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Course Outlines

Risk Management

Risk Management Techniques and Basel II-III

Operational Risk and Basel II

Credit Courses

Writing Credit Applications - A Foundation Course

Advanced Credit Analysis and Risk Management

Analysing Banks

Loan Documentation

Loan Markets

Credit and Loan Markets

Consulting and On-Site Training Services

Basel II Operational Risk Framework Design and Build

Basel II Framework Implementation, Compliance and Training

Operational Risk Compliance Review and Gap Analysis

Organizational Structure Design



Validation of Credit Scoring and Rating Systems

This course provides practical knowledge for the validation and monitoring of credit scoring and internal rating systems with a focus on the relevant statistical techniques and tools.

Attendees should have a background in predictive modelling or credit risk management and want to learn more about validating predictive models in the credit risk area, especially in the context of Basel 2.

Dr Hendrik Wagner

Dr Hendrik WagnerFor 9 years Dr Wagner was Product Manager Data Mining Solutions at the SAS Institute covering Europe, Middle East and Africa.

He introduced scorecard development functionality into SAS' flagship data mining solution Enterprise Miner and made it the market leading solution for inhouse scorecard development. He also led the creation of an end-to-end model development, deployment and monitoring solution and defined specific functionality for building internal rating systems for Basel 2 -PD and LGD modeling, pooling and backtesting.

After writing SAS' first Risk Weighted Assets calculation code, he helped launch SAS' market leading Credit Risk Management solution.

He became a consultant in 2006 providing credit risk and internal audit departments with advisory and implementation services, such as readiness assessment, model development and rating system auditing.

Clients include inter alia GHB bank, Thailand, (Housing Loan Application Scorecard), Samlink, Finland, (Behavioral PD Model),Maybank Malaysia( Corporate PD Model Validation), National Australia Group UK, (Retail PD, LGD and EAD Model Validation for Basel2 IRB Approval), Deutsche Telekom Germany (PD model validation and development, early warning system, profit scoring) and BHW Bausparkasse ( PD and LGD model validation of a home loans portfolio).

Dr Wagner holds a doctorate in Computer Sciences.

Part 1: Introduction

  • The Basel Validation Approach
  • Model Design, Data Quality and Use Tests
  • Backtesting and Benchmarking
  • Validation and Monitoring
  • Criteria for Good Validation
  • The Validation Protocol

Part 2: PD Model Validation

  • Validating PD Model Design
    • Design of the Development Data
      • Definition of Default
      • Aggregation Level
      • Use of all Factors
    • Model Type and Development Strategy
      • Sampling
      • Dealing with Erroneous Values
      • Accommodating Non-Linearity
      • Multivariate Modelling
      • Controlling Input Correlation
      • Economic Plausibility
    • Calibration and Pooling
      • Definition of Default-Rate
    • Segmentation
    • Application and Behavioural Models
    • Composite Models
    • Statistical Models and their Environment
    • Model Documentation
      • Development Documentation
      • Development-Time Performance Documentation
      • Availability of development sample
      • Specification for Implementation
  • Backtesting
    • Design of the Validation Data
    • Performance Measures
      • Overall and Pool-Level Calibration
      • Discriminatory Power
      • Stability
      • Backtesting over Time
      • Conservativeness
      • Input Validation
      • Thresholds
  • Systems Validation: The Historical and the Operational View
    • obustness and Transparency of Data Systems
    • The Risk Data Mart
    • Model Implementation and Use

Part 3: LGD Model Validation

  • Validating LGD Model Design
    • Design of the development data
      • Definition of Default
      • Definition of Loss Realized LGD
      • Aggregation Level
      • Use of all Factors
    • Model Type and Development Strategy
      • Segments, Cohorts and Averages
      • Scenarios Cure Rate
      • Recovery Rates and Corrections
      • Downturn LGD
      • Default At Observation
      • Multivariate Approaches LGD Scoring
    • Calibration and Pooling
    • Model Documentation
  • Backtesting
    • Design of the Validation Data
      • Finding predictions and outcomes
      • Aligning collateral level and account level
    • Performance Measures
      • Calibration of Parameters
      • Calibration of Predictions
      • Power of Predictions
      • Stability
      • Conservativeness
  • Systems Validation: The Historical and the Operational View
    • Robustness and Transparency of Data Systems
    • The Risk Data Mart
    • Model Implementation and Use

Course Outlines

Quantitative Analysis

Credit Model Validation

Credit Scoring and Internal Ratings

LGD and EAD prediction

Counterparty Credit Risk: CVA and EPE

Course Outlines

Financial Markets

ACI Dealers Certificate Workshop

ACI Operations Certificate Workshop

Introduction to Financial Markets

Money Market Workshop

Foreign Exchange Workshop

Bonds Workshop

Financial Math Workshop

Introduction to Derivatives

Introduction to Banking

Fundamental Analysis

Treasury Management Workshop

Finance for Non Financial People

Ethics and Compliance

Balance Sheet, asset and Liability Management

Yield Curves