changes in basel operational risk framework

Changes in Basel Operational Risk Framework

March 26, 2016

Arpit Mehta

https://www.linkedin.com/in/arpitpmehta

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Table of Contents

Background ............................................................................................................................................. 3

Reasons for changes in the existing framework ...................................................................................... 4

1. Weakness of Gross Income (GI) and loans and advances (L&A) as a proxy indicator for

operational risk exposure .................................................................................................................... 4

2. Review of Operational Risk Framework (ORF) was due ........................................................... 4

3. Reducing Model Complexity ...................................................................................................... 4

4. Promoting comparability of risk-based capital measures ........................................................... 4

Key Changes in the existing framework ................................................................................................. 5

1. New proxy indicator for operational risk exposure ..................................................................... 5

2. Different calibration for regulatory coefficients ......................................................................... 7

3. Internal Loss Multiplier .............................................................................................................. 8

4. Computing Minimum Capital Requirements for Operational Risk ............................................ 9

5. Adopting Risk Management Principles Entry level capital methodology .................................. 9

Key Impacts of SMA .............................................................................................................................. 9

1. Computation made simpler ......................................................................................................... 9

2. More Focus on Data .................................................................................................................... 9

3. Reduced Subjectivity ................................................................................................................ 10

4. Resource Optimization .............................................................................................................. 10

5. Validation Requirements........................................................................................................... 10

6. Implementation Timeline .......................................................................................................... 10

7. Road Ahead ............................................................................................................................... 10

Background

In March 2016, Basel Committee on Banking Supervision (BCBS)

that propose an alternate approach to the existing

Approach (BIA), The Standardized Approach (TSA), Alternate Standardized Approach

(ASA) and advanced approach

risk capital computation. BCBS has named the alternate approach as Standardized

Measurement Approach (SMA).

version** and recommends replacing the existing approaches for operational risk capital

computation by a simpler SMA approach.

The existing Basel framework provides four approaches for computation of operational risk

capital. The simplest is BIA where capital is calculated as percentage (alpha

coefficient) of Gross Income (a proxy indicator of operational risk expos

most advanced methodology is AMA, which allows banks to use internal models to compute

capital charge. An intermediate approach between BIA and AMA is TSA, where Gross

Income (GI) is divided into 8 business lines and capital is comput

of GI for each business line and a regulatory coefficient (beta) for that business line. Another

intermediate approach between BIA and AMA is ASA which is a variant for TSA. Banks

with high interest margins are allowed to compute

GI for two business lines (retail banking and commercial banking) with a fixed percentage of

their loans and advances. BIA being the most basic approach does not require prior

supervisory approval. TSA, ASA and

June 2004

Set out the framework for approaches to compute operational risk capital charge (BIA, TSA, ASA and AMA)

June 2011

Provided supervisory guildenines on data and modelling for AMA

In March 2016, Basel Committee on Banking Supervision (BCBS) issued consultative paper*

an alternate approach to the existing simpler approaches

), The Standardized Approach (TSA), Alternate Standardized Approach

approach - Advanced Measurement Approach (AMA

BCBS has named the alternate approach as Standardized

Measurement Approach (SMA). This consultative paper is build upon its October 2014


er SMA approach.


capital. The simplest is BIA where capital is calculated as percentage (alpha

coefficient) of Gross Income (a proxy indicator of operational risk exposure of the bank).



Income (GI) is divided into 8 business lines and capital is computed as a sum of the product



with high interest margins are allowed to compute their operational risk capital by replacing



supervisory approval. TSA, ASA and AMA require prior supervisory approval for adoption.

Set out the framework for approaches to compute operational risk capital charge (BIA, TSA, ASA and AMA)

Provided supervisory

Oct 2014

Introduced Revised Standardized Approach which aimed to simplify BIA, TSA and ASA

March 2016

Issued a consultative paper on SMA approach which replaces BIA, TSA, ASA and AMA. Built on Oct 2014 consultative paper.

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consultative paper*

simpler approaches – Basic Indicator

), The Standardized Approach (TSA), Alternate Standardized Approach

AMA) for operational

BCBS has named the alternate approach as Standardized

This consultative paper is build upon its October 2014



capital. The simplest is BIA where capital is calculated as percentage (alpha – a regulatory

ure of the bank). The



ed as a sum of the product



their operational risk capital by replacing



prior supervisory approval for adoption.

Issued a consultative paper on SMA approach which replaces BIA, TSA, ASA and AMA. Built on Oct 2014 consultative

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Reasons for changes in the existing framework

1. Weakness of Gross Income (GI) and loans and advances (L&A) as a proxy indicator

for operational risk exposure

Existing simpler approaches assumes that bank’s operational risk exposure increases linearly

in proportion to gross income/loans and advances/size. It was observed in the wake of

financial crisis starting 2008-09 that when a bank experiences decline in GI/size due to a

systemic or bank-specific events, its required capital for operational risk falls at a time when

it should be increasing. Also it is observed that operational risk exposure of a bank increases

non-linearly with size.

2. Review of Operational Risk Framework (ORF) was due

When BCBS recommended simpler approaches in 2004 and higher approach in 2006, it had

limited data on operational loss. Review of the framework was due with almost a decade long

experience of the BCBS in supervising ORF and availability of data.

3. Reducing Model Complexity

SMA is a single non-model based method for estimation of operational risk capital. This,

BCBS believes, reduces model complexities and assumptions of distributions fit for

frequency and severity of operational loss data used in AMA approach. Building loss

distribution approach (LDA) based internal models was a cumbersome exercise for the bank

and it was proven to be resource intensive.

4. Promoting comparability of risk-based capital measures

Introduced in 2006, AMA approach estimates regulatory capital required for operational risk

based on a diverse range of internal modelling practices subject to supervisory approval.

Wide range of internal modelling practice and failure of BCBS to narrow done flexibility in

AMA approach has led to lack of comparability and increased variability in risk-weighted

assets (RWA) calculations.

* https://www.bis.org/bcbs/publ/d355.pdf dated March 2016

** http://www.bis.org/publ/bcbs291.pdf dated October 2014

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Key Changes in the existing framework

1. New proxy indicator for operational risk exposure

Existing simpler approaches uses financial statement based proxies for operational risk such

as gross income, loans and advances. These indicators are either cyclical in nature or are

affected by accounting practices of the bank. Moreover, it is observed that operational risk

exposure of a bank does not increase linearly with indicators based on financial statements.

After analyzing 20 different indicators, BCBS has proposed Business Indicator (BI) as a

superior proxy to capture a bank’s exposure to operational risk. BI comprises of three

components 1) Interest, Lease and Dividend (IL&D) Component 2) Services Component and

3) Financial Component. To compute the BI for year t, a bank must determine the three-year

average of the BI, as the sum of the three-year average of its components. �� = ��& �� + �� + �� Where ��& �� = �� − �� !"��#,0.035 ∗ �� !��* +��, + �� − �� !"��# + ��-��- �� = �"�.�ℎ�� .��* �� , .�ℎ�� .��* !"��,+ �" 0 ��1�� − �� !"��2,

�� 3 �"�� , �� !"��# ,�0.45 ∗ ��567895:;<8,��# + �0.1 × �"�� , �� !"��# # ?@ Where ��567895:;<8,��= ��& �� + �"�.�ℎ�� .��* �� , .�ℎ�� .��* !"��, + �"�� , �� !"��# + �� =�� A�� B&� �� -��* ��C��# + �� A�� B&� �� C��* ��C��#

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The following are major differences between BI and GI: -

• BI includes items that are sensitive to operational risk which are ignored or netted from GI

(e.g. P&L from the banking book, other operating expenses, fee and commission

expenses)

• BI uses absolute value of its components in order to avoid counterintuitive results based

on negative contributions of components to capital charges in the existing framework (e.g.

negative contributions to the capital charge from net trading losses)

• BI introduces weights to the components of capital charge based on its sensitivity to

operational risk (e.g. gains and losses on traded or sold portfolios, commissions from

services payments, fees received from securitisation of loans and origination and

negotiation of asset-backed securities, penalties from mis-selling and inadequate market

practice)

BI

Component

Gross Income Business Indictor

(2014 consultative paper)

Business Indictor

(2016 consultative paper)

Interest,

Lease and

Dividend

(IL&D)

Component

�� − �� !"��)

absolute EInterest Income - Interest Expense

F min Gabsolute EInterest Income -

Interest ExpenseF ,

0.035*Interest Earning Assets

H

+ absolute ELease Income - Lease Expense

F

+ Dividend Income

Services

Component

�� − �� !"��+ .�ℎ�� .��* ��

Fee Income + Fee Expense

+ Other Operating Income

+ Other Operating Expense

Max(Fee Income, Fee Expense)

+ Max (Other Operating Income,

Other Operating Expense)

*Adjusted for high-fee banks

Financial

Component

Net P&L on

trading book

absolute E Net PL on

trading bookF

+absolute E Net PL on

banking bookF

absolute E Net PL on

trading bookF

+absolute E Net PL on

banking bookF

Other Dividend Income Not included Dividend income included in interest

amount.

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There were a few concerns raised as a response to the BCBS October 2014 consultative paper

on revised standardized approach. These concerns were addressed in March 2016

consultative paper. Few of those changes are as below: -

BI Component Concerns raised as a

response of October 2015

paper

Proposed changes made in

March 2016 paper

Interest, Lease and Dividend

(IL&D) Component

Treatment of dividend

income is inconsistent across

jurisdictions. Some banks

include dividend income

within the interest component

Dividend income included in

interest amount.

Interest, Lease and Dividend

(IL&D) Component

Credit finance, financial

leases or operating leases

face similar operational risks,

therefore should be treated

similarly

To ensure consistency across

banks and jurisdictions, all

financial and operating lease

income and expenses are

netted and then included in

absolute value into the

interest component

Services Component Asymmetric impact on the

‘distribute only’ and the

‘originate to distribute’

business models

Formula changed from sum

to maximum

Services Component Banks with a high fee

component has very high BI

values, resulting in high

regulatory capital

Formula changed – Banks

with high fee component is

accounted for only 10% fees

in excess of 50% of

unadjusted BI

2. Different calibration for regulatory coefficients

Under BIA, regulatory coefficient (alpha) is stipulated to be 15% which is multiplied with GI

to arrive at required capital charge. Under TSA, GI is distributed business line wise which is

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then multiplied by regulatory coefficient (beta) of each business line. Values of beta range

vary between 12%, 15% and 18% depending on the business line.

Since it was observed that operational risk varies non-linearly in proportion to the size, BCBS

has recommended five-bucket structure with values for coefficients increasing from 10% to

30% with rise in the value for BI. The proposed coefficients per bucket under SMA are as

below. A layered approach is to be adopted where the coefficient for a given bucket will be

applied on a marginal basis to the incremental BI falling under that bucket.

Bucket BI Range BI Coefficient (in %) BI Component

1 €0 to €1 billion 11 0.11 * BI

2 €1 to €3 billion 15 €110 million

+ 0.15 * (BI – €1 billion)

3 €3 to €10 billion 19 €410 million

+ 0.19 * (BI – €3 billion)

4 €10 to €30 billion 23 €1.74 billion

+ 0.23 * (BI – €10 billion)

5 €30 billion to +∞ 29 €6.34 billion

+ 0.29 * (BI – €30 billion)

3. Internal Loss Multiplier

SMA is based on the assumption that operational risk should be same for two banks with

same business indicators (BI). However, since volumes may not be the only parameter

influencing operational risk exposure, banks with same levels of BI may face different

operational risk due to other factors such as different business models. In order to improve

the sensitivity of SMA to operational risk, BCBS recommends adjustment by internal loss.

�� I�� = ln E�L − 1 + �� F

Where

Loss Component = (7 * Average Total Annual Loss)

+ (7 * Average Total Annual Loss only including loss events above €10 million)

+ (5 * Average Total Annual Loss only including loss events above €100 million)

Banks is suggested to use minimum 5 years and upto 10 years of good-quality loss data to

calculate average total annual loss in loss component.

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4. Computing Minimum Capital Requirements for Operational Risk

BCBS recommends the following supervisory formula to compute minimum capital required

for operational risk under SMA approach MNO� = =

PQRQS �� ; �U ��C �� U�� C�� 1��

€ 110 �� + V�� − € 110 ��) × ln E�L − 1 + �� F ; �U ��C U�� C�� 2 �� 5X

Where,

BI Component and Loss Component is calculated as per formulae mentioned before

5. Adopting Risk Management Principles Entry level capital methodology

Unlike TSA/ASA/AMA which has explicit qualifying criteria to be met, SMA is to be an

‘entry level’ capital methodology; no prior supervisory approval is required to adopt SMA.

Supervisor is ought to be more rigorous in its Pillar-II supervisory review to ensure the

effectiveness of Pillar-I capital computed under SMA approach for operational risk.

Key Impacts of SMA

1. Computation made simpler

Under SMA, Banks are not required to spend its resources in cumbersome LDA modelling of

AMA. Computation is made fairly simpler to carry out.

2. More Focus on Data

While capital charge computation is made formula-based and much simpler, banks shall be

required to demonstrate ongoing identification of high-quality internal loss data to a much

detailed granularity.

SMA introduces Internal Loss Data as an additional component along with BI to calculate

capital charge. Focus of BCBS has been on industry average loss. A bank with higher or

lower loss than the industry average will have capital charge higher or lower than the BI

component respectively. Bank shall carry larger capital for historical high losses.

Operational risk capital charge will thus depend on size and internal loss experiences of the

banks. Two banks with same size with one bank having higher historical loss will be required

to keep aside more capital.

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3. Reduced Subjectivity

Opportunities for adjusting the capital charge amount by modelling choices are removed.

This will lead to reduction in subjectivity in tweaking models and/or data inputs which is

possible under AMA.

4. Resource Optimization

The reduction in investments in technology to model loss data distributions shall bring cost

savings. However, it is expected to use this savings to focus on identification, capturing and

management of high-quality internal loss.

5. Validation Requirements

As the focus shall be shifted to internal loss data and its high quality and integrity, there could

be certain validation requirements stipulated by the supervisors in the future

6. Implementation Timeline

As SMA approach is simpler to implement and there is no prior approval required from

supervisors to adopt SMA, once finalized, implementation timeline is expected to be

aggressive.

7. Road Ahead

BCBS has currently issues consultative paper on SMA approach which is available in public

domain for soliciting comments. The approach is likely to get modified based on the results

of the ongoing Quantitative Impact Studies and the three month comment period.

changes in basel operational risk framework

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