 050 1050 1050 1050 10501 000

CDS spread 0,50% 0,60% 0,70% 0,80% 0,90%

LGD 60% 60% 60% 60% 60%

Cumulative survival prob 99,17% 98,02% 96,56% 94,81% 92,77%

Periodic PD 0,83% 1,15% 1,46% 1,75% 2,03%

PD * LGD 0,50% 0,69% 0,88% 1,05% 1,22%

EAD 1 050 1 050 1 050 1 050 1 050

Expected loss per period 5,23 7,25 9,19 11,05 12,80

Expected loss per period (discounted at EIR) 4,98 6,57 7,94 9,09 10,03

Lifetime expected Loss (discounted) 38,62

test (flat PD and constant EAD) 39,32

12M expected loss 4,98

Lifetime expected loss versus 12 month expected loss


35

A simplified example

Impact canbe significant



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Special provisions

• No loss allowance on initial recognition

• Apply a credit-adjusted effectiveinterest rate (based on theexpected cash flows at inceptionincluding expected credit losses)

Stage 3Purchased or originated credit-impaired financial assets

General model

Stage 2 Stage 3Stage 1

• Trade receivables with asignificant financingcomponent

• Contract assets withsignificant financingcomponent

• Lease receivablesPolicy

choice

36

• Trade receivables without asignificant financingcomponent

• Contract assets withoutsignificant financingcomponent

Simplified model

Stage 2 Stage 3


Exemptions from the general model


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risk

Initialrecognition

Modification

D e r e c o g n

i t i o n

N o

d e r e c o g

n i t i o n

Stage 2Stage 1Gain/loss on derecognition

Original credit = credit risk onthe date of modification

Recalculate gross carryingamount and recognisemodification gain/loss

Original credit risk =credit risk on initial recognition

Stage 1

Stage 2


Impairment Requirements: Loss AllowanceModification of cash flows


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Bond

Time (years) 1 2 3 4 5

Coupon 50 50 50 50 50

Capital repayment 1000

Cash flows 50 50 50 50 1050

Effective interest rate 5% 5% 5% 5% 5%

DF (EIR) 0,95 0,91 0,86 0,82 0,78

EAD 1 050 1050 1050 1050 1050

1 000

CDS spread 0,50% 0,60% 0,70% 0,80% 0,90%

LGD 60% 60% 60% 60% 60%Cumulative survival prob 99,17% 98,02% 96,56% 94,81% 92,77%

Periodic PD 0,83% 1,15% 1,46% 1,75% 2,03%

PD*LGD 0,50% 0,69% 0,88% 1,05% 1,22%

EAD 1 050 1 050 1 050 1 050 1 050

Expected loss per period 5,23 7,25 9,19 11,05 12,80

Expected loss per period (discounted at EIR) 4,98 6,57 7,94 9,09 10,03


Presentation of our simplified example


Debit Credit

1/01/2014Financial Asset (AC) – B/S 1000Cash – B/S 1000Impairment loss – P/L 4,98Loss Allowance – B/S 4,98

Impairment Requirements: Accounting & Disclosure


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One year later: scenario 1 – increase in credit risk without full life timelosses


Bond (stress after 1 year)

Time (years) 1 2 3 4

Coupon 50 50 50 50


Cash flows 50 50 50 1050

Effective interest rate 5% 5% 5% 5%

DF (EIR) 0,95 0,91 0,86 0,82

EAD 1 050 1 050 1 050 1 050

1 000

CDS spread 1,20% 1,30% 1,40% 1,50%

LGD 60% 60% 60% 60%

Cumulative survival prob 98,02% 95,76% 93,24% 90,48%

Periodic PD 1,98% 2,26% 2,52% 2,76%

PD*LGD 1,19% 1,36% 1,51% 1,65%

EAD 1 050 1 050 1 050 1 050

Expected loss per period 12,47 14,24 15,87 17,36

Expected loss per period (discounted at EIR) 11,88 12,92 13,71 14,28


Debit Credit

31/12/2014

Impairment loss – P/L 6,9 (= 11,88 - 4,98)

Loss Allowance – B/S 6,9

Financial Asset (AC) –B/S 50

Interest revenue – P/L 50



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One year later: scenario 2 – increase in credit risk with full life timelosses


Bond (stress after 1 year)

Time (years) 1 2 3 4

Coupon 50 50 50 50


Cash flows 50 50 50 1050

Effective interest rate 5% 5% 5% 5%

DF (EIR) 0,95 0,91 0,86 0,82

EAD 1 050 1 050 1 050 1 050

1 000

CDS spread 1,20% 1,30% 1,40% 1,50%LGD 60% 60% 60% 60%

Cumulative survival prob 98,02% 95,76% 93,24% 90,48%

Periodic PD 1,98% 2,26% 2,52% 2,76%

PD*LGD 1,19% 1,36% 1,51% 1,65%

EAD 1 050 1 050 1 050 1 050

Expected loss per period 12,47 14,24 15,87 17,36

Expected loss per period (discounted at EIR) 11,88 12,92 13,71 14,28

Lifetime expected Loss (discounted) 52,79

Debit Credit

31/12/2014

Impairment loss – P/L 47,81 (= 52,79 - 4,98)

Loss Allowance – B/S 47,81

Financial Asset (AC) –B/S 50

Interest revenue – P/L 50



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Credit r iskmanagementpractices and their

relation to therecognition andmeasurement ofexpected creditlosses

1Evaluation ofexpected credit lossamounts in the

financial statementsarising from

2Credit risk profileincludingsignificant credit

risk concentrations

3


Impairment Requirements: Accounting & DisclosureThe disclosures shall enable users of financial statements to understandthe effect of credit risk on the amount, timing and uncertainty of future

cash flows


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1

Disclosure ofaccounting policies

chosen and judgment applied

Definition ofdefault

Grouping ofassets

Transfer

out ofstage 2

Modifications

Assumptions,inputs, etc.

Forward lookinginformation

Changes inestimationtechniques

Transfer

out ofstage 1

Credit risk management practices and their relation to the recognitionand measurement of expected credit losses




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2

Evaluation of the amounts in the financial statements arising f rom

expected credit losses

Reconciliationof the lossallowance

Reconciliation inthe gross carrying

amountModifications

Collateral(and other creditenhancements)

Write-off




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Illustrating the application of the reconciliation of the loss allowance

45

(IFRS 7.IG20B)



Stage 1 Stage 2 Stage 2 Stage 3

12-month EL (collectivelyassessed)

(individuallyassessed)

Loss allowance as at 01. January X X X X

Changes du to financial instruments

recognised as at 01. January:

- Transfer to stage 1 X (X) (X) --

- Transfer to stage 2 (X) X X --

- Transfer to stage 3 (X) -- (X) X

- Financial assets that have been

derecognised during the period

(X) (X) (X) (X)

New financial assets originated or

purchased

X -- -- --

Write-off -- -- (X) (X)

Changes in models/risk parameters X X X X

Foreign exchange and other

movements

X X X X

Loss allowance as at 31. December X X X X

Mortgage loans - loss allowance

-- X


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3

An entity‘s credit risk profile including significant credi t risk

concentrations

Significantconcentrations of creditrisk by for example:

• Loan-to-valuegroupings

• Geographicalconcentrations

• Industryconcentrations

Disclose by credit riskrating grade

• The gross carryingamount of financialassets

• The exposure to creditrisk on loancommitments andfinancial guaranteecontracts

Creditrisk

exposure




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47

Financial Impact: Impact Assessment Process

Impact Assessment Process

Using a structured end-to-end process to quantify the financial impacts,understand portfolio drivers and inform senior management strategic

decisions.



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Fi i l I t V l tilit id ti


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49

Stage 2 migration can result in earlier recognition ofincreased impairment stock with “Credit deterioration”options available including:

• Current PD (relative to risk appetite or origination)• Delinquency and forbearance

• Lifetime PD changes from origination

Stage 1 impact for secured is limited in this exampleas 12 month EL is already used for performing assets

Assets in Stage 2 at transition will have an increasedimpairment stock as a full lifetime Expected Loss isused

IAS 39 recognises losses later than IFRS 9 so P&Lvolatility is driven by migration to credit deterioration (e.g.rating downgrade) pre subsequent deterioration to default

All IFRS 9 options recognise loss earlier with delinquency arequired Stage 2 trigger (see IFRS 9 Option 1) which willdrive account level P&L movement when LEL is recognised

Defining credit deterioration earlier (e.g. using PDdowngrade in IFRS 9 Options 2) increases P&L volatilityyear on year but reduces the impact at arrears

Variances at write off remain constant with the end cashflow position under IAS 39 and all IFRS 9 options

Transition from IAS 39 to IFRS 9 P&L volatility post transition to IFRS 9

At Transi tion : Increase driven by status and product

1

2

3

Volatility: P&L movement increase is policy driven

1

2

3

4

IAS 39 Variance IAS 39

EL (£) LEL (£) Total (£) (£) Option 1 Option 2

1 At Origination 5 38 5 0 5 5 5

2 Performing 8 50 8 0 3 3 3

3

Downgrade

48 121 48 0 40 114 40

4 Missed Payment 2 126 209 126 83 161 87 78

5 Default 3 600 600 600 0 391 391 474

Impairment Stock

IFRS 9

P&L Impairment

ChargeYear Status

IFRS 9Stage

1

1

2

3 42

3

1

Financial Impact: Volatility considerationsIFRS 9 Impairment volatility increases in our example although the volatility posttransition depends on multiple design decisions


Fi i l I t R f lt


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53-67% 67-83% 83-90%

1. PD Modelling

2. LGDModelling

3. Behavioural Life

4. Stage 2 Triggers

5. Stage 3 Approach

Scenario selected, considering IFRS 9 TOM design options

50

Financial Impact: Range of results

Dynamic PD across the lifetime Constant current PD

Constant LGD Forward looking LGD

Prepayment included Prepayment excluded

30 days past due (current) 1 day past due (current) 1 day past due (current & last 12 m)

No forbearance trigger High risk forbearance (current) High & low risk forbearance (current & last 12 m)

No credit risk grade trigger High credit risk grades, but wi thin risk appeti te Credit risk grades above risk appet ite

Constant LGD Forward looking LDGIAS 39 estimate

Example Mortgage Portfolio• 1,728 simulations generated• Transition impact ranged from 52.5% to 90.2%• Conservative selection of Stage 2 triggers results in

higher impairment stock but also attracts lower ongoingP&L volatility due to more stable Stage 1 assets

Transition Impact – Impairment Stock Change

Volatility Impact – Ongoing P&L Volatility

Medium LowHigh

Leveraging our Loan Impairment Valuation Engine (LIVE), we have estimatedIFRS 9 financial impacts across different model methodology and impairmentchoices plus assumptions to inform firm’s key design decisions

Other Portfolios• Transition impact highest for Credit Card portfolios (200-

260%), Loans (85-120%) and Current Accounts (25-80%)• Variable for Commercial portfolios• Volatility is highest for portfolios with longer behavioural

lives


Fi i l I t A ti d it l i t ti


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Expected position under IFRS9 if no change to Basel rules

Stock of relevant provisions

One-year Expected Loss AmountCount as Tier 2 capital

(up to a limit)

Basel III treatment: Scenario 2: Provisioning stock higher than one-year EL

Basel III treatment: Scenario 1: One-year EL higher than provisions

One year Expected Loss Amount

Stock of relevant provisions Deduction from CoreTier 1 Capital

Standardised approach IRB approach

Any impairment loss on a loan taken to the incomestatements has a 1:1 impact on Core Tier 1 capital asit reduces retained earnings. However, the cumulativecollective impairment provisions can be eligible tocount as Tier 2 capital resources up to a “ceiling” of1.25% of Risk Weighted Assets (RWAs) calculated underthe standardised approach. An example of suchimpairment provisions would be those held to coverlatent (incurred but not reported) losses on a pool of

performing residential mortgages.

The IRB approach uses a one-year time horizon, andintroduces the concept of Unexpected Loss (UL) andExpected Loss (EL) over that period. In essence, in thedefinition of eligible capital resources, the EL replacesthe stock of accounting impairment provisions onportfolios subject to measurement on the IRB approach(as long as the EL exceeds accounting impairment).However, in scenarios where the accountingimpairment stock is greater than the EL, the surplus

over the EL is allowable to count as Tier 2 capitalresources up to a ceiling of 0.6% of RWAs.

The results of our recent survey showed thefollowing:

• 11% of participants expected impairmentprovision to be lower than regulatory EL

• 13% of participants expected impairment

provision to be between 0-10% higherthan IRB

• 9% of participants expected impairmentprovision to be between 10-20% higherthan regulatory EL

• 7% of participants expected impairmentprovision to be more than 20% higherthan regulatory EL

• 60% of participants do not yet know

Financial Impact: Accounting and capital interaction




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CRD IV Requirements

4.5%

1.5%

2%

2.5%

0-2.5%*

* Upper bound may increase furtheron supervisor discretion

Common Equity Tier1 (CET1)

Additional Tier 1

Tier 2

Capital

Conservation Buffer

Counter-cyclicalCapital Buffer

3%Tier 1 Capital

Exposure

CRD IV Capital Impact Leverage Ratio Impact

Capital position w orsens in terms of capital quality,due to the ‘re-tiering’ effect

Leverage ratio declines

GrossExposure Tier 1 Capital

Tier 2 Capital Provisionstock

Tier 1 CapitalNet Exposure

Provision stockdeduction

1. Provision stock increasesupon IFRS 9 transition

3. Tier 1 capital andexposure reduceequally and thereforethe leverage ratio willdecrease

↑

↓

2. If new provision stockrequired, core Tier 1 capital)reduces, but if classified as'collective' can be counted asTier 2 capital ('re-tiering effect')

↓

↑

↓

• Collective provisions on standardised portfolios that are freely and fully available, can be counted as Tier 2 capital(limited to 1.25 % of RWAs)

• Specific provision reduce the asset balance and associated risk weighted assets. However, if the loan is 3 monthspast due and provision covers less than 20% of net exposure, risk weights on 'un-provisioned‘ balance increases

• At transition to IFRS 9, some capital instruments will be reallocated from Tier 1 to Provision Fund Tier 2 which mayrequire new Tier 1 capital instruments to replenish

• The change in Tier 2 would be ∆Provision assuming the 1.25% RWA cap on Provisions counting towards Tier 2capital is not modified or exceeded

↑

Financial Impact: Accounting and capital interactionUnder the Standardised Approach, new capital may be required to replenish Tier1 capital and a potential reduction in the leverage ratio




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CRD IV Requirements

4.5%

1.5%

2%

2.5%

0-2.5%*

* Upper bound may increase furtheron supervisor discretion

Common Equity Tier1 (CET1)

Additional Tier 1

Tier 2

Capital

Conservation Buffer

Counter-cyclicalCapital Buffer

3%Tier 1 Capital

Exposure

Capital position remains unchanged / improves in d ownturn Leverage ratio remains unchanged /declines in a downturn

Gross

Exposure Tier 1 Capital

Tier 2 Capital

Prov. shortfalldeduction

IRB ELProvision

stock

Tier 1 CapitalNet Exposure


Provision stockdeduction


↑

↔

↔

3. Provision shortfall and Tier 1 capitalreduction cancel out

2. IRB EL unchanged as it is uses grossexposures (assuming the additionalprovisions do not trigger an IRB default)

1. Provision stock increases upon IFRS9 transition ↔

↔ 4. Tier 2 capital increases if a provisionsurplus exists

Prov. surplusadd-on ↑

CRD IV Capital Impact Leverage Ratio Impact

↑ ↑ ↑

↑

If provision stock < IRB EL – Provision Shortfall• Mortgage focused IRB banks have substantial provision shortfall, resulting in a capital deduction. It is likely, that under

the current macroeconomic outlook, this shortfall will decrease but remain a capital deduction

If provision stock > IRB EL – Provision Surplus• In an economic downturn, IFRS 9 provision stock could exceed the IRB EL• CRD IV only covers the possibility of accounting for a provision shortfall but does not specify the requirements for

provision surplus• EEL difference can be added back to Tier 2 Capital (limited to 0.6% RWA: GENPRU) resulting in stronger Tier 2

capital but not impacting leverage ratio

Financial Impact: Accounting and capital interactionUnder the Internal Ratings Based (IRB) Approach, the excess expected lossabsorbs any potential capital impact, unless it is fully eroded in a downturn.


I l t ti C l iti Fi id I t


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Implementation Complexities: Firm-wide Impact

Risk adjusted pricing

Risk and Finance operatingmodel efficiency• People• Processes• Data & systems

• Policies• Models• MI & Reporting

Pillar 1 and 2A capital requirements

Pillar 2Bcapital

planningbuffer for

drawn downin a stress

Basel 3 Tier 1 and Tier 2capital instruments andleverage ratio

P&L impact of IFRS 9provisioning, includingon-going volatility

Portfolio andproduct mix

Stakeholderexpectations

Externalrating,

reflectingincreased P&L

volatility

Market position relativeto peers

Cost offunding

Externalaudit

Balance sheet impact of IFRS9 provisioning, including stepchange upon introduction

Products andvolume

Pricing

Disclosures and

market discipline

Revenue Growth

Operating Margin

Liquidity

Reputation

Capital

IFRS 9

IFRS 9 creates wider challenges for organisations beyond the direct, quantifiableimpact on impairment and P&L with indirect but material impacts on a wide rangeof factors contributing to shareholder value.


I l t ti C l iti Ti li


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2014 20152016 2017 2018

Oct Nov Dec Jan Feb Mar Q2 Q3 Q4

Study

Design

Build

Test andHandover

Test

QIS 4

Mandatory effective date

(1st

January 2018)

S C

P a r a

l l e l

R u n

L i v e

R u n

Most banks believe that three years is the necessary lead time for all phases of IFRS 9. Typically banks areimplementing the components of IFRS 9 as a related set of work streams, particularly as the judgments made forclassification and measurement purposes will determine whether instruments are held at fair value or amortized cost,and hence which financial instruments will be subject to impairment testing.

Hedge Accounting

Classification & Measurement

Impairment

4th Global Deloitte IFRS SurveyStatus of IFRS 9 Implementation Project as of 2013

Number of institutions with activity completed

Number of institutions with activity not completed

Industry Perspective

Impact Assessment Design Build

19

33

35

35

21

19

2

2

5

52

52

49

1

1

0

53

53

54

S C

S C

Project Plan

S C

Pilot QIS 1

S C

S C

S CQIS 3

TOM Build

QIS 2

Pilot TOM Study

TOM Design

S t e e r i n g

C o m m

i t t e e

( S C )

Implementation Complexities: TimelineThe Study Phase is a starting point of the IFRS 9 journey and should focus onunderstanding the IFRS 9 financial and operational implications, with outcomesbeing key inputs to the design and build planning phase.


I l t ti C l iti LEL M d l O ti


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56

Credit Risk Analytics Alternative Delivery Models

L o s

s G i v e n

D e f a

u l t ( L G D )

Modelling Options Macroeconomic Adj us tments

P r o b a b i l i t y o f

D e f a u l t

( P D )

E x p o s u r e a t

D e f a u l t ( E A D )

Constant : Extrapolate long run IRB PD output minusSR

Each model approach can be prioritized based ondata availability, approach maturity and model risk:

Primary approach Secondary approach Tertiary approach(s)

Portfolio priorities (varies per jurisd iction)

R e

t a i l

m o r t g a g e

R e

t a i l L o a m

( U n s e c u r e

d )

R e

t a i l O / D &

c r e

d i t c a r d

U n s e c u r e

d /

S e c u r e

d S M E

A s s e

t F i n a n c e

C o r p o r a

t e

W h o

l e s a

l e &

T r e a s u r y

S p e c

i a l i s e

d

L e n

d i n g

Risk tree: Calibrate Hazard function per risk segment

Regression: Develop “default in ever” scorecard

Migration Matrix: Create Markov Chain per grade

Market implied: Extrapolate data e.g. CDS spreads

Simulation: Monte Carlo default distribution estimate

C o m p o n e n t

M e t r i c

Constant : Recalibrate downturn output to PiT result

Risk tree: Calibrate average loss risk per risk segment

Regression : Develop “average loss in ever” scorecardSimulation: Monte Carlo loss distribution estimate

Constant : Recalibrate downturn output to PiT CCF

Best Estimate: Project most likely repayment profile

Regression: Develop “average in ever” scorecard

Simulation: Monte Carlo balance distribution estimate

L H M L

M L M M

L H M M

M M M M

M L H L

H L M M

L H M L

M L M M

M H M MH L M M

L H M L

H L M M

L H H M

H L M M

Modelling Risks

B u

i l d

C o m p

l e x

i t

y L o w

a c c u r a c y

H i g h

V o

l a t i l i t y

P o o r

u s a

b i l i t y

High / Medium / Low)

Year 1 adjustment

Multi year projection

Year 1 adjustment


Year 1 adjustment


Year 1 adjustment


Year 1 adjustmentMulti year projection

Year 1 adjustment


Year 1 adjustment


Forward lookingresults need toincorporate economicexpectations overremaining life

Implementation Complexities: LEL Model OptionsForward looking lifetime expected loss impairment models willintroduce operational complexity across risk and finance withspecific challenges for firms offering multiple credit products


Implementation Complexities: Detailed Approach


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Impairment

modelling

Impairment

calculation

Impairment

forecast Disclosure

Models

Data

Processes

Controls

Reports

People

IT

WP1 – Impairment model methodology

WP2 – Impairment

modelmain-

tenance

WP3 – Impairmentcalculation

WP6 – Organisation design

WP4 – Impairment

fore-casting,

budgeting &stresstesting

WP7 – Impairment IT infrastructure

WP5 – Disclosure

Study Approach

Potential options are defined in the beginning of the StudyPhase and evaluated against various criteria.

Project Costs Quantitative BenefitsProject Risks

£m or FTEProject investment toachieve IFRS 9compliance and / orstreamlining benefits.

£mQuantitative benefitsarise from cost savings:• Regulatory costs• FTE & 3rd party costs

Delivery risksassociated with theselected option, with apotential adverse.

R A G

5-year ReturnQualitative Benefits

Qualitative benefits areassociated per TOMdimensions and includenon-monetary factors.

£m- Project Costs+ Quantitative Benefitsover a 5-year horizon= 5-year Return

Implementation Complexities: Detailed ApproachOutlined below is an example of a study approach for assessing the operationalmodel against the IFRS 9 Impairment rules, split into seven work packages thatspan functional capabilities and operating model layers impacted by IFRS 9.

EL and LEL Modelling Methodology design Impairment Actuals & forecast process flowsOrganisational design & roles

Illustrations of high level design

Study approaches foreach IFR9 componentare designed to alignwith selected optionand meet firm principlesas illustrated below


Implementation Complexities: Balancing Priorities


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Implementation Complexities: Balancing Priorities

PrecisionLow

volatility

Internalfocus

Market insight

Accuracy Timeliness

Complexity Clarity

Global Regional

Setting a Balanced Approach

The IFRS 9 design needs to meet a number of – sometimes conflicting – requirements.

Managing Stakeholders

External auditors

SEC and listing author ities

Management

Shareholders

Banking regulators

Rating agencies

Customers

There is a wide range of stakeholders affected bythe IFRS 9 implementation approach, as well as thebusiness-wide impact.

Designing an IFRS 9 programme which addresses businessrequirements requires clear communication and management of multiple

stakeholders.



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Transition and

Effective Date



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Transition Expected loss impairment model


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Transition – Expected loss impairment model





risk

• Assessed at Date of Initial Application (DIA) sincedate of initial recognition

• Using reasonable and supportable informationavailable without undue cost or effort

Not availablewithout unduecost or effort

• Recognise lifetime expected credit losses untilderecognised

• Unless low credit risk at reporting date

61


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General Hedge

Accounting

© 2014 Deloitte

Project Overview


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Project Overview

Starting Point:

IAS 39

(Portfolio Fair ValueHedge in particular)

Discussions on

IFRS 9 Phase 3Hedge Accounting

Since

2008/09

Finalisation of

IFRS 9 Phase 3General Hedge Accounting

November

2013

Can be applied until

macro hedges project is

finished

No longer part of the IFRS 9 project – discussed as separate agenda project

Macro Hedge Account ing

September 2010

April 2014

October 2014

Evaluation of comments received and articulation of next steps

Publication of DP/2014/1 Account ing for Dynamic Risk Management:

a Portfo lio Revaluation Approach to Macro Hedging

For discussion

purposes only, no

requirements yet!


Transition from Hedge Accounting Requirements


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Transition from Hedge Accounting Requirementsunder IAS 39 to IFRS 9 Financial InstrumentsKey elements that have not changed…

* Except for fair value hedges of equity instruments for which the OCI option has been exercised

No change inmechanics of fair

value, cash flow andnet investment

hedge *

Most written options

continue to beprohibited as hedging

instruments

No change tothe requirementto measure and

recogniseineffectiveness

Applying hedgeaccounting remainsa choice


Transition from IAS 39 to IFRS 9 hedge accounting


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Transition from IAS 39 to IFRS 9 hedge accountingKey changes introduced by IFRS 9

Hedging Instrument Hedged Item

Designate and document

Cash flowhedge

Fair valuehedge

Net investmenthedge

Effectiveness assessment

“Mechanics” (a/c entries)

Disclosures

Ineffectiveness measurement

No more 80-125%test

Only prospective

More disclosures

Non-derivativesat FVTPL

Time value /Forward element

Foreign currency basis

Separate riskcomponents

Groups of items,including net

positions

Aggregate exposures


IFRS 9 hedge accounting


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g g Accounting for the “cost of hedging”

Time value ofOption

contracts

Aligned *

timevalue

Exclude time value

from designation ofthe hedging

instrument andaccount

separately?

Accountexcluded

element at

FVTPL, oras ‘cost ofhedging’?

No

Yes

Yes

Aligned *forward

element

Residual

+

Deferred

in OCI

P&L

Residual

+P&L

Deferredin OCI

See next slide

* The aligned time value / forward element is that of a purchased option / forward contract with critical terms that perfectly match the hedged item.

CoHExclude forwardelement from

designation of thehedging instrumentand accountseparately?

FVTPL

Entire value subject to mechanicsof FV hedge, CF hedge & NetInvestment hedge

No

Forwardelement of

Forwardcontracts andForeign

currency basis


IFRS 9 hedge accounting


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IFRS 9 hedge accounting Accounting for the ‘cost of hedging’ (cont’d)

Time value / Forward element = cost of hedgingSubsequent FV changes OCI

“ Transaction related”

Non-financial

asset/liability

Other e.g., financial

asset/liability

“ Time-period related”

Account ing

ReclassificationDoes the time value / forward element relate to a transaction

related hedged item or to a time-period related hedged item?

Forward contracts -

Account ing policychoice for each

hedging relationship

Upon transaction occurrencereclassify and adjust carrying

amount of hedged item(basis adjustment)

Upon transaction occurrencereclassify and recognise in

P/L in sync with hedged item

Amortise to P/L on rationalbasis over term of hedging

relationship

Cumulative changes in FV AOCI


Qualifying hedged items


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Qualifying hedged itemsRisk components of non-financial items


Crude oil

Under IAS 39 Under IFRS 9

Crude/Fueloil spread

Transportcharges

Crude oilforward

Crude oil

Crude/Fueloil spread

Transportcharges

Crude oilforward

Risk components ofnon-financial items

Separatelyidentifiable

ONLY ELIGIBLE IF

Reliablymeasurable

+

Non-financialhedged item

Hedginginstrument

Non-financialhedged item Hedginginstrument

Expert

68

Qualifying hedged items


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Qualifying hedged items Aggregated exposure


Example: On 01/01/19, Entity A (functional currency €) wants to hedge highly probableforecast interest expense in $.

A derivative An exposure

Aggregated

exposure

FV interest rate riskSecond level relationship Designation on 01/01/20 withthe term ending 31/12/2021 Aggregated exposure IRS (pay variable €/receive fixed €)

Hedged item Hedging instrument

CF $ interest rate andFX risk

First level relationship

Designation on 01/01/19 withthe term ending 31/12/2021

Forecast $ variableinterest payments

CCIRS (pay fixed €/receive variable $)

Two risk exposures Features

Forecast fixedinterest

payments in €

Hedge effectiveness requirements


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Hedge effectiveness requirementsThree-part test


Economicrelationship

Values of hedged item andhedging instrument generally

move in opposite direction

Qualitative vs quantitative

assessment (ineffectivenessstill measured)

Prospective test only

Credit riskdoes notdominate

Credit riskcan negateeconomic

relationship

Both own credit andcounterparty credit

Consider bothhedged item and

hedging instrument

Hedgeratio

Generally the actual ratio

Cannot create

ineffectivenessinconsistent with thepurpose of hedge

accounting

Rebalancing of hedge ratiomay be required

IFRS 9 hedge accounting – Impact


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IFRS 9 hedge accounting Impact

71

No impact Examples

• Entities which applymacro-hedging

Financialinstitutionsmanaging interestrisk and applyinghedge accounting

on portfolio basis• Entities which apply

straightforwardhedge accounting

Treasury centerswhich enter intoplain vanilla IRSthat perform directswap of interest

rates• Entities where costs

of hedgeaccounting stillexceed benefits

Burden of hedgedocumentation

Impact

More types of hedge relationships qualifyingfor hedge accounting, for example:

• Hedge of specific risk components

• 80-125% bright line removed

• Potentially less P&L volatility whenhedging with options and forwardcontracts

• Hedge of aggregate exposures

More disclosures!

Impact on Entit ies



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Transition and

Effective Date



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Transition from IAS 39 to IFRS 9 hedge


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Transition from IAS 39 to IFRS 9 hedgeaccounting


New requirements w ill apply prospectively…..

With specific exceptions with regard to time value and forward elements…

Qualified hedgingrelationships under IAS 39at the date of initialapplication

Qualified hedgingrelationships under IFRS 9from the date of initialapplication

Transition requirements atthe date of ini tialapplication

Continuing hedging relationships(after rebalancing on transition)

X

A new hedge relationship could bedocumented prospectively

XMandatory discontinuation of thehedge relationship on transition

But... accounting policy options when adopting IFRS 9:

• apply the IAS 39 hedge accounting requirements for Portfolio Fair Value Hedges of InterestRate Risk (only); or

• continue to apply IAS 39 hedge accounting requirements for all hedges.

74


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IFRS9Implementationchallenges

Arno De Groote

Enterprise Risk Services

What are your biggest concerns about using


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What are your biggest concerns about usingcredit risk data & systems for financial reportingpurposes?


Source: the 4th Banking Survey


77/96

Will data management really be a challenge?

Data and systems


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The calculation of impairments under IFRS 9 will incorporate historical, current and supportable forecast

information. This will require the involvement from various divisions within the organization.

Past Experience:Borrower, s egmentation

and other riskcharacteristics

Prepayment information,Cash flow information

(past due, other), specificcontract characteristics,…

Forward lookinginformation (economic

outlook), additional clientand market information

Risk dataTreasury andFinance data

Other data

Collated dataset from which to produce reporting

Although IFRS 9 states that major system enhancements are not envisioned as part of newrules, the changed rules, as well as a change in MI requirements, do need to be considered


It’s a messy world of data out there…


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It s a messy world of data out there…

Common myths:

• We do not have data quality issues

• Informal data change control processes work

• We know our customers, the products we sell to them and our operating metrics

• IT is responsible for our data so we let them handle it

• We have so many compliance programs in place we must therefore be governing data

Data complexity is oftenunderestimated!

Credit data is noexception……..


Will data management really be a challenge in


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Datasources

Collection Preparation Calculation Reporting

order to reach IFRS9?

• Credit risk informationpreviously used only forinternal purposes supportsfinancial reporting

• Traceability is not anautomated functionality

• Manual adjustments areperformed

• Process is highly decentralizedand involve many EUC tools

• Data quality checks areperformed but on an informalbasis

• Difficult to reconcile dataextracted from different sources

• Variety of legacy systems• Some information kept up to

date in spreadsheets• Multiple credit products

across multiple jurisdictions• Inability to link borrower

information across multiplesystems

Internal &external datasets

required forcalculation and

reporting

Collect andtransform the

data;Quality control,correction and

validation

Valuationengines, IFRS

treatment, IFRScalculations

IFRS accounting Analysis andvalidation of

results

Internal andexternal

reporting;Validation of the

results;

Public disclosure

Operations and monitoring

Data archiving

• Data is not stored in consistent sets• Reconciliation between risk and finance, and reuse of data

(single version of the truth)© 2014 Deloitte Belgium 80


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Deep dive on some datamanagement challenges

Key elements to achieve superior Data Quality


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82

Governance Processes

Systems Data

DataQuality

Operating model

Supporting enablers

Establish an organizational model

and a framework of policies,processes, and enabling

technologies to ensure that datais owned and stewarded

accurately and consistently tomeet business goals

Establishes processes andprocedures to appropriately

diagnose data quality issues,remediate them and monitor thedata quality to keep it evergreen.

Identify and define architecturalcomponents that provide a

framework to facilitate storage,integration, usage, access, and

delivery of data assets across theenterprise.

Standardization, by designing andimplementing a centralized

repository of business rules, datastandards, and data definitionsthat is referenced across the

enterprise.


Any standards from a regulatory point of view?


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Any standards from a regulatory point of view?

83

Insurance undertakings

Solvency II requirements for data quality(technical provisions / internal model)

Illustration of some requirements:

• Establish policies on data quality

• Compile a directory of any data used to operate,

validate and develop the internal model

• Specify in detail the data source, itscharacteristics and usage

• Describe databases, that is data items,construction info, external and internal interfaces,processes used to obtain and load data

• Implement processes, procedures andresponsibilities to ensure the appropriateness,completeness and accuracy of data.

• Assess and monitor the quality of the data

• Correct any material data quality issue identified

Banking institutions

BCBS 239 (Effective Risk Data Aggregationand Risk Reporting) defines eleven principlesthat banking institutions should follow


Metadata Management


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What does Metadata Management stands for ?

• Metadata is information about data providing a context for those business data.

• Metadata management is the organization of metadata with the aim toimprove sharing, retrievingand understanding of enterprise information assets.

What Metadata Management is used for

• Metadata management is the vehicle forinventorying and managing the business dataassets.

• It establishes awareness and understanding ofthe data architecture and IT assets (e.g.applications, software) provided by various dataand application environments.

• It also enables effective adminis tration, changecontrol, and distribution of information about aclient’s information technology environment.

• It tracks and identifies events and changes whichoccurs during data processing and determines theirorigin.


Systems Data

DataQuality

Need to establish a datadictionary


Metadata Management


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What does Metadata Management stands for ?

Illustration


Containing information allowing toidentify and locate precisely thegiven Data Item

Fields describing what the Data

Item is (name, format, etc.) andwhat it contains

Defining the accountability andresponsibility over the Data Item

Describing the Data Quality

Indicators on Key Data Items

Link Finance and Risk data

together in order to improve

the Single Customer View

across the organisation

Data Governance


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What does Data Governance stands for ?

Data Governance defines the organization, roles and mandates that govern decision makingand ownership of data management within the organization. The objective of the datagovernance is to ensure that data is owned and stewarded accurately and consistently tomeet business goals

What Data Governance is used for

• Guaranty that important data assets are formallymanaged throughout the enterprise.

• Ensure that data can be trusted and that peoplecan be made accountable for any adverse eventthat happens because of low data quality.

• Put people in charge of fixing and preventingissues with data so that the enterprise can become

more efficient.

• Support processes which are used to provideinformation that can be used by thewholecompany.


Systems Data

DataQuality

Need to define roles andresponsibilities within

processes.


Data Governance


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Data

Quality

Manager

Data

Owner

System

Owner

Data

Steward

Data

Owner

Data

Owner

Data

Steward

Data

Steward

Data

Steward

Data

Steward

Data

Steward

Data

Steward

Data

Steward

Data

Steward

Data

Steward

Data

Steward

System

Owner

System

Owner

System

Owner

System

Owner

System

Owner

System

Owner

System

Owner

System

Owner

…

…

…

Coordination

Sign-off

Data

handling

System

maintenance

Sponsor

Typical roles

Senior

Function

DataQualityOfficer

DataCustodian

DataCustodian

DataCustodian

DataCustodian

DataCustodian

DataCustodian

DataCustodian

DataCustodian

DataCustodian

Re-think the organisation

design in order to define

roles and responsibilities

under IFRS 9 and facilitate

cooperation between

Finance and Risk


Data Governance


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Illustration of the roles in a data management process

Who does what in the data quality process ?

Seniorfunction

• Supports the organization to communicate and promote the governance• Set standards

• Holds ultimate responsibility for data quality and signs off on the overalllevel

DataSteward

• Handles the data files

• Produces dashboards and controls the quality

• Maintains the data dictionary

• Fix issues

DataOwner

• Controls dashboards

• Approves data directory updates

• Can initiate data cleaning actions

• Sign off on data set or domain level

DataCustodian

• Stores, retains and disposes data as per requirements.

• Designs technical infrastructure to meet requirements (i.e. dataarchitecture)

• Analyses impacts of changes to existing data sources, informationarchitecture, security, etc.

DQ Officer • Coordinates the global effort to install and maintain the governance

• May challenge controls and results© 2014 Deloitte Belgium 88

Data Quality Management


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What is Data Quality ?

The aim of Data Quality Management is to support the predictability of results and reports produced by

the IFRS9 process by assuming quality of input data.

What Data Quality Management is used for

• Data Quality refers to the degree of excellence ofdata used for a specific business need,

• Data Quality represents the state ofcompleteness, appropr iateness and accuracyof data for a specific use. Additional indicators aree.g. integrity, timeliness, validity, accessibility.

• Data Quality management also refers theprocesses and technologies involved inensuring the conformance of data values tobusiness requirements and acceptance criteria.


Systems Data

DataQuality

Need to establish policies anddefine indicators to assess

the quality of data.




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What is Data Quality ?

Illustration of definitions; basis to define Data Quality Indicators


Accuracy means that a high levelof confidence can be placed onthe data. Data is considered to beaccurate if it is free frommaterial mistakes, errors andomissions; the recording ofinformation is adequate,performed in a timely manner andis kept consistent over time.

Example:

• Age at entry is a numericalvalue between 0 and 120

• Variation of averages or totals(e.g. sum assured, duration inforce, reserve, premium, etc.)per LoB/sub-portfolio withinthreshold

Accuracy

Data is considered to becomplete if it has sufficientgranularity to allow theidentification of trends and the fullunderstanding of the behavior ofthe underlying risks or f inancials.

All material informat ion shall betaken into account and reflected inthe data set.

Example:

• For all concerned data, oneyear of complete historicalinformation more than last

year (without merger impact ortransfers between LOBs at apoint in time)

Completeness

Data is considered to beappropriate if it is suitable forthe intended purpose andrelevant to the portfolio of risksbeing analyzed (i.e. directlyrelates to the underlying riskdrivers).

Example:

• All fields are defined asmandatory or optional

• New products have beentaken into account in the datadictionary and all relevantfields are defined: validated byexpert

Appropriateness



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Ensure that the data is

clearly defined.Is a periodic review.

Ensures that the data is free from error before starting the IFRS9calculations.

Is done just after collecting the data and before the execution of anytransformation.

Compare Data Directorywith model data needs

The granularity of thedata attribute must be

specified and validatedby an expert.

Control that allmandatory fields arefilled in.

Verify that the field hasan acceptable value,the right format andrange of values.

Identify deviations fromexpected values basedon expectations andreconcile data withother sources.

Measuring Data Quality in a 4-step-framework

Level 1:Data

Definition

Pre-requisite Elementary controls Complex controls

Level 2:Data

Identification

Level 3:Data

Validity

Level 4:Data

Reasonableness

Data Quality Indicators are then aggregated to repor t data quality in scorecardsby e.g. data set, legal enti ty, …


Are your processes optimized, robust and


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• Streamlined andautomated

• Controlled and traceable

• Documented

• Mainly manual with highrisk of mistake

• Origin of data sometimesunknown

• Undocumented

controlled?

Minimise costs by

pursuing opportunities to

streamline existing capital

and impairment

processes as part of the

IFRS 9 design and build

Maximize benefits byrelying on existing capital

and impairment processes

to reduce the incremental

cost of introducing IFRS 9

in the organisation’s target

operating model


What about your Data Quality Architecture?


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y y

process (ii)process (i)

Input

Output Output

DQI level 2: data occurrence check

DQI level 3: range, format check

DQI level 4: reasonability check

Process controls Process controls

Key considerations:

• DATA COLLECTION: How to establish a link (data flow) between the physical data running throughthe processes and the DQIs documented in the Data Directory?

• DQI CALCULATION: Where can we automate the measurement of DQIs? Where should DQIresults be stored? How to ensure traceability?

• DQI REPORTING: How will dashboarding be organised on data set level? How to reportconsolidated results?

DQI level 2

DQI level 3

DQI level 4

InputDataDictionary Ok?

DataDictionary Ok?



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Your speakers

Contact details


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Audit Partner

Tel: +32 2 800 2045Mobile: +32 496 57 48 96E-mail: [email protected]

Yves Dehogne

Partner, Financial & Actuarial Risk Advisory


Arno De Groote

Audit Director, IFRS expert


Carl Verhofstede

Director, Financial & Actuarial Risk

Advisory


Nicolas Castelein


Senior Manager, Financial & Actuarial Risk Advisory


Roeland Baeten

mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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