op risks in banks.ppt

8/14/2019 op risks in banks.ppt

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OPERATIONAL RISKMANAGEMENT

Banks experiencein building

a Basle II compliant


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Developing an Appropriate Risk Management

Structure

Board of Directors

Internal Auditors

Senior Mgt

Risk Management Committee

Risk Mgt

Operations Personnel and Risk Takers


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The Committee has proposed that the

Minimum Regulatory Capital (MRC) be

lowered from 20% of minimum regulatory

capital of 8% (i.e. 1.8% of the total risk

weighted assets) to 12% (ie 1.08% of the

total risk weighted assets).

With AMA implementation this can be brought down to

9% (0.72%).

THE KEY DRIVER


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Internal Causes

People

Processes

Systems

A Model Bank has adopted Basels definition ofOperational Risk ..

The risk of loss resulting from inadequate or failed

internal processes, people and systems or from

external events.

Definition

External Events


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BASLE II has prescribed Three approaches

for ORM :

Basic Approach

Standardised Approach

Advanced Management ApproachAMA

Banks in India generally adopt the AMA


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BASIC INDICATOR APPROACHBanks using Basic Indicator Approach(BIA) have to hold capitalfor operational Risk equal to a fixed percentage (alpha) of asingle indicator (Gross Income)

K = { EI * )/n

Where K = Capital charge under BIA EI = Annual Gross Income where positive , over the previous 3

years

= a fixed percentage set by the Basle committee

15% set by the committee Capital/IndicatorIndustrywise

N=Number of previous 3 years for which the Income ispositive

GI = NII

GI = Nprofit+( Provisions & Contingencies)+Op Expenses(SCH16)- Profit from HTM sale of InvestmentsIncome fromInsuranc+loss on sale of HTM investments


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STANDARDISED APPROACH

Banks activities are divided into 8 Business Lines.

Each Business Line is measured by an Exposure Indicatorwhich is Gross Income for that Business Line.

Within each Business Line the capital charge is calculated bymultiplying the said Business line Gross Income by a betafactor

The sum of all Business Line Capital charge would be theCapital charge for the Bank.

K = E (EI * )

K is capital charge

EI is Exposure IndicatorGross Income

is the a fixed percentage for each Business line set by theBasle Committee.


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ADVANCED MEASUREMENT

APPROACH (AMA)

The AMA gives banks incentive to collect internal loss data step

by step. Under the AMA banks would be allowed to use the

capital charge as per their internal measurement systems

subject to Qualitative & Quantitative standards set by the

Committee.

Among the most important of these quantitative standards is that

the risk measurement system must be based on internal loss

data that can be mapped into the Basle Committees specified

Business Lines and Loss Event Types.


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One of the most visible effects of implementingan advanced approach for operational riskmanagement is the positive impact on

reputation and perception by stakeholders Theuse of internal models to calculate capitalrequirements under the AMA may also lead toa reduction in regulatory and economic capital.

Capital is based on risk exposures and not onincome levels as is the case for the more basicapproaches.


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Organisation Structure

Board of Directors

Risk Management Committee

Operational Risk Group ALCOHead

Risk ManagementOperational Risk Credit Risk Market Risk


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Bank has developed a framework called ORBIT (OperationalRisk Business Intelligence Tool)for measuring, monitoring and

controlling Operational Risk, based on the guidelines set by

Basel.

The main features of the framework of Operational Risk

developed by IDBI Bank are as under:

KRI data gathering framework

Control Framework

Incident Reporting Structure (IRS)data gathering framework

VaR Engine

Query and reporting

Scenario analysis

Framework


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Key Risk Indicators (KRIs)are identified product wise.

Each KRI is linked to a product and each product to a

Business line.

Business lines are defined as per Basel guidelines.

For any new product introduced by the Bank , KRIs are

identified and gathered.

KRI - Data Gathering Framework


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KRI - Data Gathering Framework

(KRIs)framework pinpoints information from Core bankingsoftware for use in ORBIT

Most of the KRIs are gathered using an automated data upload

process by which specific KRI are sourced from various

applications of the Bank viz. Finacle, Net Bkg, Phone bkg,

ATM etc.. Additionally, there are some KRIs which are

sourced by means of manual feeds from branches / various

functions.

KRIs are gathered every month and stored in the KRI data

base from which Analysis of Ops data is done

kri
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comprises of :

Branch operations performance rating

Trigger reports module

ControlFramework


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KRIs are rated on a five grade scale:

Excellent / Good / Satisfactory / Fair / PoorRatings are done by attributing weightsto certain critical KRIs.

Rating parameters are classified into five categories & Weight assigned

to each category .

People management

Business management

Security management

Customer management

Compliance with internal policy

Operational quality of a branch is rated on a 5 grade scale:

Well managed / Low risk / Medium risk / High Risk / very High Risk.

Model

Control Framework - Branch Performance Rating
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This module consists of reports, which as the name

suggests, are triggered whenever certain events occur viz.

Brisk Triggers. A trigger report is generated for branches

which have scored poor in any of the parameters used inOps rating model for branch heads to take corrective action.

Report also goes to controlling authority concerned for

monitoring corrective action effectively.

Control Framework - Trigger Reports

S S


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An operational loss event is defined as one where the Bank

suffers either an actual loss or a potential loss.

Under the Advanced Measurement Approach, historical loss

data forms the basis of VaR. The loss data is captured using an

incident report framework. IRS is a loss incident gathering

framework.

An incident report is filed on the occurrence of an operational

loss event.

Loss event is categorised by Loss event category andBusiness line.

Event

IRS Structure
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VaR Model facilitates computation of Economic Capitalfor Operational Risk.

Idb i bankhas classified its business lines. Loss event

category and loss effect category as per the guidelines

of BASEL.

Under this approach idbi bankestimates the likely

distribution of operational loss over one year horizon,

for each business line and loss event type, at a

confidence level of 99.9%.

VaR Engine


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Methodology for VaR Computation-

Data collectioncapturing of Loss Data.

Curve Fittingapplying Statistical formulas on Loss Data.

Simulationapplying Monte Carlo Simulation

VaR Estimationreadingthe final value using a 99.9% Confidence Level.

Perform the same iterations for each Business Line, Event type

combinationVaR Estimate for the Bank is the sum of all VaR estimates for all

the Business Lines of the Bank.


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Reports

Query & Reporting

This module generates queries/reports branch-wise,

region wise and product wise.

Scenario Analysis

What if analysisadds flexibility to the system to

stimulate the impact of external loss/fraud event

or any extreme values.


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Challenges for Indian banks

Data availability & integrity

Data warehousing / mining

Building up processes

Strengthening skills

Model validationrequires greater collaborationwith regulator

Cost - investment in risk analytics and risk

technologygetting management buy-in

Stress testing, scenario analysisbuildingcapabilities


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Thank you!