Credit Risk Modelling

1. Fully revised and updated
Credit Risk Modelling
Highlighting Best Practice And Current Developments
20 – 23 November 2011 • Kempinski Hotel, Mall of the Emirates, Dubai, UAE
5 KEY LEARNING OBJECTIVES
1. Explore the latest qualitative and quantitative credit measurement and modelling techniques related
to individual credit facilities, consumer and retail credit, accounts receivables and collections, corporate
lending, sovereign credits, securitised credit exposures and portfolios of credits, as they can be applied in
the region
2. Learn current credit risk modelling best practice for the assessment, measuring and modelling of credit
risk factors including potential credit exposures, credit loss distributions, default frequencies, times to
default, recovery rates, credit migrations, credit spreads and dependent default frequencies
3. Understand best practice and the applicability of structural and reduced-form credit risk models, including
an overview of common commercial/vendor credit portfolio analysis models
4. Implement qualitative and quantitative credit modelling techniques, including credit-Value-at-Risk (CVaR),
presented over the duration of the course using practical Excel-based Monte Carlo simulation exercises
5. Acquire knowledge of credit loss protection techniques and various procedures for hedging different
aspects of credit risk and follow the evolution of a global regulatory capital standard, i.e. Basel I, II and III
Delegates should bring
their laptop with Excel
ORGANISED BY OFFICIAL REGIONAL preloaded.
RECRUITMENT PARTNER
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2. Course Overview
Since the mid-1990s, innovative and groundbreaking techniques have
been developed in credit modelling and measurement, which have led
to a modern approach to credit risk management. This course presents
the fundamentals, objectives and procedures for assessing, evaluating
and modelling the creditworthiness of those exposed to different credit
exposures, which affect credit providers and lenders. The course is
designed to present a comprehensive discussion focused on current and
best practice in qualitative and quantitative credit risk modelling and
measurement techniques, which have become a required part of the skill
sets for both credit risk managers and analysts. The course also presents
the best practice for modelling and measuring of credit loss distributions,
individual and dependent default probabilities and intensities, credit
migration transition matrices, recovery rates and credit spreads.
Extensions of Value-at-Risk (VaR) for assessing credit risks, i.e. Credit
Value-at-Risk (CVaR) are also presented for standalone and portfolio
credit risk.
The course will introduce you to qualitative credit risk assessment
techniques, including credit scoring assessment procedures and scorecard
management techniques, in the context of the management of accounts
receivables, granting credit facilities and behavioural scoring of customer
accounts. Collection management procedures are presented for the
management of credit exposures inherent to accounts receivables.
Discussions and comparisons of structural and reduced-form credit
risk models are also presented, including an overview of common
commercial/vendor credit portfolio analysis models. Credit loss protection
techniques such as factoring of accounts receivables, letters of credit,
credit insurance and securitisation, collateral and margining, and the use
of covenants are detailed. Hedging techniques for counterparty credit
risk and methods for assessing credit concentration risk are also covered.
Hedging applications of credit derivatives and credit derivative indices
are also presented.
Basel II, as detailed in the latest June 2006 version of Basel II, presented
in terms of general principles of Basel II is a set of three mutually
reinforcing pillars, i.e. Pillar I - minimum capital requirements, Pillar II -
Supervisory review, and Pillar III - Market discipline. Also, Basel III, which
is the latest extension of the Basel accords, is discussed in terms of the
new rules included in the December 2010 Basel initiative for reforming
global regulatory framework.
Notes
An understanding of the workings of the credit markets, basic
knowledge of standard risk measurement models and intermediate-
level courses in statistics and probability are prerequisites.
Proficiency with Excel is also suggested. Delegates should bring their
laptop with Excel preloaded.
971-4-3352437 971-4-3352438

3. Meet Your Expert Course Leader
D
Dr. John W. Dalle Molle is an independent financial
markets consultant and trainer specialising in quantitative
m
credit, energy, market and operational risk management,
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a
analytics and modelling. Recently, he has been involved
in model validation consulting projects with major
Singaporean and Malaysian banks. He has presented
executive educational and professional training programs in Africa, the
Americas, Asia-Pacific Region, South Asia, the Middle East, the GCC and
various European countries. His clients include several large financial
institutions and central banks. In the past, he has also taught at a number of
renowned universities in Asia, Europe, and the Americas. Dr. Dalle Molle has
also made several professional presentations at international conferences
and exhibitions.
Who Should Attend?
Organisations and individuals seeking commercial and personal credit
and credit lines, those making commercial and personal credit-granting
decisions, lending and credit policy makers, commercial and in-house credit
scorecard developers and users, credit risk managers and regulators; and
specifically:
• Asset/Liability Managers
• Back and Middle Office Personnel
• Billing and Collection Managers
• Central Bankers, Market Regulators and Bank Supervisors
• Chief Risk Officers and Enterprise Risk Managers
• Corporate Financial Analysts
• Credit Portfolio Risk Managers
• External and Internal Auditors
• Loan Origination Officers and Underwriters
• Project Finance Managers
• Quantitative Credit Risk Analysts
• Retail and Consumer Lending Managers
• Securitisation and Structured Finance Market Practitioners
• Treasury and Capital Markets Analysts and Managers
Course Methodology
The lecturing and course context are developed and presented through a
systematic approach, starting from fundamentals of credit exposures to
qualitative scoring methods, quantitative standalone and portfolio credit risk
modelling techniques and advanced credit risk modelling using structures
and securitised credit products.
The modelling procedures are supplemented with the analysis of various
case studies of systemic credit crisis examples over the last 30 years
including the subprime crisis mid to late 2000s, the subsequent credit
market freeze up of late 2008 and early 2009, and the European sovereign
debt of 2011.
An extensive set of practical worked exhibits and examples, discussions
and case studies, computer simulations and various other exhibits are used
throughout this course. You should be familiar with Microsoft Excel.
• www.iirme.com/creditrisk
Email: register@iirme.com

4. Credit Risk Modelling
20 – 23 November 2011 • Kempinski Hotel, Mall of the Emirates, Dubai, UAE
Course Timings Registration will be at 07:30 on Day One. The course will commence at 08:00 and conclude at 14:30. There will be two refreshment breaks at
approximately 10:00 and 12:30 and lunch will be served at the end of each day’s session.
Course Outline Day Two
Day One Credit Scores, Credit Scorecards, Credit Scoring Techniques,
Scorecard Management Reports, Collections Management And
Credit Risk Exposures, Credit Events; Credit Ratings, And Credit Exposure Distributions
Qualitative And Quantitative Credit Quality Assessment
Techniques Classic Credit Evaluation And Analysis Using Credit Scores And
Scorecards And Consumer Credit Scoring Methods
Credit Risk, Credit Exposures And Credit Events • Credit evaluation using credit-scoring techniques
• Credit, credit analysis, and credit decisions – historical perspective • Comparing credit scoring and credit rating
• Credit risk categories, sources, and exposures for credit-sensitive products • Different classes of credit scores and credit scorecards
- Exposures for different credit products • Scorecard development and the selection of scorecard characteristics
- Exposures for corporate loans • Characteristics used in accounts receivables and collection scoring
- Exposures from credit given to retail customers
- Exposures inherent to a bank’s trading operations Exhibit: Scoring criteria – characteristics and attributed used in consumer
- Exposures from derivatives positions scoring models
• Credit events used in credit risk modelling – default, trigger and Exhibit: FICO and vantage credit scores – a comparison
termination events
• Effects of credit events on creditworthiness assessments Characteristics Of Credit Scoring Methods
• Common statistical and judgmental indicators of credit worthiness
Exhibit: Establishing good credit and the credit lending decision • Common predictors of credit quality for individuals/consumers
Excel Exercise: Simulation of the time to default and default events • Distinguishing between risk classes in score-based rating systems
• Extracting a credit rating system from credit scoring models
Credit Quality Evaluation Using Credit Ratings • Judgmental and quantitative risk characteristics for consumer credit
• Credit ratings methodologies – guidelines, criteria, information and scoring
performance
• Corporate credit ratings – historical perspective and an overview Exhibit: Credit scoring examples for credit approval, accounts receivables,
• Credit ratings migrations, default probability forecasts and credit gradings fraud, recovery, and collections scoring
• Granularity issues and other limitations for credit rating scales
• Sovereign credit ratings – overview Scorecard Management Reports and Collections Management
• Front and back-end scorecard management reports – An overview
Exhibit: Comparing long and short-term debt rating and equity ratings • Accounts receivables, credit collection policies, and reducing counterparty
Exhibit: Comparing Standard and Poor’s, Moody’s credit ratings – criteria risk
and definitions • Collections scores, maintaining accounts, and measuring collections
performance
Credit Quality Assessment Using Qualitative Credit Assessment • Delinquent payment management and collections management techniques
Techniques
• Corporate/retail business failure prediction – an overview Exhibit: Developments and interpreting in front and back-end scorecard
• Six Cs of credit: factors affecting the credit ratings management reports
• CAMEL creditworthiness assessment system Excel Exercise: Examples of front and back-end scorecard management
• Argenti’s A-scores for assessing creditworthiness reports
• Piotroski F-score for assessing financial strength
Credit Exposures and Credit Loss Distributions
Exhibit: Key Risk Indicators (KRIs) and a credit risk rating framework for • Modelling loan exposures – current and potential exposures
individual banks and banking industry structure • Credit loss structures – expected, unexpected and extreme losses
• Common loss distribution models used in credit risk modelling
Regression-Based Credit Ratings Models • Multivariate credit loss distributions for portfolios of dependent credits
• Financial attributes affecting retail and corporate credit quality worthiness
• Scoring criteria – financial ratios/variables for retail and corporate scoring Exhibit: Sources of Standalone Risk Factor Estimates for Credit Assets
models Excel Exercise: Simulation modelling of potential credit loss distributions
• Regression-based credit ratings models
- Beaver’s financial distress model and predicting failure Day Three
- Altman’s Z-score and Zeta score models using financial ratios
- Ohlson’s Logit bankruptcy model using financial ratios Credit Exposure Factors, Default Likelihoods And Dependent
- Horrigan’s bond ratings prediction model Defaults, Recovery Rates, Credit Spreads, Credit Rating
Migration And Credit Portfolio Risk Exposures
Exhibit: International survey of credit scoring models and associated
explanatory variables Default Likelihood Forecasting And Dependent Defaults
Exhibit: Using scoring models to distinguish between various credit rating • Default frequency models – assumptions and characteristics
grades • Default intensity models, time to default and term structure models of
defaults
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5. • Modelling default probabilities over multiple periods and maturity aging • Reduced-form models based on credit spreads and default likelihoods
effects • Reduced-form models – strengths and limitations
• Commonly used approaches to modelling dependent/conditional defaults
Excel Exercise: Simulation modelling of reduced-form models using credit
Exhibit: McKinsey’s Logit Default Prediction model spreads
Excel Exercise: Simulation modelling of multiple-period defaults and aging
effects Commercial/Vendor Credit Portfolio Risk Models
Excel Exercise: Simulation modelling of dependent default events • Key risk factors affecting parameter specifications for credit portfolio risk
• Best practice for commercial credit portfolio risk platforms, including:
Recovery Rate Modelling - RiskMetrics CreditMetrics® portfolio credit risk model
• Factors affecting recovery rates - Credit Suisse Financial Products (CSFP) CreditRisk+
• Modelling recovery rates - KMV/Moody’s Credit Portfolio Manager™
• Link between default frequencies and recovery rates - McKinsey’s Credit Portfolio View
Excel Exercise: Simulation modelling of loss-given-default with random Exhibit: Commercial credit portfolio models – structural comparisons
recoveries Exhibit: Comparison of commercial credit portfolio models - strengths and
limitations
Credit Rating Migration Probabilities And Transition Matrices Exhibit: Default correlation/dependency in commercial credit portfolio
• Credit ratings migrations – properties of credit quality downgrades and models
upgrades
• Forecasting rating transition frequencies and rating transitions correlations Credit Loss Protection Techniques, Hedging Counterparty Credit
• Limitations of historical estimation of credit migration probabilities Risk, Assessing Credit Concentration Risk, Hedging Credit Risk Using
Credit Derivatives And Credit Derivatives Indices, And Credit Fraud
Excel Exercise: Simulating credit rating transitions using Markov chains Prevention
with multiple credit categories and including a default absorbing state • Common credit loss protection techniques - bills discounting, factoring of
accounts receivables, financial guaranties, Letters of Credit (LoC), credit
Credit Spreads Applications In Credit Risk Modelling insurance, securitisation, collateral and margining and the use of covenants
• Economic factors affecting credit spreads and the expected cost of default • Credit concentration risk – sector and single-name concentration risk and
• Rating-based models for credit spread the Herfindahl-Hirschman index of concentration
• Credit curves and modelling of the term structures of credit spreads • Counterparty credit risk hedging using Credit Valuation Adjustment (CVA)
as a credit adjustment on a positive derivative exposure
Excel Exercise: Simulation modelling of credit spreads • Credit Default Swaps (CDSs), credit derivatives indices and other credit
derivatives – default protection and hedging credit risk
Standalone And Portfolio Credit Risk Assessment Using Credit Value-at • Customer identity verification and preventing fraud in a credit scoring and
Risk (CVaR) rating
• Credit VaR model types – overview and characteristics
- Default Mode models (DM) Basel I, II And III Accords –Evolution Of A Global Regulatory Capital
- Mark-to-Market (MTM) models Standard
• Standalone CVaR – assessing expected and unexpected losses for a risky • Regulatory capital and the Basel I and II accords – overview
credit • Basel II – Pillar I - minimum capital requirements
• Portfolio CVaR – assessing expected and unexpected losses for portfolios • Basel II – Pillar I modelling approaches – I: standardised approach
of credits • Basel II Modelling approaches – II: foundation internal rating based
approach
Excel Exercise: Simulation modelling of portfolio credit risk losses with • Basel II Modelling approaches – III: advanced internal rating-based
random default arrivals, recovery rates, and credit exposures approach
Excel Exercise: Putting it all together – developing Monte Carlo simulation • Basel II Pillar II: supervisory review – overview
models for standalone and portfolio credit VaR forecasts • Basel II Pillar III: market discipline – overview
• Basel III – December 2010 initiative for reforming the global regulatory
Day Four framework
Reduced Form And Structural Credit Models, Commercial Credit Exhibit: Comparing expected and unexpected credit losses, economic risk
Portfolio Risk Models, Credit Loss Protection Techniques, capital, and regulatory capital
Hedging Techniques For Credit Risk Exposures, and Basel I, II
And III Accords The following short case studies related to systemic credit crises
since the 1980s will be discussed during the program
Structural Credit Risk Models And Forecasting Default Times
• Merton (1974) Structural Model – option-theoretic default forecasting Case study – LDC crisis of the early 1980s and the brady bond
model restructuring innovation
- First generation structural-form models and forecasting default at Case study – US saving and loan crisis of the early 1980s
maturity
- Second-generation structural-form models and forecasting default at Case study – Leveraged Collateralised Mortgage Obligations (CMOs) crisis,
any time between issuance and maturity US bond market sell-off of 1994 and mutual funds losses
• Structural credit risk models – strengths and limitations
Case study – Global and national implications and consequences of the US
Excel Exercise: Simulation modelling of time to default using Merton subprime crisis of the late 2000s - implications of prolonged US recovery
(1974) model and the “New Normal” for global markets
Case study – Systemic sovereign debt crises in European Union arising in
Reduced-Form Credit Risk Models And Forecasting Times To Default
the aftermath of the credit crunch and liquidity freeze of the late 2000s
• Reduced form or intensity-based models of credit risk measurement
• Reduced-form models and exogenous factors underlying time to default
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6. Credit Risk Modelling
20 – 23 November 2011 • Kempinski Hotel, Mall of the Emirates, Dubai, UAE
FIVE WAYS TO REGISTER
971-4-3352437 IIR Holdings Ltd.
P.O Box 21743
Dubai, UAE
971-4-3352438
GCS/IIR Holdings Ltd.
P.O Box 13977
register@iirme.com Muharraq
Kingdom of Bahrain
www.iirme.com/creditrisk
DISCOUNTS AVAILABLE
FOR 2 OR MORE PEOPLE
CALL – 971-4-3352483
E-MAIL – a.watts@iirme.com
WEB BC4077
Course Fee Before Course Fee Before
Event Final Fee
11 September 2011 9 October 2011
Credit Risk Modelling
US$ 3,950 US$ 4,450 US$ 4,750
20 – 23 November 2011
Interested in running this course in-house?
Course fees include documentation, luncheon and refreshments. Delegates who attend all sessions will receive a Certificate of Attendance. Please call the Customised Training Solutions Team
on 971-4-3352439 or CTS@iirme.com
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