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IFRS9 Implications & Challenges

GARP – Istanbul Chapter

Presenter:

Sandip Mukherjee, Cofounder - Aptivaa

23rd March 2016

Private and Confidential

2

About Us

IFRS-9 Guidelines: Key Requirements

IFRS-9 Vs. IRB Approach

Basel ECL Guidelines

Aptivaa’s IFRS-9 Approach

Q & A

Agenda

About Aptivaa

4

About Us

Brief Background | Journey so far

Consulting

Services

Analytics

Data and

Technology

2005 - Aptivaa

Launched as a

focused Risk

Consulting firm

2008 – CNBC Award

for Emerging India

2016 – Global

presence with offices

in UAE, USA, UK &

India

- Proven credentials having worked with over 100 financial institutions

- Global Presence with offices in UAE, USA, UK & India

- Emerging India first runner up in CNBC-TV18 in 2008

- Cutting Edge IP in Risk Management, Analytics & Reporting

- 100+ institutions as clients across over 20 countries

- Thought Leadership in the Risk Management industry

4

5

Breadth of Our Offerings

Core Risk

Management

Services Offerings

Consulting

Analytics

Technology

Implementation

Support

Credit Risk

Management

Market Risk

Management

Operational Risk

Management

ALM, Liquidity Risk

and FTP

Basel, IFRS 9,

COSO compliance

Credit Risk Models (PD,

LGD, EAD, IFRS 9)

Market Risk (Risk and

Pricing) and CVA

Models

ICAAP and Stress

Testing

Economic Capital, EVA,

RAROC

Operational Risk AMA

Data Governance and

Management

Risk Aggregation and

Reporting (BCBS 239)

Tactical Solution

Development and

Implementation

End-to-end System

Implementation (Third

Party Solutions)

Development of

Functional & Technical

Architecture

Use of statistical

analysis to

arrive at

solutions

Functional (Banking Specific) support to

other areas as well as aspects such as

governance, policies, regulatory

compliance, documentation etc.

Intermediate

Banking

solutions for

small to mid-

sized Banks

Resource

Augmentation

Introduction to IFRS 9

7

IFRS 9 Accounting Standards: An Introduction

IFRS-9 standards have been developed by IASB & FASB over the years after considering inputs from Banks, FIs,

groups such G20, Financial Crisis Advisory Group

Mandatory Compliance Deadline January 1, 2018 > Need to Start Now

The new standards

have replaced rule-

based standards of IAS

39 and aims to closely

align with risk

management, as such

management will apply

considerable judgment

in implementing the

changes to IFRS

IFRS 9 introduces new

classification category

(FVOCI) for debt

instruments. Also,

incurred loss model of

IAS 39 is replaced with

forward looking Expected

credit loss model.

Impairment losses will be

recognized sooner than

under IAS 39

Various support groups

being created to handle

interpretational

challenges:

ITG Meetings

Local Supervisor

Local banking

associations

CFO/CRO/Audit

Groups

Principle Based Approach instead of Rule Based

Inclusion of new accounting rules & Introduction of New Expected Credit Loss Model

Support Groups

IFRS-9 is mandated for

institutions from annual

periods on or after

January 1, 2018.

Considering the

complexity of changes in

systems & processes &

data requirement, Banks

would require minimum

of 2 years for

implementation & Dry

run to ensure the

readiness for 2018

IFRS: International Financial Reporting Standard

IASB: International Accounting Standards Board FASB: Financial Accounting Standards Board

IAS: International Accounting Standards

8

IFRS9 Implications / Challenges

IFRS9 has the following major implications on the Banking, Insurance & Financial Services industry:

Classification

& Measurement

Impairment

Hedge

Accounting

Business Strategy

• Business Models and plan

redesign

• Product restructuring

• Pricing strategy

• Capital & Dividend plans

Industry Challenges

• Heavy burden for smaller

institutions

• Regulatory Uncertainty

• High or Low Quality Adoption

• Dual provisioning framework in

some countries

Comparability & Consistency

• Principal based guidelines

• Interpretational Issues

• Practical Expedients / Simplifications

• Judgemental Overlay

• Disclosures are key to standardization

& quality

Financial Impact

• Provisions expected to significantly

increase on transition date

• Increased Volatility

• Increased Procyclicality

• Decline in shareholder’s equity &

Capital Ratios

Firm Challenges

• No market standard

• Data Unavailability

• Forward Looking view

• Significant increase in

credit risk

• Closer integration

between risk & finance

Skillset Building

• Core teams & senior

management skills to be

upgraded

• Regulator, Auditor, rating

agencies, investor & analyst

also need training

9

IFRS9 Categories: Developments over IAS39

IFRS9 Principles

IAS39 Principles

Classification & Measurement

• Introduction of new measurement category ‘Fair Value

through other comprehensive Income’ (FVOCI)

• Classification of instruments are now based on-

a) Entity’s Business Model

b) Contractual Cash flow characteristics

• 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)

10

Overview of Classification & Measurement

IFRS 9

The classification is based on both the entity’s business model for managing the financial

assets and the contractual cash flow characteristics of the financial asset

(i) Business Model Assessment

Based on the overall business, not instrument-by-

instrument

Entity’s business model determines whether financial assets

are –

a. Held to collect contractual cash flows

b. Both held to collect contractual cash flows and selling of

financial assets

c. FVTPL (not falling under the above two categories)

(ii) Contractual Cash Flow Assessment

Based on an instrument-by-instrument basis

Financial assets with cash flows that are solely payments of

principal and interest (SPPI) on the principal amount

outstanding.

Fin

an

cia

l A

ssets

Business Model SPPI Criterion

Hold Assets to collect cash

flows

Are the assets contractual cash flows

solely payments of principal & interest

Collecting cash flows &

selling financial assets

Amortized Cost

FVOCI

FVTPL

1

2 Are the assets contractual cash flows

solely payments of principal & interest

Yes

Yes

Yes

Yes

No

No

Neither 1 nor 2

11

Intention

Intention

Illustrative classification under IFRS 9 vis-a-vis IAS 39

Held to Maturity

Dated securities - Sovereign

and corporate bonds

Hold to collect

business model

Amortized cost

Generally, these securities

would satisfies SPPI test

Available for sale

Equities and preferred stock

Discounted securities,

corporate bonds,

Hold to collect and

sale business model

Fair value through other

comprehensive income

(FVOCI)

Loans and advances

Plain vanilla loans except for

loans held for sale

Fair value through profit or

loss

Equity securities

Dated bonds

Securitized instruments

Loans held for sale

FVPL business

model FVPL

Diagram below represents illustrative classification under IAS 39 vis-à-vis IFRS 9 and is based on assumption that the

intent of management will not significantly change under IFRS 9

Classification is subject to satisfaction of SPPI test and business model of the bank

Intention

12


IFRS9 Principles

IAS39 Principles Classification &

Measurement









Hedge Accounting

• Introduction of new hedge accounting model

• Closer alignment of accounting for hedge instruments with

risk management

• Broader scope for accommodating entity’s risk management

strategy and the rationale for hedging on the financial

statements

13


IFRS9 Principles

IAS39 Principles Classification &

Measurement









Hedge Accounting

• Introduction of new hedge accounting model

• Closer alignment of accounting for hedge instruments with

risk management

• Broader scope for accommodating entity’s risk management

strategy and the rationale for hedging on the financial

statements

Impairment

• IFRS 9 replaces IAS 39 Incurred Loss Model with new

Expected Credit Loss (ECL) model

• ECL model is applicable for instruments classified under

Amortized Cost and FVOCI category (only for Debt)

• Need to incorporate forward-looking information (macro

economic factors) for estimation of expected credit loss

• 3-Stage model for portfolio quality assessment & ECL

estimation

14

IFRS9 ECL Framework

IAS 39 – Incurred Loss Model

Credit losses are recognized only on the

occurrence of a loss event

IFRS 9 – forward-looking expected credit

loss model

Recognizes 12-month loss allowance at initial

recognition, and lifetime loss allowance on

significant increase in credit risk

Performing

Assets

Watch-List

Assets Non-Performing

Assets

Object evidence

of impairment

Significant increase in credit risk

(PD) since initial recognition

12-month Expected

Credit Loss Lifetime Expected Credit Loss

Gross Carrying Amount Net Carrying

Amount

Impairment

Recognition of Interest

General / Collective Provisions Specific Provisions

Stage 1 Stage 2 Stage 3*

* Stage 3 impairment calculation is status quo with IAS 39 methodology

15

Identification of indicators for increase in credit risk i.e. movement of an asset to Stage 2 from Stage 1, for calculation of

lifetime expected loss is a key challenge:

Credit Deterioration Triggers

Change in internal credit spread (or risk premium) 1

CDS spread, equity or debt price 3

Actual or expected change in Internal Credit

Rating or Behavioral Score 5

Actual or expected significant change in operating

results of borrower 7

Regulatory, economic, or technological

environment of the borrower 9

Quality of guarantee 11

Expected change in loan documentation (covenant

waiver, collateral top-up, payment holiday etc.) 13

Changes in bank’s credit management approach

(or appetite) in relation to the financial instrument 15

Significant difference in rates or terms of newly

issued similar contracts 2

Actual or expected change in External Credit

Rating 4

Existing or forecast adverse changes in business,

financial or economic conditions 6

Significant increase in credit risk on other financial

instruments of the same borrower 8

Collateral value 10

Reductions in financial support from parent entity

or credit enhancement quality 12

Significant changes in the expected performance

and behavior of borrower or group 14

30-dpd rebuttable presumption 16

16

Expected Credit Loss (ECL)

ECL is an unbiased and probability-weighted amount that is determined by evaluating a range of possible outcomes

The purpose of estimating expected credit losses is neither to estimate a worst-case scenario nor to estimate the best-case

scenario. Instead, it shall always reflect the possibility that a credit loss occurs and the possibility that no credit loss occurs

even if the most likely outcome is no credit loss.

When making the assessment, an entity shall use the change in the risk of a default occurring over the expected life of the

financial instrument instead of the change in the amount of expected credit losses.

Practical Expedients:

An entity may assume that the credit risk on a financial instrument has not increased significantly since initial

recognition if the financial instrument is determined to have low credit risk at the reporting date

Consider the reasonable and supportable information that is available without undue cost or effort at the reporting date

about past events, current conditions and forecasts of future economic conditions.

30 days past due rebuttable presumption

Use of provision matrix to estimate ECL for trade receivables

The discount rate to be used for the measurement of expected credit losses i.e. Effective Interest Rate (EIR) should be

the same as the rate used for the purpose of interest revenue recognition

Lifetime Expected Credit Loss or Significant increase in Credit Risk is a relative concept (from risk pricing perspective)

17

Lifetime ECL

EAD and LGD estimates could also vary based on different time points. For an example, an amortized loan (mortgage

loan) as on 2015, will have lower LGD in 2017 compared to 2016 as the LTV will decrease (for simplicity assuming a

single factor (LTV) based LGD model). EAD will also be lower in 2017 as compared to 2016.

1-PD1

PD1

1-PD2

PD2

1-PDN

PDN

Maturity

Discounting EL1

at T=0

Homogeneous pool of

customers

EL1 = PD1 * LGD1 * EAD1

EL2 = (1- PD1) * PD2 * LGD2 * EAD2

ELN = (1- PD1) * (1- PD2)...* (1- PDN-1)* PDN * LGDN * EADN

T=0

Discounting EL2

at T=0

Discounting ELN

at T=0

PD Term Structure is key to estimation of Lifetime Expected Credit Loss (LECL)

An illustration is given below for LECL computation:

Where EIR = Effective

Interest Rate

18

Differences between Basel - IRB and IFRS 9

Basel – IRB Approach IFRS 9 Theme

Model Coverage

(Partial Use)

Regulators allow exclusion of certain

portfolio outside the treatment of IRB

and can be under standardized

approach

IFRS 9 doesn’t permit partial use of

impairment models on the

instruments which are identified under

the scope

PD Calibration

Estimates of PD represent probability

of default over a 12 month horizon

PDs are calculated on the basis of

historical long-run average (TTC)

Multi-period estimation is necessary

(for stage -1, 2 & 3)

IFRS 9 requires Point in Time

estimates (PiT), with inclusion of

macro-economic factors

Loss Given Default

(LGD)

Under FIRB supervisory LGDs are

permitted to use, however under

AIRB Downturn LGD estimation is

required

IFRS 9 doesn’t provides complete

clarity on LGD calculations.

Regulatory LGDs can be the basis or

Long run avg. /point in time LGDs

estimates.

Excepted Credit Loss

(ECL)

The Basel framework expected credit

loss model looks through-the-cycle

logic

IFRS 9 framework expected credit

loss model looks more point-in-time

logic to arrive at Lifetime Expected

Credit Loss

19

Concept of Defaults and Predictions

PIT PD

Estimates of PIT PD represent

probability of default over a future

horizon (typically 12 month) using

statistical methods using recent

historical data. Probability of Default of

a borrower under PIT Framework will

fluctuate in line with economic cycle.

TTC PD:

TTC PD is calculated on the basis of

historical long-run average historical

default. Borrower TTC PD will not

change due to economic conditions

as long run average includes

economic downturn effects.

12 Month Prediction:

The PD model predicts default within

the next 12 months. The 12 month

horizon prediction is generally used

for BASEL capital calculation or EL

calculation.

Lifetime Prediction:

Lifetime PD estimates cumulative

probability of default over the life of a

exposure . The prediction can be

done either by using PIT PD or TTC

PD framework. For IFRS 9, the

lifetime PD should be calculated

based on PIT PD.

1st year 2nd year 3rd year

PD

(%)

PD Term Structure

20

Macroeconomic effect on PD

Z Score

Building relationship

using statistical

methodologies to

predict Z Score

Macroeconomic factors

GDP

Employment Indicator

Inflation

Interest Rate

Stock Index

Exchange Rate

(Change in Default Rates)_t = 0.0119 -

0.00142 * (Stock Index)_t-1 * - 0.00114

*(GDP)_t-1 - 0.000211 *(Employment

Indicator)_t-1 - 0.000152 *(Inflation)_t-1

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

1 2+ 2 2- 3+ 3 3- 4+ 4 4- 5+ 5 5- 6+ 6 6- 7+ 7 7-

PD Calibration - Normal Vs Stressed Case

Normal PD

Stressed PD

According to IFRS9, the PD should be forward looking i.e. the PD should be predicted using past event, current

conditions and future outcomes.

Relevant macroeconomic factors like GDP, stock index, oil price etc. could be used to forecast the PD Term Structure.

1

2 2

1

21

PD Term Structure Methodologies

BBB

AAA

AA

A

BBB

D

1st year

AAA

AA

A

BBB

D

2nd year

1st

year

2nd

year

3rd

year

PD

(%) PD Term Structure

Binomial Movement Approach:

Binomial movement approach assumes that the borrower will

either default or will remain in its current credit quality. This

approach assumes no transition in credit quality. The PD Term

Structure under this approach is developed based on 1 year PD

rate.

Credit Deterioration Approach:

Under this approach, it is assumed that in addition to default,

borrower also has probability of moving to other credit rating

grades (typically represented in the form of Transition Matrix).

PD Term structure under this approach is developed through

transition matrix multiplication.

BASEL Maturity adjustment Approach:

Basel III capital calculation formula (ASRF) uses a maturity

adjustment formula to convert 12 month PD to Lifetime PD

based on maturity of the exposure.

Multi year Transition Matrix Approach

Under this approach, Banks needs to develop Transition Matrices for multiple years ( 1,2,3…). PD Term Strcuture can be

developed directly by taking PD from these multi year Transition Matrices.

1

2

3

4

𝑀𝑎𝑡𝑢𝑟𝑖𝑡𝑦 𝐴𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡 =1 + 𝑀 − 2.5 ∗ 𝑏(𝑃𝐷)

1 − 1.5 ∗ (𝑏(𝑃𝐷)

Where , b(PD) = (0.11852-0.05478*log(PD))^2

N

PD in next 3 years =

PD1 + (1- PD1) * PD1 + (1- PD1)

* (1- PD1) * PD1

One Year average PD

22

Impairment Methodologies

Roll Rate Models Vintage Loss Models Provision Matrix Model Expected Loss Model Discount Cash flow Method

Model Characteristics

Segments are created based on

Delinquency or PD bands

Determines flow of instruments or

loss across Transition Matrix

May be augmented with vendor

data

Relatively robust and transparent

Predicts loss rate account

migration and recovery analysis

Frequently used for short-term

loss forecasting

Losses are estimated using

multistep process

Separates estimation of

vintage effect, economic effect

and maturation effect

Tend to use primarily for

consumer portfolios

Used for Long term loss

forecasting

Based on historical data and

judgment

Done at a homogenous

segment level

Directly predicts loss ratio or

loss amount

Typically used for the short

term trade receivables

Predict default probability or

loss severity by using loan

specific characteristics and

macroeconomic inputs

Often used to calibrate vendor

models

Much more complex modeling

concepts

Much more data intensive

Use of Survival model to

predict Time to default

Individual assessment of

instruments

Required business and

individual customer level

knowledge

Future cash flows are

discounted by the

EIR(effective interest rate)

IFRS 9 prerequisites

Longer Time Series data required

Assumptions on pre-prepayment

patterns

Linking roll rate rates with macro-

economic drivers to incorporate

forward looking scenarios in the

loss estimates

Separate estimation of Lifetime

PD

Assumptions on effective maturity

at portfolio or segment level

Longer Time Series data

required

Assumptions on pre-

prepayment patterns

Separate estimation of

Lifetime PD

Need to develop models to

incorporate macro-economic

variable for forward looking

scenarios

Assumptions on pre-

prepayment patterns

Separate estimation of

Lifetime PD

Assumptions on effective

maturity at portfolio or

segment level

Need to make the maturity

adjustment if Survival model is

not used

Assumptions on pre-

prepayment patterns

Assumptions on lifetime

maturity

Quantitative measures for

loss forecasting by

integrating macro-

economic drivers

Assumptions on pre-

prepayment patterns

Assumptions on lifetime

maturity

Limitations

Does not consider loan specific

information

Heavy assumptions for long term

estimations

Does not consider loan

specific information

Does not consider loan

specific information

Heavy on assumptions

Heavy on data requirements Difficult to implement for

large number of

instruments in the banking

book

Portfolio Suitability

Retail Assets Retail Assets Trade Receivables, Contract

assets

Corporate and Retail Corporate

23

BCBS Guidance (d350) on ECL

Supervisory expectations regarding sound credit risk practices associated with implementing and

applying an ECL accounting framework (8 principles for banks & 3 for regulators)

BCBS has significantly heightened supervisory expectations of the high quality, robust &

consistent application of IASB standards at internationally active and sophisticated banks.

Stress on ‘periodical supervisory prudential review’ of the methodologies adopted by various

banks for ECL estimation.

BCBS has not provided any exemption bucket for compliance to accounting standards, and

therefore, all the lending exposures should be considered for ECL estimation.

BCBS has recognized that supervisors across jurisdictions may adopt a proportionate approach

with regard to the guidelines issued to banks of different scale and complexities.

BCBS has explicated that due consideration should be given to the principle of materiality, and

should not be assessed only on the basis of the potential impact on the P&L statement at the

reporting date.

BCBS expects that banks should have robust policies and procedures in place for validation of

models, thus maintaining its rigor stance for model governance framework, consistent with the

requirements for Basel II IRB purposes.

Information Set: BCBS expects banks to develop systems and processes that use all reasonable and supportable information that is

relevant to the group or individual exposure, as needed to achieve a high-quality, robust and consistent implementation of the approach.

This will potentially require costly upfront investments in new systems and processes but the Committee considers that the long-term

benefit of a high-quality implementation far outweighs the associated costs, which should therefore not be considered undue.

Low credit risk: IFRS 9 introduces an exception to the general model in that, for “low credit risk” exposures, entities have an option not to

assess whether credit risk has increased significantly since initial recognition….In the Committee’s judgment use of this exemption by

banks would reflect a low-quality implementation of the ECL model in IFRS 9.

30dpd rule for stage 2: BCBS would view significant reliance on past-due information (such as using the more-than-30-days-past-due

rebuttable presumption as a primary indicator of transfer to LEL) as a very low-quality implementation of an ECL model.

Aptivaa’s Approach & Methodology

25

Overview of Our Approach for IFRS 9 Compliance

Training

Change Management

Program

Organizational

Structure Review

Audit & Regulator

Feedback

WS 1: Gap,

Impact &

Design

WS 2:

Specification and

Implementation

WS 3: Parallel run

& Business

Transition

1

2

3

Process & Policy

Development

Development of

Impairment Models Data & Systems Allied Areas

Governance &

Policy Overview

Review of Impairment

models

Review of Data

Architecture & Systems Impact Assessment Allied areas

• Assessment of

existing credit risk &

stress testing models

• Develop Concept

Notes for key ECL

areas

• Assessment of Data

availability for

Impairment

calculations

• Changes required in

existing IT systems

• Assess the impact of

provisions on bank

capital

• Assess the need of

required skill-set,

staffing and trainings

• Impact assessment

on core areas of

ICAAP

• Impact on pricing

(RAROC)

• Credit Risk,

Accounting, Model

Management, and

Hedging policies and

procedures

• Documentation of rules

for Asset Classification

• Updating accounting,

provisioning, credit risk,

hedging policy and

disclosures

• Validation & recalibration

of existing models

• Identification of credit

deterioration triggers

• Lifetime ECL estimation

• Data & system gap

resolution strategy

• Data Flow architecture

• Functional DataMart for

disclosures & reporting

• Updating policies

related to credit risk

strategy, ICAAP report

• Updated reporting

frameworks

Parallel Run

26

Impairment Models: Portfolio Coverage & Model Inventory

High level review of portfolio coverage & IFRS9 suitability of credit risk models (PD, LGD & EAD), credit monitoring and stress

testing models need to be performed

Portfolio Coverage & Model Inventory

Basel allows partial use of IRB i.e. exclusion of certain portfolio outside the treatment of IRB Approach due to lack of

internal models and the way out is to continue using standardized approach for them. However IFRS9 doesn’t permit

partial use of impairment models on the instruments which are identified under the scope and a bank is required to

produce risk estimates for all portfolios whether on individual or collective basis.

Prepare an inventory of all existing models relevant to IFRS9 ECL framework such as credit rating models, credit risk

scorecards, LGD, EAD, prepayment behavioral models, credit monitoring / early warning models, and macroeconomic

stress testing models etc.

All the relevant model documents, dataset and prior validation reports (if any) need to be collected for further

assessment.

Portfolio

Segment

Model Coverage

Rating /

Scoring LGD EAD

Stress

Testing

Monitoring/Early

Warning Prepayment

Bank No No No No No No

Corporate Yes No No Yes No No

SME Yes No No Yes Yes No

Auto Loan Yes Yes No Yes No No

Home Loan Yes Yes No Yes No Yes

Credit Cards Yes Yes Yes Yes Yes No

Personal Loans Yes Yes No Yes Yes No

27

Impairment Models: IFRS9 Suitability Assessment

Suitability Assessment Criteria Impairment Models

Credit Risk Rating

or Scoring Models

Model construct, portfolio coverage, underlying data/assumptions & documentation

Model Validation results or Audit comments (if any)

Rating and Calibration Philosophy (PIT / TTC / Hybrid)

Presence of behavioral or forward looking factors (if any)

Loss Given Default

(LGD)



Discount factor used to calculate present value of recoveries and expenses

Calibration Philosophy (PIT, Average or Downturn LGD)

Availability of external recovery/LGD data and its suitability for benchmarking

Exposure at

Default (EAD)

CCF Model construct, portfolio coverage, underlying data/assumptions & documentation


Prepayment or behavioral maturity modeling (if any)

Stress Testing

Macroeconomic forecasts and availability/role of Economist (if any) at the Bank

Stress Testing models for forward looking impact on Ratings, PD, LGD, EAD etc.

Models establishing linkage between macroeconomic factors to bank specific risk factors

and their suitability for scenario generation and Lifetime PD forecasting


Forward looking assessment (horizon, sophistication, suitability for IFRS9)

Stage Assessment

Indicators or criteria used for credit monitoring or early warning frameworks

Definition of default, 30 dpd rule (cure rate data availability),

Credit Rating process (upgrade/downgrade), behavioral scorecards (if any)

Availability of initial rating or PDs

28

IFRS9 Architecture – Go Strategic or Tactical ?

With regards to IFRS9 compliance strategic roadmap, the key decision that bothers banks is

whether the software architecture should be of a strategic integrated nature or one that is

decoupled and modular ?

We propose to follow our 4Rs framework while trying to figure out whether a strategic, integrated

solution is needed or a more tactical but modular solution:

Readiness – How ‘ready’ are you with the expected credit loss computation methodologies? If you are not yet ready or

believe methodologies are likely to evolve over time, then a modular approach may work best.

Reflectiveness - User access and control is as much an important criteria as is automation. During this compliance

exercise, in the initial stages, data availability for estimation of various risk components will be an issue. Banks will be

required to check the data inputs and outputs for each of the underlying models used in the ECL computation so that

validation, error resolution and judgemental overrides (based on management decision) could be performed at each level

of ECL computation. There should be an ability to deliberate and ‘reflect’ upon various intermediate outputs.

Redundancy - Are you already struggling to maintain a plethora of solutions that seemingly do very similar tasks?

Yes, Redundancy is another major factor to be considered. Banks should look to leverage existing infrastructure like

Basel II IRB infrastructure instead of creating another parallel infrastructure for IFRS9.

Regularity - Are you looking to (re)generate ECL computation results on a daily basis? If the answer to the question is

Yes, then indeed a fully integrated strategic solution is needed. However, in our experience, the frequency or regularity of

usage is quarterly or maybe monthly at most. In such circumstances, traditionally, tactical modular architecture based

solutions work better. Level of automation required for data feeds (Manual data upload or ETLs) should be based on

cost-benefit analysis.

Organise stakeholder workshops to discuss key issues, pros/cons of both approaches in context of existing

infrastructure and IFRS9 compliance timelines.

Develop an ideal IFRS9 Architecture along with strategy for database and level of automation required at various

levels.

29

Illustrative Data Flow Architecture –

Multiple sources increases computational complexity

Source Systems

Input Data Feed

Sources

A B C D E

Documentation

F

Core Banking/

Trade Finance

Treasury &

Finance CIF/ CRM

Models

Database Recoveries Contracts

A

B

C

F

Collateral

Information

PiT& Lifetime PD

12-months

PiT PD

D

Macroeconomic

Adjustment

Stage 2 & 3 Stage 1

A

B

C

F

A

C

A

Business Model

identification

Cash flow

characteristics test

Classification

Rating Models

LGD

Contractual

Maturity

Expected

Maturity

Calculator

Macro Economic

Variable Analysis Reporting

Tool

Financial

statements

IFRS 9

Disclosures Reconciliation

Provisioning

IAS 39 Provisions

Amortized

Cost

FVOCI

FVTPL

Regulatory

Provisions

Credit Deterioration

Assessment Framework

Practical expedients

(More than 30 days

past due, etc.)

Stage

Assessment

Management

Judgment

Loss Calculator

EAD Calculator

Prepayment

Lifetime PD

1

2

7

5

3

4

8

9

E

Behavior

6

EIR

30

Illustrative Functional Architecture & Data Model

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• UAE

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Also visit us at:

Website: www.aptivaa.com

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http://www.aptivaa.com/

http://www.linkedin.com/company/aptivaa

http://www.linkedin.com/company/aptivaa

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