Michael Rehwinkel
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Agenda
JPMorgan Chase & Co. Operational Risk Overview
Objectives and Framework
Tools for Risk Measurement and Risk Management
Control Self Assessment Process
Risk Event Database
Capital Methodology
Reporting
Firmwide Technolo Platform
Future Agenda: Maximizing Return on Investment
2010 JPMorgan Chase & Co. Strictly Confidential and Proprietary
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Overview
Development and Implementation Timeline
JPMor an Chase is movin into the fourth sta e of a four-sta e model
Begin loss Anal ysi s and
quan t i f i ca t ion
and self
assessment
Repor t ing
Ad Hoc
Ad Hoc Orientation
Orientation Analytics
Analytics Framework
Framework
Business
specif ic only ;
no f i r m-wi de
da ta
Begin l oss
quan t i f i ca t ion
and self
assessment
Analy si s and
Repor t ing
Int egrat ed r isk
management
f ocused on
cont inuous
Traditional Audit &
Financial reviews
Governance
framework
Dashboard reporting
Risk driver analysis
Predictive
models
mprovement
pera ona r s
managementmostly reactive
an ar oss a a
reporting
Rigorous self
assessment model
Root cause
analysis
Internal and External
orre a ons
across risk classes
Risk mitigation
tools
Risk-based capital
2002Pre 2000 2006 2010 +
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Overview
Objectives and Framework
Improve understanding of drivers
Objectives Integrated Framework Design
Create environment of reliabledata, transparency of issues,
ss
ControlControlAssessmentAssessment
Risk EventRisk EventDataData
escalation and accountability
Move to no surprise environment
BusinessBusinessUnitsUnits
GovernanceGovernanceFrameworkFramework
OperationalOperational
RiskRiskCapitalCapital
issues as they develop and before
losses are incurred
Meet regulatory requirements:Basel II, Sarbanes Oxley 404 & FDICIA
IntegratedIntegratedReportingReporting
Key RiskKey Risk
IndicatorsIndicators(in(in
development)development)
through lower losses, reduced
volatility, greater productivity and
more efficient capital usage
Single, Integrated Technology Platform
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Tools for Measurement and Management
Risk and Control Identification and Management
Central Source of Operational Risk Information in the Firm provided byself-assessment process supplemented by other sources of data
Comprehensive operational risk and control data
Business Processes Information Technology: Infrastructure and Applications
Controls
Compliance
Multi le SourcesAssess
Effectiveness
Self Assessment
Internal Audit
Identify Gaps &Action Plans
Identify Gaps &Action Plans
External Audit
Regulatory Issues
Report &
Track
ynam c ssessment
Linked to Loss Data and Capital
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Tools for Measurement and Management
Risk Event Data: Fundamental for Improved Risk Management
Trend of Total Errors by Date
Occurred
15
65
115
165
215
265
01/1 01/2 01/3 01/4 02/1 02/2 02/3
IntegratedError
TrendAnalysis
HISTORICLOSSDATA
SeverityDistribution ofErrors $1Million andGreater(firmwide)
006
0.08
0.1
0.12
0.14
0.16
0.18
0.2
Pro
ba
bilit
y
Effect of 'Find Time' on Event Severity
1,000
1,500
2,000
2,500
Avg.Impact
300
400
500
600
700
#ofEvents
AverageImpact
#ofEvents
Capital Allocation
Lessons Learned
RiskEvent Profile -ActivitybyFunctionFY 2001,AllEconomic andTiming Events
(inabsolute value,$000)
All Op Risk Events Economic Impact>=$20k(FY 2001/2002,in $millions)
0
0.02
0.04
.
1 3 5 7 911
13
15
17
19
21
23
25
27
29
31
33
35
37
39
41
$millions
0
500
1-15 15-30 30-90 90-180 6mo-1yr 1yr+
FindTimeLine
0
100
200
Root CauseAnalysis
Customer Service
Client Rel / Front Office
Trading / PortfolioManagement
TransactionSupport &Mgmt
Core Ops / CorpService
Finance / Corporate Staff
Technology/ Applications
N/A-Other
0
10,000
20,000
30,000
40,000
50,000
60,000
Total Impact ($000)
ActivityType
Function
$0
$50
$100
$150
$200
$250
$300
E xecu tion C lients F raud /T hef t E mployee/S afety Majo r E xte rna l
$0
$1
$2
$3
$4
$5
$6
$ ImpactAvImpact
AvgImpactTotal
Impact
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Tools for Measurement and Management
Capital Methodology
Capital measures of regulatory and economic capital based on statisticalmodel that includes the four required regulatory elements
1. CALCULATE BASE CAPITAL 3. ASSESS CAPITAL2. ADJUST FOR
InternalLoss Data
APPROPRIATENESSINTERNAL CONTROL
FACTORSInternal Losses
Exter nal Losses
BaseCapital
StatisticalModel
Risk-basedCapital
QualitativeAdjustmen
t
Int ernal and
External
Benchmarks
ScenarioAnal sisLoss Data
LDA Frequency distributionbased on internal data
Severity distribution based on
Audit Grades
Control Gap ActionPlan metrics
Senior ManagementReview
Appropriateness of
Aggregate Loss Distributiongenerated via Monte Carlo
Potential for othermetrics / KRIs
Capital May be adjustedUp or Down
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Combination of Internal and External Loss Data Enables Risk
Measures at Business / Risk Type Level (31 Units of Measure)
Cap ta Ca cu ate or our aggregate r stypes for each business
Business Practice / Litigation Risk (BP)
xceptons to overcome s ortcomngs:
Asset Management BP risk split forInvestment Mgmt and Private Banking
Execution Risk (EX) Fraud Risk (FR)
Investment Banking BP risk split intounderwriting and non-underwriting
Underwritin risk uses different mp oyee spu e s
Plus one aggregated firmwide
Dama e to Ph sical Assets DPA
exposure-based methodology
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Tools for Measurement and Management
Standard LDA Approach Used (for all but one Unit of Measure)
The Modeling Approach is based on the standard actuarial model of estimating afrequency distribution and a severity distribution to derive an aggregate loss distribution
Same Model for Regulatory and Economic CapitalFre uenc of Loss Severit of Loss
Frequency Distribution Poisson
ensity
Density
Severity Distribution
Mixture of Lognormal (up to 6 components)Annual Frequency
D
Loss Amount in $
Internal Data
External ORX Data
Aggregate Operational Loss
Regulatory Economic
99.9% C.I. 99.97% C.I.
UnexpectedLoss
ExpectedLossD
ensit
y
Belowthresholdlosses
1-Year Holding Period 1-Year Holding Period
Includes Expected Loss Excludes Expected Loss
(= Model EL +-
Mean 99.9th
percentile
0
Regulatory Capital
99.97th
percentile
Thold
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Tools for Measurement and Management
Large Tail Events Distort Results from Traditional LDA Approach
A Generation 2 Exposure-based Model Developed for IB Underwriting Risk
Model Attributes Model Summary
Port f o l io of Relat ionships Total $ amount at risk?xposure
Pr obabi l i t y of Event (PE)
rel
ation
Event FrequencyHow often do such eventsoccur?
Invest or Loss (IL)Even
tC
o
Given an event how muchcould an investor have lost?
Event Severity
How much could a settlement
Event Correlation
be as a % of investor loss?
What is the joint
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Tools for Measurement and Management
Reporting
Losses in current period, risk and control ratings, Issue resolution status, KRIs etc.
9 Information conveyance, actionable reports
Historic Data Trends Loss data, CSA metrics, KRIs etc.
9 Information conveyance
Ad hoc query capability
Tailored reportsuppor s ana ys s
Benchmarking,
JPMC vs. ORX Benchmark projects, Range of Practices, LDCE
9 Information conve ance, some actionable re orts
Visualization
Simple management dashboard, Heat maps, E2E process maps
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Tools for Measurement and Management
One Firmwide Technology Platform for Operational Risk Data
Used by all businesses globally
In-house development
Launched in 2004
6,500 Registered users
3,000 average users / month
Compliance Assessment
Test Capture
My Alerts
Key Metrics
M Profile
Updates
Capital
IT Risk
Administ rat ion
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Reports
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Future Agenda
Leverage the investment in time, effort and $ to improve risk managementpractices, and increase financial performance through lower losses, reducedvolatility, greater productivity and more efficient use of capital.
Im roved Anal tics and Re ortin
Greater insight Forward looking
More actionable
Key Risk Indicator Development
Directionally correct, if not statistically defensible
Benchmarking Internal: Quantitative and Leading Practices
External: Quantitative (via ORX) and Leading Practices (ORX, RMA and others)
Extended Integration p r s an us ness per ormance me r cs
Op risk and other risk classes
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