Course overview

4 Live Interactive sessions

The PD Modelling workshop offers a focused and practical learning opportunity for credit risk professionals interested in Probability of Default modelling.

Attendees will gain essential knowledge on techniques to develop accurate PD models, understand data requirements, and validate the models effectively. This workshop is designed for credit analysts, risk modelers, and deci-sion-makers aiming to enhance their credit risk assessment capabilities and optimise lending decisions.

Who should enroll

This workshop comes with many Excel worked examples and case studies re-inforce key as to demonstrate and reinforce key aspects.

It is recommended that delegates have a good knowledge of the Excel functions required for financial modelling

  • Credit Risk Analysts

  • Risk Modelers and Quantitative Analysts

  • Credit Officers and Credit Managers

  • Data Analysts

  • Credit Portfolio Managers

Topics covered

Over 4 Live Interactive sessions for three hours each, the facilitator will cover the following topics

  • Introduction to probability of default modelling

    *Definition of Probability of Default (PD)
    *Why PD modelling is important in finance.
    *Overview of PD modelling techniques.

  • Data collection and preparation

    *Sources of data for PD modelling
    *Data cleaning and pre-processing techniques.
    *Variable selection and feature engineering.

  • Statistical methods for PD modelling

    *Linear Regression.
    *Logistic Regression.
    *Discriminant Analysis.
    *Decision Trees.

  • Model evaluation and validation

    *Model selection and comparison.
    *Overfitting and underfitting.
    *Model evaluation metrics (e.g., AUC, accuracy).
    *Model validation techniques.

  • Advanced topics in PD modelling

    *Time-series analysis for PD modelling.
    *Model interpretability and fairness.

  • Case studies and practical applications

    *Application of PD modelling in credit risk management.
    *Real-world examples and applications in finance and banking.
    *Hands-on project using a real-world dataset.

Course curriculum

    1. Course Material for Session 1

    2. LIVE SESSION 1|| 16 November 2023

    3. RECORDING | 16 November 2023

    1. Course Material for session 2

    2. LIVE SESSION 2 || 23 November 2023

    3. RECORDING | 23 November 2023

    1. Course Material for session 3

    2. RECORDING | 30 November 2023

    1. Course Material for session 4

    2. RECORDING | 07 December 2023

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About this course

  • $699.00
  • 12h of live facilitator led sessions
  • Supporting workbooks & slides
  • Access replays and course materials for 30 days after last live session

Instructor

Who you will learn with

Wade Gunning

Course Director

Wade obtained his BComm degree at Stellenbosch University before going on to complete an Honours degree in Financial Analysis and Portfolio Management at the University of Cape Town. Wade completed his Masters in Financial Engineering (cum laude) in the Department of Mathematics and Applied Mathematics at the University of Pretoria.

He is a freelance contractor, working as a quant analyst and consultant for EY Johannesburg, RiskWorx, and Yara International where has completed several successful audits and model validations on financial institutions' IFRS9 models, built and implemented credit risk scorecards, and set up and calibrated credit pricing tools and IFRS9 ECL valuations for local (South African) and Middle Eastern (Jordan and Saudi Arabia) banks. He is currently studying in the US.

Social proof: testimonials

“It was very insightful and has a ton of key lessons to pick up from and utilize in the real world.”

Olerile Segaetsho | FNB Botswana

“Go for it. A wealth of knowledge awaits you.”

Grace Newa | KCB Group

“Fantastic course, would definitely recommend.”

Gachara Ng’ang’a | Stanbic IBTC

“Truly beneficial. Andrew is an encyclopedia ”

Karabo Lekwana | Rand Merchant Bank

“Very detailed and informative. The facilitator knows his subject matter.”

Rael Ndinda Mukiti | KCB Group