Scenario-based AMA

38 Pages·2003·0.86 MB·English

SScceennaarriioo--bbaasseedd AAMMAA
Presentation for RMG-Conference 29./30. May 2003
May 2003 (final version 1.0)
The following banks have contributed to the content and draftingof the presentation. Such contributions do not imply
that the institutions will implement the approach set out in thepaper, but rather that they believe a Scenario-based AMA
is conceptually sound and, if implemented with integrity, shouldberecognisedas qualifying for AMA status. The views
expressed do not necessarily reflect the overall view of each individual institution.
Banca Intesa
Barclays Bank
CreditSuisseFirst Boston
Dresdner Bank
FortisBank
Halifax Bank of Scotland
Lloyds TSB
The Royal Bank of Scotland Group
UFJ Holdings, Inc
Euroclear
RCO OR
Group Risk Control
CC Risikocontrolling
Operational Risk
© Scenario-based AMA working group
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 Objectives of presentation
 Introduction
 Overview of concept
 How to determine appropriate scenarios for OR?
 Howtoensure that scenarios are consistent, relevant andcaptureall material OR?
 How to evaluate scenarios in anorganisation?
 How to use scenarios formodellingpurposes?
 Why a scenario based AMA improves OR management (example application)
 Key benefits of a scenario based AMA
 How other building blocks link into a scenario based AMA
 Overlap / similarities with LDA / Scorecard
 Illustrations
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 To demonstrate that a scenario based approach is conceptually sound
 To define the key features of implemented scenario-based AMA approaches
 To prove that a scenario based approach is a valuable basis for managing risks
 To indicate that banks are fairly aligned in terms of thinking about scenarios
 To describe how scenarios can form an integral part of economic and regulatory
capital calculations
 To illustrate how scenarios can be constructed in the most useful way
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A scenario based AMA
 is focused on a forward looking assessment of the key operational risks in an
organisation taking into account both the internal control environment and external
threats
 is an approach that employs the technique of individual scenarioevaluation in a
similar fashion to market and credit risk
 is based on all available information (expert experience, internal / external losses,
KRIs, quality of control environment)
 leads via a model to a sound economic capital number that helps to incentivise
prudent and pro-active OR management
 bridges the gap between LDA and Scorecard approach
(or at least has a considerable overlap with each)
 has been or is being successfully implemented in a number of international banks
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 Scenarios are defined aspotentialevents(i.e.events that could happeninthe
future).
 Risk is inextricably linkedtothe evaluationof „what-if“certain scenarios occur.The
evaluation process involves providing answerstotwofundamentalquestions:
 How likely are certain scenariostohappen?
 How severe could their impact be?
 Scenarios are alreadyanimportant techniqueinthe evaluationofmarketandcredit
risk as illustratedinthe following questions:
 What is the impact if the yield curve shifts by20bp?How likely is this?
 What is the impact if this customer defaults?How likely is this?
 Scenarios arealso an essentialcomponentinthe assessmentof operationalrisks
anddeterminationofcapital.
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Scenario Scenario Data Determination of Model & Model
Generation Assessment Quality Parameter Values Parameters Output
How to determine How to evaluate How to use scenarios for modelling purposes?
appropriate scenarios in an
scenarios for OR? organisation?
high CA 275,26
UA
Potential Loss Severity medium highmedium low EINSEXTEPITEMAIFOGPR 127,69
EC
low RR 574,68
Mean,
low medium low medium high high
Potential Loss Frequency Scenario Classes
892,72 Std. deviation,
O
etc. r
449,62 g
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688,35 s
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694,28 o
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How to ensure s
that scenarios are
consistent,
relevant and
capture all
material OR?
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 The determination of a appropriate scenarios that are
Scenario Classes
representative for OR is key to the scenario based AMA O
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 Scenario classes –one or more–are classes that are n
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derived from loss event types or risk factorsandthat t
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contain scenarios. (Example:Scenario class= IT-breakdown.) a
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 Organisational parts are the partsofthe organisation for r
t
s
whichORis separately evaluated.
 Generate scenario(s) perscenario classandorganisational part basedon:-
 guided discussions with thebusiness inworkshops(eg. Dresdner;Fortis, HBOS)
 amatrixof „critical resourcesandstatesofrisk“ (eg.Banca Intesa)
 weaknessesperrisk factor(eg. UFJ Holdings)
 aspecificationofcritical resourcesandfailure periods by the organisational parts
(eg. Dresdner)
 addressing particular management concerns(all)
 All scenarios are fully documented to allow independent review and assessment
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 Consistent?
 Every organisational part must consider as aminimum eachofthe common setof
scenario classes,thereby achieving consistency of the overall framework.
 Techniques such as workshops assist to achieve consistency of scenarios across
organisational units
 Review by Internal Audit and Risk Functions provides further consistency between
organisational parts.
 Relevant?
 Every organisational part assesses the relevanceof allscenariostoitsbusinessthereby
ensuring relevancetothem(e.g.if aorg-unit is not dependenton IT,it does not make
sense toevaluate the risk dueto ITbreak-down).
 Captureall material operationalrisks?
 The techniquestodetermine the scenario classes(eg useofexpert judgementand
historical loss data)maximise coverageofknownandforeseen risks.
 This coverage is further enhanced when applied to the organisational parts and discussed
with them to ensure that their specific risks are covered.
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 Foreach scenario banks assesspotentialloss frequenciesand potentialloss
severities.
 The organisational processofevaluation is basedon:
 questionnaires
 guided workshops
 central(management)expertise
 In order to come upwithplausibleanswers banks base their evaluationon
informationrelevant tothe scenario, suchas
 anassessmentof operationalquality/qualityofcontrol environment
 past losses,key risk indicators,insurance
 industryandmanagerial experience
 Tovalidate the scenario evaluations banks apply techniquessuchas
 4-eye principle
 Internal auditsofassessment processandresulting quality
 Comparison between actual lossesandexpert expectations
 Consistency checks(e.g.psychometric analysis, Groupfunctions challenge profilesof
organisational parts,comparisontointernal audit findingsandvalidation.)
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 A goodrisk model must be consistent, robust, and stable over time, so that
changes in economic capital result from changes in the underlying risk profile and
not from changes in the model.
 A model on risk requires plausible assumptions where distributions or analytical
solutions are used
 The model requires the estimation of its parameters.
 The data required for the parameter estimation must go through arigorous data
quality assurance.
Raw Data AFTER data cleansing Parameter Estimates for Distribution
Scenario Typical Frequency Typical Severity Mean Standard Mean Standard
Class Frequency Upper Bound Severity Upper Bound Frequency Deviation Severity Deviation
IT 4 2 200 233
* Scenario 11650300
* Scenario 26103001000
* Scenario 357250700
Control 6 3 250 125
* Scenario 136100500
* Scenario 2710400100
* Scenario 3820250900
... ... ... ... ...
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