1. Model validation review

2. 2
Agenda
Our expertise in model validation| Modelsin the value chain
1
3
Introduction to CH&Cie. Focus on Global Risk Reseach& Analytics (GRA)
Our approachto model review| An integrated, iterative and proven
2

3. 3
Finance delegates to CIB Finance the supervision of the entire P&L and valuation control process
CIB Finance responsibility is carried out through “CIB Financial Control” and the coordination of the governance structure
CIB Financial control is a “global” finance control function which is responsible for supervision of the entire Valuation and P&L Control framework (which includes 1st and 2nd level controls) across capital market activities, global coordination (prepares and drives the monthly Committees that examine all issues relating to valuation, P&L and system booking)
The responsibility is shared by many players, each of them is responsible for their respective perimeter
Operations
Front Office
Risk
Finance
Middle Office & Product control
Back Office
Global Finance
Headquarter
Global Finance Control
CIB Local Finance
Global Finance Control
Local
1
2
3
4
Based on the charter of responsibilities, which defines the breakdown of responsibilities on the valuation and P&L controls, the organization is placed under the supervision of the Finance function
Finance guarantees the production and the quality of the Group financial statements and Group Management accounts
Finance uses to delegate the production and control of the financial instruments’ fair value, to the various participants
Finance delegates to Risk the authority to control the fair value of the financial instruments booked in the Group accounts (models, parameters)
Our expertise in model validation| Models in the value chainGeneral Overview: Functional organization & delegation principles

4. 4
Ensurecorrectrepresentationofoperationsintheofficialsystems
Determinethemarketparameterstobeusedandensuretheirdailycontribution
Contributetotheobservabilityassessmentwork
Proposemodificationstothemodelsandvaluationmethodologies
Supervisemodelimplementationwork
ContributetotheeconomicP&Lvalidation
AreresponsiblefortheimplementationoftheFOsystemsthataresecureandthatfulfilthecontrolobjectives.
Front Office
Finance
Operations
Risk
Define the adequate economic valuation methodologies and establish a reserve policy covering model, parameter and liquidity risks
Approve and review the models used by the Front Office
Draw up and maintain the “models/products” mapping
Contribute to the controls over deal representation in the systems, when no booking rules have been set
Have authority over the observability status of market parameters and products
Are directly responsible for the control of the non- standard market parameters, and are responsible for assisting Operations in the implementation of the standard parameter controls
Determine reserves.
Ensurethatthedealrepresentationintheofficialsystemsarecompliantwithasetofpre-definedrules
EnsurethattransactiondetailsbookedbytheFOthatimpacttheeconomicrevaluationareproperlyreconciledwiththecontractualterms
Validatethe“standard”marketparameters
Contributetothereservescalculationprocess(undertheresponsibilityofRCM)
Produce,analyseandvalidate(substantiate)theofficialP&L
ContributetothereconciliationbetweentheaccountingP&LandtheeconomicP&L
ContributetocalculationoftheDayOneP&Ladjustments
Ensuretheaccurateprocessingofoperations(i.e.clearingandsettlement,paymentandcashmanagement,confirmations)
Performoperationalcontrols(i.e.resolutionofunsettleddeals,reconciliationofcashandsecuritiesmovementswithclearer/custodian/broker)
Middle Office & Product Control
Back Office
EnsurethesupervisionoftheentireValuationandP&LControlframework(firstandsecondlevelcontrols)throughtheconsolidationandanalysisofthereportsreceivedfromallthecontributorstotheValuationandP&LControlChain
Prepareandcoordinatethemonthlyandquarterlymeetings.
Coordinatethegovernancestructure,namelymonthlyP&Landquarterlyexecutive
Headquarter
Local
PerformthefirstlevelcontrolsthatarewithintheFinancearea,notablyaccountingcontrols;
PerformthereconciliationbetweenaccountingandeconomicP&Ls,
Assumetheentity-specificpartofthe“CIBFinancialControl”supervisionmandate
1
2
3
4
Our expertise in model validation| Models in the value chainFocus on mission statements (Key responsibilities)

5. 5
Front Office
BackOffice
Finance
Risk
MISSION STATEMENT
PROCESS
TRANSACTION APROVAL
DEAL EXECUTION AND BOOKING
MODELS
(Initial development, implementation in the systems and Model control framework)
RESERVES AND VALUATION ADJUSTMENTS POLICY
MARKET PARAMETERS VALIDATION
P&L PRODUCTION
Transactions are approved by product lines (New Product and Transaction Approval Committees)
Responsible for 1st level controls on
complex deals booking
Responsible for the model control framework (approval, review and mapping)
Responsible for uncertainty or liquidity
reserves valuation
Responsible for controls defined in the flowcharts of official market parameters Responsible for controls on “non standard” parameters
Validate the observability status of
parameters (for the Day One P&L
adjustments)
Modelconception&implementation
•Formallyapproveanynewvaluationmodelormodificationofvaluationmethodologyfollowingaspecificprocedure(superviseback-testingandnumericaltestsperformedbyResearch/ITteams)
•Assessthevalidityofthemodel’stheoreticalrepresentationandtheadequacyofthemodeltotheproducttowhichitapplies
•ReviewtheresultsoftestsonreliabilityandqualityoftheITcode,andhasauthoritytoaskthatfurthertestingiscarriedoutand
•Finallyapprovetheuseofthismodelforofficialvaluation(go-live)
2.Modeloperationaluse
•Isresponsibleforthesettingandthemaintenanceofthelistofofficial(authorised) models,thatincludesthenumericalconfigurations,thecalibrationprocedureand/orset,andtheofficialusagerules(scopeofproductstowhichamodelappliesthroughtheproduct/modelmapping)
•Isinchargeofverifyingthatthevaluationmodelusedforoff-systemsdealsisadequate(inaccordancetotheproduct/modelmapping)
•Performsspecificcontrolsondealswhichhavenomodelsorspecificcharacteristics(reserves, limits…)
Zoom # 1
Zoom # 2
Our expertise in model validation| Models in the value chainA complex control framework: Zoom on the risk function

6. 6
Model Design
Model Validation
Analytics
Business valuation
Expert interventions
1
Expertise
and experience
2
Benchmark
and Best practices
3
Network
and people
Corresponds to the validation of a model , methodology or all or part of an implementation model (BT , Stress ... )
Consists in the design / construction of a model or a dominant quantitative methodology
Reflects the policy of development and innovation in academic subjects (publications *) or more operational (applied like CVA desk research).
Results in quantitative work but support interventions trades vocation ( collection efficiency , performance of grant impact simulation, ... )
Corresponds to highly specialized missions, requiring expert interventions, targeted, quick, effective and whose ultimate impact should be detailed
Objective
theeffectiveresolutionofquantitativeissueswithenvironmental/constraintsofthebankinmind
Objective
Positionthebankinacompetitiveenvironment,directthebanktobestinclasspractices
Objective
Havinganetworkofexpertstokeepupwiththemarketanditsevolutions,keepuptospeedwithmarketandregulatorydevelopments
5 major types of intervention around quantitative subjects ...
... Based on three pillars
*Electronicversionsofourwhitepapersareavailableathttp://www.chappuishalder.com/publications/
Our expertise in model validation| Models in the value chain3 pillars for 5 major types of missions

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Model maintenance and validation techniques
Benchmarking
Find a price based on a benchmark established
1
Methodologicalreview
Detailed review of the methodology used for pricing ( particularly used for illiquid products)
IndependantBack- testing
Find an acceptable price range from a set of external data ( sellers or benchmarks)
4
Re-performance
Find a prize by replicating the same methodology (or similar)
Analyticalreview
Price quotations obtained from third party sources
2
3
Conformity of the model with regulatory requirements and market practices
Regulatorywatch
6
Documentation
Organizational mapping , functional, technological and conditions of validity of the models by asset class and information system
Rationalizationet synergies
For convergence and pooling
9
10
Marketpractice
Identify the model adapted to best practices ( FVA , OIS discounting ...)
Flexibility
This census drivers of change for an adaptable model
Model-Based Pricing vs Market based pricing
7
8
5
CH&Ciehasarobustmethodologytounderstandthecomplexityofmodelsandadapttoregulatorychangesandmarketpractices(egcalibration,stresstesting,backtesting...)
Our expertise in model validation| Models in the value chainEffective and easily replicable methodology

8. 8
Modelisation
Model validation
•Model quality
oEase of use and integration ( speed of calculation and calibration
•Model relevance
oY a-t-ilun risque de modèle ?
•Flexibility of the model vis-à -vis the regulatory constraints and market practices
oCan the model easilyintegratenew regulatorybias?
oCan the model serve the business to operateas «best in class»
Pricing methodologyvalidation
•Model practicality
oFroma continuousto a discreteseries
oFroma continuousto a discreteprojection
•Calibration and pricingmethodologyimplementation
•Calculation of sensitivities and comparison with other models already on instruments calibrated
Model design and conceptualsoundness
•Validity and robustness of the assumptions and inputs
oFor instance, is the model performing in a low rate and volatility market regime
•Representativenessof output
oIs the model able to represent the risks in line with expectations
Model documentation and maintenance
•Maintenance processreview
oE.g. dailymargincoverage, back testing
•Is documentation up to date withlatestevolutions
oE.g. Model in compliance with the recommendations of the regulator
Model calibration
•Under which conditions the model is (in)effective and (in)valid it ?
oBack testinget stress testing
•Quelles sont ses limites?
oE.g. Pricing shortcut?
Our expertise in model validation| Models in the value chainCH & Ciecontrols the entire cycle of model construction and can assess its quality

9. 9
MODEL VALIDATION
PROBABLITIES & PARAMETERS REVIEW
An example of audit points on a FX rate model review -on emerging currency with jumps in FX-.
ExposurecomputationfromMarketData:forwhichdistributionprofile?
Pricingtransactionstocomputeexposureandfutureexposure(stressfulbehavior)
AremodelsConsistent?
Correlationsbetweentheprocesses
Shorttermrisk-freeInterestandFXRatesdiffusionprocess
RiskNeutralorActualProbability?
HowOtherparametersarecalibrated?
Volatilities(impliedmarketorhistoricalvolatilities)
Correlations
Whatisthebehaviorforeachmarketdata?
CurrentandFuturemarketconditionsfromdiffusionprocesses
Oneormanyfactorsprocesses(withalog-normal(Brownianmotions),Jumps(PoissonProcesses),…
Full pricingor proxies?
Full pricing using official valuation models
Valuation models are transaction specific
Hence may be different from diffusion models
Proxies for performance issues ?
Simplified analytic, semi analytic, Monte Carlo, …valuations
Conservative measure of the risk
Riskneutral
LGM Diffusion model for IR
-Brownianfactors
-Meanreverting
-Volatilitytermstructure
FX volatility from FX ATM option prices or historical data
Correlation from historical data
Jumpsfromhistoricaldata or economicanalysisproposed by Fixed Income Market / Economic Research and Validated by Risk & Permanent Control
1
2
4
5
3
Usually,itisrathertheunderlyingassumptionsratherthanthemodelsthemselvesthatarereviewedandchallenged.
Stability,robustnessandperformance(especiallyunderastress/adverseenvironment)arethefundamentalcriteriaratherthantheexactfairprice=>Toavoidarbitrage,roguetrading, imperfecthedgingstrategyorP&Lswings
Our expertise in model validation| Models in the value chainBenchmark and best practices within the market risk department

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Agenda
Our approachto model review| An integrated, iterative and proven
2
1
Our expertise in model validation | Modelsin the value chain
3
Introduction to CH&Cie. Focus on Global Risk Reseach& Analytics (GRA)

11. 11
Market Model review
Review of MtModel
consistency & robustness
Review of Model and
pricing system
Mapping &
output analysis
Analytical review
of model results
Gap analysis of
key parameters
Dif ferences
explanation
Data
quality
Inputs /
components
Model design
Design
benchmark
Calculation
process
Closed Formula
Monte Carlo
simulations
Trees / other …
Scenarios
review
Simulations
convergence
Market Risk
parameters
Other Risk
Market direct
access
No access =>
MtModel
Partial access /
Smoothng /
interpolation
Lquidity
Maret
volatlity /
stress
CVA/DVA
Cross
gamma
effect
Step 2:
Review global
methodology
Step 1:
Preliminary
diagnosis
Step 3: detailed review of a core
component
Arbitrage
…
Correlation
Step 2:
Review global
Methodology
Step 1:
Preliminary
Diagnostic
Step 3:
Detailed review of the core
components
This approach is also designed to address regulatory expectations
Our approach to model review | An integrated, iterative and proven
A vertical integration in business

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Our approach to model review | An integrated, iterative and provenFrom a quantitative tool to a more business oriented instrument with strategic guidance
Qualitativeprocess:
Qualitativereviewandmanagementoversight
Modeloperatingenvironment
Systemsimplementation
Dataqualitychecks
Examinationofassumptions
Quantitativeprocess:
Reviewofinputandparameters
Modelreplication
Benchmarkingandhypotheticalportfoliotesting
Backtestingandstresstesting
•Profitandlossattribution
Modeldocumentationanditsreview
Reviewoftheoreticalsoundness
Reviewofmodelimplementation(includingsystemsanddataquality)
Reviewofmodelinputs
Reviewofmodelassumptions,limitationsandusage
Implementationandreviewofmodelcontrols
Environment analysis:
Vacuum of the snapshot
Heterogenity& asynchronicity
To validate a model is not strictly limited to a quantitative review. The environment and the internal organisation’s «fit» is also tested
Reviewing a model should encompass:
The model operating environment includes:

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Is the model answering all the bank expectations?
What is the trading strategy?
What are the criteria for validating a model?
Risk of mispricing? (new model, strong assumptions, strong hypothesis …)
Very sensitive model? (Greeks and parameter sensitivities are high …)
Risk of P&L swings? Easy to Hedge or not? Very expensive to hedge?
Complex to follow or not? (change in portfolio composition / change in the underlying maturities …)
Risk of arbitrage?
No benchmark? Mark to Model? (no market price, partial quotes …)
Illiquid market? (higher bid-ask spreads…)
Instability of the model under stress conditions?
Regulatory risk? (Arbitrage in ISDA or CSA contracts …)
Capital requirement is too high? (Basel III, cash collateral requirements …)
Avoid gamma holes
When volatility is high, gamma is high, hedging is expensive
Large gamma may show imperfect hedge and possible jumps in PnL(barrier options)
When gamma changes sign (spread options), delta hedge is not possible
Monetize variance risk premia
Sell implied, buy realized volatility by creating a flat dollar gamma portfolio, go long gamma
Volatility term structure arbitrage
After the crisis we expect short volatility to decrease and long volatility to increase
Sell short volatility, buy long volatility by delta hedged straddles
Smile arbitrage
Volatilities are extremely volatile, but volatility smile is always flat
Sell straddle, buy butterfly
Monetize liquidity risk premium
Borrow on short-term, lend on long-term
…
Our approach to model review | An integrated, iterative and proven Critical choices and model functions needs to be tested

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Our approach to model review | An integrated, iterative and proven Model reviewobjectives servedby CH&Cie powerfultools
The objectives of the review are to:
To ensure your model meets each requirement of the regulation (including technical standards);
To ensure the quality and soundness of the modelling principles on which your framework is based;
To gain comfort on the model calibration, back-testing and stress-testing of the margins;
To identify the model limits and if needed assess the materiality of lump add-ons required to cover the risk; and
To the extent feasible, propose a benchmark analysis and suggest state-of-the-art enhancements.
Model mapping
Model validation guide
Sampleof toolsdeveloppedby CH&Cie & Cie for model validation

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Our approach to model review | An integrated, iterative and proven Model reviewphased approach
By or across product lines, CH&Cie is reviewing model documentation and testing methodology performed by internal teams with the following phased approach:
Liaise with institution market risk manager to obtain detailed model methodology/policy and validation documentation. This should contain:
•Rationale for the selected model
•Key model assumptions and provisions
•Data sources, parameter definition and model calibration procedures
•Calculation framework and frequency
Identify institution existing VaRtesting procedures to review scope, relevance and results under calibrated parameters (market regime, confidence level, look back period…)
•Assess risk factor relevance, return calculation, depth and source
•Define standard parameters and calibrate model accordingly
•Compare VaRand expected shortfall
Prepare test scenarios that can be run independently to verify VaRimpact and model performance (back testing, input parameter sensitivity, stress testing) and compare with institution results. For instance, we will “fine-tune” parameters such as:
•Risk measure/number of breaches, confidence level, look-back period, scale vol, correlations, decay factor…
•Description of the tests performed
Sample a representative portfolio and simulate scenarios for additional comparison between institution and CH&Cie model, using back testing at risk factor level.

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Our approach to model review | An integrated, iterative and proven Model reviewdeliverables
This model review shall include:
An evaluation of the conceptual soundness of the model and framework;
A review of the on-going monitoring procedures such as daily margin coverage and back-testing;
A review of the parameters and assumptions made in the development of its models, their methodologies and the framework including an assessment of the theoretical and empirical properties of the margin model;
A review of the adequacy and appropriateness of the models, their methodologies and framework adopted in respect of the type of contracts they apply to;
A review of add-ons to the base model;
An analysis of the outcomes of testing results against institution performance criteria;
A review of the diversification benefits of the model;
A review of the margin period of risk;
An assessment of pro-cyclical effects and how such affects are mitigated;
An assessment of margin model sensitivity to the material risk factors and correlations to which the institution is exposed;
A review of pricing models; and
A review of model documentation

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Our approach to model review | An integrated, iterative and proven Our recent work in modeling : one of the richest experiences in the street
Risk managementandmodelling
AccompanyingtheproposedimplementationofIMMmodels(EPE...)
•French Commodity house
•Price dissemination and pricing models
•Validationoftherelevance/consistencyoftechnicalresponsesbyclient
•ReviewandvalidationofmeasurementmethodologyandmonitoringofPDparameterandwritingareportACP
ReviewofVaRmodelsandCVaRforseveralfinancialinstitutions
•Tier 2 financial institutions
•VaRMC,historicaletparametric+Stresstest+inputs
•Documentation
DetaileddiagnosisofthemodellingoftheEPEofalargeFrenchCIB
•French CIB (under CRD4 constraints
•Pricedisseminationmodelreview
•Comparisonstandardmarketpractices(benchmark)
AssistinreviewingtheACPRrecommendationsforapprovaloftheinternalcounterpartyriskmodel
•French CIB (namely inputs and proxies)
•Reviewingtherecommendationsandproposedresponses
•Implementationofcorrectiveactions
•Documentationtotheregulator
Detailed diagnostic work for the establishment of a CVA desk
•French CIB
•Studytheprofileofcounterpartyrisk(maturity,concentration,…)
•Designdeskmandate
•ImpactSimulation
•ReviewofCSA
(*) non exhaustive.
Other examples available upon request
Mission
Perimeter
Actions
Buildingoflibrariesforpricingvanillaandsemi-exoticderivativesforseveralsecuritiesinstitutionsinChina
•Securities firms
•Chinese market
•Pricingtools(closedformulasmainly)
•Adaptationtolocalmarketspecificities(data,legal…)
•Training
Reviewofmodelsriskprovisions(includingbid-ask,smile...)forseveralinstitutions
•French CIB
•(incl. Commodities)
•Reviewprovisionmethodologies
•ImpactAnalysis
ModelvalidationforIMcalculation, historicalVaR
•Tier 1 institution (largest IRS clearer)
•Reviewofexistingmodelvalidationmethodologies
•Back-testing,stress-testingonHypotheticalportfolios
•Reviewofadd-ons:basisrisk,problematiccurrencies

18. 18
Agenda
Our expertise in model validation | Models in the value chain
1
3
Introduction to CH&Cie. Focus on Global Risk Reseach & Analytics (GRA)
Our approach to model review | An integrated, iterative and proven
2

19. 19
CH&Cie Risk Management offer (1/4) From managing risk processes, to measuring risks and establishing strategic guidance
Strategic
guidance
Measurement &
validation
Processes & organisation
Risk Management
1
2
3
•Helpingtomakinghigh-leveldecision(CVAdeskimplementationetc…)
•Definingriskappetiteinaccordancewiththebusinessstrategy&development
Strategic guidance
Measurement & Validation
•Quantifying risks and measuring impacts on a business level
•Validating models and developing advanced quantitative techniques
Processes & organization
•Reviewing risk management processes
•Establishing monitoring procedures
•Organizing and defining risk governance and follow-up

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1. Finance
2. Pricing
3. ALM / Liquidity
4. Credit Risk
5. Market Risk
6. Operat. Risk
7. Business & Strategy
8. Customer relationship management
1.1ICAAP / Pillar 2
1.2Economic capital
1.3Capital budgeting / RAPM
1.4P&L and budget forecasting
2.1Standard & Complex Models
2.2Instrument pricing
2.3Pricing Parameters control
3.1Basel III : LCR, NSFR, liquidity
3.2Securitization SPV, collat. manag.
3.3Gap : CF patterns, survival horiz
3.4Dynamic modeling
4.1Basel II: PD, LGD, EAD, CCF, UL, RWA
4.2Basel III, CVA, CCP, Capital
4.3Solvency II : capital
4.4Provision specific, collective
4.5Stress & back testing
5.1Classic & stress VaR, CVar
5.2Risk reserves
5.3Sensitivities Modeling & Calculation
5.4Incrementaland liquidityrisk
6.1Fraud detection
6.2AMA models
6.3Rogue trading
7.1Strategy guidance and decision
7.2Brand notoriety, reputation
7.3Process optimization
8.1Credit granting models
8.2Portfolio scoring
8.3Marketing and targeting
8.4Data mining and desctriptive statistics
CH&Cie Risk Management offer (2/4) A large scope of intervention with expertise, experience and benchmarking at the heart of our strategy
0. Advanced Modeling, experience, expertise, benchmarking
Please, specify the subjects you are interested in, by checking the orange boxes
Legend
Business intent
Regulatory intent
6.4Operations structuringcontrol

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CH&Cie Risk Management offer(3/4) Modeling as an integrated business tool: a cross-disciplinary skills and decision-making facilitator tool
Modelingas a
transversal tool
Risks
1
•Market:VaRcomputing,volatility, liquidity,valuation
•Credit:BaselIIparameters, Provisioning,stress,backtesting
•Operational:fraud,roguetrading...
Finance
2
•ManageAssetsandLiabilities
•ManageEconomiccapital(ICAAP)
•SimulateP&Limpacts
•CapitalBudgeting:RAROCetc…
Business
3
•Optimizeoperatingmodel
•Adaptmarketing(CRM)
•Scoringandtargetingcustomers
Strategy
4
•Buildbusinessstrategy
•Monitorreputation
•Arbitragebetweenrisktakingandbusinessdevelopement
Modeling allows to anticipate, prevent, detect, measure, test, develop and decide… It is a powerful tool that requires a specific set of skills and knowledge

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CH&Cie Risk Management offer(4/4)
Modeling techniques and requirements: the work tools
1 Data analysis
• To give a quantitative
perspective of a
specific context or for
problem detections
(by analysing data)
Main objectives
2 Simulation 3 Solving 4 Prediction 5 Methods
• To validate hypotesis
and / or find the best
option of a specific
strategy
• To give a closed
formula of a specific
problem
• To give an estimate or
a prediction (estimed
probability of an event
to happen under
certain hypothesis)
• To define and design a
quantitative
methodoloy for
strategy purposes or
business decision
• Data Mining
• Statistics
Underlying
techniques
• Monte Carlo
simulation
• Bayesian networks
• Fuzzy logic / Expertise
• Mathematics
• Statistics
• Probability
• Statistics
• Benchmark
• Experience/ Best
practices
• Fraud detection
• Portfolio analysis
• Correlation analysis
• Dashboard / reporting
• Marketing …
Illustrations • Capital planning
• Strategic plan
forecasting
• Pricing
• Stress testing …
• RWA Calculation
• Pricing
• Marketing
• Valuation (firm
value)…
• Risk parameter
estimation (PD, LGD,
EAD)
• VaR / Credit VaR …
• CVA desk implement.
• « Cost of risk »
hedging policy
• Choice among
different approaches
…
AAA
AA
A+
A-BBB
BB+
BB-B
CCC
DX
-
200
400
600
800
1 000
1 200
2011
2012
2013
2014
2015
2 020
2 030
2 040
2 050
2 060
2 070
2 080
2 090
2 100
Rating
Number of clients
Maturity
Profile analysis
 









 
 
 

i
i i
i
p y
P Z Y y


1
( )
1
1
Markov
Models
Regression models
Vintage analysis
Binomial Tree
Actuarial models (Beta calibration)
Statistical
Models
Loss Calc
Others...
External
Models
Recovery
Assessment models

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People
Research & analytics
Technical expertise
Scope
Business intelligence
We are a team specialized in quantitative expertise. From various background & with varied academic profiles, we yet converge towards Excellence, achieved with high standards and flawless delivery.
From regulatory requirements to optimization and value creation, our experience of the financial services issues enable our teams to capitalize on CH benchmark and enhance our performance on new missions
Our offer & approach are multi-dimensional : we cover all banking activities issues requiring regulatory expertise and modelling skills.
We operate on all modelling issues through the whole life cycle of models, from analysing available data and inputs, to building and designing customized models and validating outputs and performance
Beyond supporting our client offers, we
are constantly challenging our knowledge and understanding of the market through
•Publications of white papers
•Analytical contents
•Conferences
•GRA Lab
CH&Cie Global Research and Analytics has been recently created in 2012.
Our expertise centre covers a wide array of interventions on Risk Management topics, and provide our clients with solutions that are customized to their specific needs and risk profile. In a changing business and regulatory environment, it is crucial to move forward and adapt our capabilities to our clients’ needs.
Furthermore our team can intervene
at worldwide level
An holistic vision of Risk Management
Introduction to CH&Cie. Focus on Global Risk Research & Analytics (GRA) CH&Cie & CieGlobal Research & Analytics© Dept.: our value added

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Static modelling
Increasing transactions volumes
•Data : poor quality / low storage capacity
•Tools : low computing power / increase in banking transactions volume
•Practices :CIB R&D development
Pricing& valuatinginstruments
•MtMarket
•MtModel
Dynamic modelling
(Average current situation)
Regulatory incentives
•Data : improved storage capacity
•Tools : improved computing power
•Practices :homogeneisationof modellingpractices
Business integrated modelling
Need for strategic guidance
•Data :centralized with unlimited capacity
•Tools : enhanced computing capabilities, algorithms & modules
•Practices : advanced & business oriented modellingtechniques
Understandingtransformation of riskmanagement tools
Measuring & capturing market risks
•Sensitivities
•VaRmodels
Covering other financial risks
•Credit IRB
•Operational / AMA
Developing advanced techniques for rare risks & complex instruments
•Reputational risk
•Complex exotics/Securitization
Optimizing profitability & managing business portfolio
•ICAAP / Risk Appetite / RAROC
•Scoring / collection
•Funding/ Cash management
Defining targets and steering strategy
•EVA / Earnings Volatility
•Strategic Plan, Risk Reserves
Computing across for every business purpose
•Measure impacts on all dimensions (P&L, B/S, CT1,Treasury, ALM, stress testing)
Solving complex equations for strategic purpose
•Competitive positioning
•Ideal target product mix
Risk Management functions are shifting from a mere measurement tool
to a business-oriented instrument
with strategic guidance
Adaptingouroffer& expertise to the evolvingneedsof ourclients
Fuelled by the need to limit conflict of interest, to reduce risks and meet regulatory requirements, banks are building longer term relationships focusing on client satisfaction.
Since 2007, the erosion of the profitability of the banking sector surged financial institutions towards a better management of their risk environment. We believe managing risks is about understanding all banking activities, as well as the dynamics of their interactions. Risk modelling is therefore cross- disciplinary and transversal across
•Financial purposes (Valuation, Credit & Market risks, ALM & Liquidity, Capital)
•Business topics (Operational risk, Business & Strategy, Customer Relationship Management)
Introduction to CH&Cie. Focus on Global Risk Reseach& Analytics (GRA) CH&Cie & CieGlobal Research & Analytics© Dept.

25. 25
Our first booklet(fromarticles publishedon ourwebsite)
Lesversionsélectroniquesdenosarticlessontdisponiblessurhttp://www.chappuishalder.com/publications/
Article on CVA (standardizedapproachcalculationdemonstartion)
Introduction to CH&Cie. Focus on Global Risk Reseach& Analytics (GRA) CH&Cie & CieGlobal Research & Analytics© Dept.

26. MONTREAL
202 –1819 Bd ReneLevesque O.
Montreal, Quebec, H3H2P5
PARIS
20, rue de la Michodière75002 Paris, France
NIORT
19 avenue Bujault
79000 Niort, France
NEW YORK
1441, BroadwaySuite 3015, New YorkNY 10018, USA
SINGAPORE
Level25, NorthTower,
One Raffles Quay, Singapore 048583
HONG KONG
905, 9/F,
KinwickCentre 32 Hollywood Road,
Central, Hong Kong
LONDON
50 Great Portland Street
London W1W 7ND
UK
GENEVA
Rue de Lausanne 80CH 1202 Genève, Suisse