IFRS9 Implications and Challenges

IFRS9 Implications & Challenges

Sandip MukherjeeCofounder, Aptivaa March 2016

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The views expressed in the following material are the

author’s and do not necessarily represent the views of

the Global Association of Risk Professionals (GARP),

its Membership or its Management.

IFRS9 Implications & Challenges GARP – Istanbul Chapter Presenter: Sandip Mukherjee, Cofounder - Aptivaa 23rd March 2016

Private and Confidential

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q  About Us

q  IFRS-9 Guidelines: Key Requirements

q  IFRS-9 Vs. IRB Approach

q  Basel ECL Guidelines

q  Aptivaa’s IFRS-9 Approach

q  Q & A

Agenda

About Aptivaa

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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

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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

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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

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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

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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)

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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.

Fina

ncia

l Ass

ets

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

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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

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IFRS9 Principles

IAS39 Principles Classification &

Measurement


•  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)

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

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IFRS9 Principles

IAS39 Principles Classification &

Measurement


•  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)

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

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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

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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

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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)

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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

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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

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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

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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

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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

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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


§  Need to develop models to incorporate macro-economic variable for forward looking scenarios



§  Assumptions on effective maturity at portfolio or segment level

§  Need to make the maturity adjustment if Survival model is not used


§  Assumptions on lifetime maturity

§  Quantitative measures for loss forecasting by integrating macro-economic drivers


§  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

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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

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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

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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

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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)

§  Model construct, portfolio coverage, underlying data/assumptions & documentation §  Model Validation results or Audit comments (if any) §  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 §  Model Validation results or Audit comments (if any) §  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 §  Model construct, portfolio coverage, underlying data/assumptions & documentation §  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

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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.

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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

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Illustrative Functional Architecture & Data Model

Our Locations •  UAE

•  USA

•  UK

•  India

Also visit us at: Website: www.aptivaa.com : www.linkedin.com/company/aptivaa

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Economy & Finance

IFRS9 Implications and Challenges