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Credit Risk Modelling
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Credit Risk Modelling
  • Overview
  • Objectives & Outline
  • Methodology
  • Participant Profile
  • Trainer
  • Overview
    PROGRAMME DETAILS

    DATE

    27 May 2019

    TIME

    9:00 AM – 5:00 PM

    VENUE

    Asian Banking School

    8

    AICB
    CPD HOURS
    Modeling credit risk for both retail (individual) and corporation credit is vital for financial institutions, as well as non-financial institutions involved in providing credit facilities. The probability that a debtor will default is a key component in getting to measure credit risk. Various credit risk models especially types that are often used in the credit scoring context, logistic regression and decision trees will be covered in this programme.
    LEARNING LEVEL

    Advanced

    PROGRAMME FEE

    AICB MEMBER

    MYR

    1,500*

    / PAX

    NON-MEMBER

    MYR

    1,800*

    / PAX

    *Subject to 6% Service Tax

  • Objectives & Outline
    LEARNING OBJECTIVES
    By the end of the programme, participants will be able to:
    • Explain the components of credit risk evaluation
    • Describe, compare and contrast various credit risk mitigants and their role in credit analysis
    • Compare and contrast quantitative and qualitative techniques of credit risk evaluation
    • Compare the credit analysis of consumers, corporations, financial institutions and sovereigns
    • Describe quantitative measurements and factors of credit risk, including probability of default, loss given default, exposure at default, expected loss and time horizon 
    PROGRAMME OUTLINE

    Classifications and Key Concepts of Credit Risk
    • Describe classifications of credit risk and their correlation with other financial risks
    • Define default risk, recovery risk, exposure risk and calculate exposure at default
    • Explain expected loss, unexpected loss, VaR and concentration risk, and describe the differences among them

    Credit Scoring Models
    • Describe the experts-based approaches, statistical-based models and numerical approaches to predicting default
    • Exploring credit models which incorporate qualitative characteristics into quantifiable models, such as logistic regression models
    • Describe the application of a logistic regression model to estimate default probability

    Structural Models
    • Describe linear discriminant analysis (LDA), define the Z-score and its usage, and apply LDA to classify a sample of firms by credit quality
    • Distinguish between the structural approaches and the reduced-form approaches to predicting default
    • Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model
    • Define and interpret cluster analysis and principal component analysis
    • Describe the application of heuristic approaches, numeric approaches and artificial neural networks in modelling default risk and define their strengths and weaknesses

    Evaluating a Credit Risk Model
    • Evaluate and compare the results obtained through several credit risk models
    • Apply the Receiver Operant Condition method to establish credit threshold
    • Model validation approaches

  • Methodology

    Instructor-led workshops

  • Participant Profile
    Financial reporting accountants, auditors, regulators, financial risk managers and finance managers
  • Trainer

    David Meow

    David has more than 20 years of experience in areas that include business valuation, financial markets and risks, and financial reporting. His exposures in diverse areas in the capital markets as well as being a Chartered Financial Analyst (CFA) holder and a qualified Chartered Accountant (Malaysia), allows him to offer training and consultancy services in areas like investment management and company valuation. He has provided training and consultancy services to government-related and regulatory bodies including Bank Negara Malaysia, Permodalan Nasional Berhad, Securities Commission Malaysia, Kumpulan Wang Simpanan Pekerja and Jabatan Perdana Menteri, as well as financial institutions like Maybank, CIMB, OCBC and RHB.
    He is currently associated with the Securities Commission Malaysia on several development projects and in several programmes initiated by Permodalan Nasional Berhad Institute. He is also the Lead Moderator for the capital markets with the Financial Accreditation Agency (FAA).

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