Credit Risk Analysis, Modelling and Management Certification Course - Rcademy (2024)

Why select this training course?

Analysis, modelling, and management of credit risk are no longer just for banks and other financial institutions. Small businesses and individuals can also use them. However, growing competition and statutory/legislation requirements will hurt any organisation that doesn’t pay attention to risk management. All firms need a strong credit assessment, modelling, and management system to manage credit risk. Risk management efficiently identifies, measures, manages and implements a risk management model. Most risk management strategies have greatly boosted consumer credit growth if done effectively. Most organisations cannot grant clients credit without models, new tools, and procedures. The need for a risk management model is now universally acknowledged by all parties involved in a company.

What is credit risk analysis?

Credit risk analysis evaluates the likelihood of default by aborrower and the potential loss to a lender or creditor if a default occurs. This involves analysing various financial and non-financial factors, such as the borrower’s credit history, income, and debt-to-income ratio, to determine the risk associated with lending money to them. Credit risk analysis aims to minimise potential losses to the lender while also providing credit to those who need it. The outcome of credit risk analysis is usually expressed as a credit score or a rating that indicates the borrower’s creditworthiness.

What are the key elements in credit risk analysis?

The key elements in credit risk analysis are:

• Borrower Information
• Financial Statements
• Debt-to-Income Ratio
• Credit Score
• Collateral
• Market and Economic Conditions
• Historical Default Rates

The Credit Risk Analysis, Modelling and Management Certification Course by Rcademy will give participants a thorough understanding of how to analyse and develop models that will be used in effective risk management. Quantitative modelling tools, such as the credit scoring tool developed by large-scale retailers to aid in portfolio risk management, have been applied to different types of assets. Now that we have data and algorithms to process that data, getting useful insights has become a breeze. Computing technology has also spurred the growth and application of rigorous statistical modelling approaches that underpin risk analysis, modelling, and management. Participants will understand the foundational building blocks of risk analysis, modelling, and management by studying quantitative and judgmental risk management methods, which are essential to modern risk management techniques.

Who should attend?

The Credit Risk Analysis, Modelling and Management Certification Course by Rcademy will be ideal for the following professionals:

• Credit risk analysts
• Internal auditors
• Accounts receivable and collection managers
• Executives of the credit department
• Credit portfolio risk managers
• Fund managers
• Balance sheet managers
• Back and middle office managers
• Liability managers
• Assets officers
• Any other interested professional

What are the course objectives?

The main aims of the Credit Risk Analysis, Modelling and Management Certification Course by Rcademy are to enable participants to:

• Understand different measures of credit risks effectively
• Discover various methods of reduced-form models development
• Apply the learnt knowledge to develop parameter specifications
• Understand the term structure of credit spread
• Develop structural models
• Analyse traditional credit models such as credit scoring and credit rating to understand their weaknesses and strengths
• Learn about different methods of credit risk assessment and modelling
• Learn about the regulatory and legislative requirements for credit risk management
• Understand the design of various credit models
• Develop common assessment methods
• Get hands-on experience in designing, monitoring, and managing risk assessment models
• Understand and project cash flow cycles and borrower’s working capital funding gap
• Define different loan covenants and recommend the appropriate use

How will this course be presented?

Rcademy designs, develop and maintains high-quality courses using the industry’s best professionals with vast experience in teaching and their respective industries. This course will be presented using the following methods:

1. Lecture notes
2. Presentational videos
3. Exercises and examples
4. Case studies

What are the topics covered in this course?

Module 1: Introduction

• Measures of credit risk modelling
• Balance sheet
• Regulations
• Role of banks
• Sources of risks
• Financial products

Module 2: Credit Scoring

• Score types
• Overrides
• Methodologies
  – Traditional credit scoring methods
  – Machine learning in credit scoring
  – Models used in credit scoring
  – Generalised additive models
  – Gradient boosting
  – Support vector machines in credit scoring
  – Using k-means clustering
  – Random forest
• Risks, challenges, and opportunities
• Regulations and oversight
• Model-agnostic interpretability method
  – Local interpretable model
  – Individual conditional expectation plots
  – Global surrogate models
  – Partial dependency plots
• Transparency and disclosure

Module 3: Risk Modelling

• Factors affecting credit risk modelling
  – Loss given default
• Types of risks
  – Market risks
  – Credit risks
  – Operational risks
• The Bernoulli model
  – Uniform default probability
  – Mixture model
  – Uniform correlation
• Exposure at default
• The KMV-model
• Probability of default
• Credit portfolio view
• Dynamic intensity models
• The Poisson model
• Copula functions in loss distribution
• One-factor/sector models
• Example in asset correlations

Module 4: Risk Management

• Expected loss
  -Ratings
  – Default probabilities and calibration
• Unexpected loss
  – Monte Carlo simulation of losses
  – Economic capital
  – Analytical approximation
  – Basel initiative and regulatory capital

Module 5: Credit Derivatives

• Credit-linked notes
• Credit default services and products
• Credit actual spread products
• The total book on return swaps
• Basket spread products

Module 6: Debt Obligations

• Collateralised debt obligations (CDO)
• CDO structure
• Modelling in CDO
• Rating agency models: Moody’s BET
• Typical cash flow
• Interest coverage tests
• Capital relief
• Funding in better conditions
• Multi-step models
• Arbitrage spreads opportunities

Module 7: Credit Analysis

• Early warning checklist in credits
• Credit modelling
• Metrics for evaluation
• Black-Scholes partial differential functions
• Credit analysis models

Module 8: Default Probability and Term Structure

• Actual default probabilities
• Exponential term structure
• Migration technique
• Risk-neutral
• Q-matrices
• Direct calibration of multi-year probabilities
• Contributory capital
  – Capital allocations
  – Varian approach
  – Expected shortfall
  – Value at risk
• Case study

Module 9: Asset Value Model

• Transforming equity into asset value
  – Ito Formula “light”
  – Asset value from equity values
• Merton’s asset value model
• Put and call options
• Option theoretic model
• Geometric Brownian motion

Module 10: Portfolio Models for Credit Risk

• Measures of portfolio risk
• Portfolio risk model formulation
• Economic capital and capital allocation
• Correlation and concentration
• Basel II portfolio model
• Loss distribution
• Implementation and application
• Overview of industry models

Module 11: CreditRisk+ Model

• Sector model
• Independent obligators
• Sector convolution
• Default distribution
• Modelling framework of credit risk