Introduction

In an era of increasing financial scrutiny and macroeconomic volatility, accurate and forward-looking loan loss provisioning is no longer a mere accounting exercise—it's a strategic imperative. The shift from traditional incurred loss models to more sophisticated expected loss frameworks, such as IFRS 9 and CECL, requires a deep understanding of complex statistical models and predictive analytics. Mastering these advanced techniques is crucial for financial professionals to ensure balance sheet stability, meet regulatory requirements, and make informed decisions about credit risk. This course is designed to provide you with the strategic insights and practical tools to effectively navigate this new frontier of financial modeling.

This comprehensive program provides a deep dive into the theoretical and practical aspects of loan loss provisioning. You will explore the interconnected nature of these fields, learning to assess the unique risks inherent in different loan portfolios and the nuances of various provisioning methodologies. The course emphasizes the quantitative and qualitative tools required to analyze a portfolio's financial health, from advanced econometric models to machine learning-based forecasting. By the end of this training, you will be proficient in using advanced analytics to make smarter decisions, manage credit risk, and unlock significant value in your financial institution's risk management activities.

Duration: 10 Days

Target Audience

• Financial risk analysts
• Credit risk managers
• Financial model developers
• Data scientists
• Regulatory compliance officers
• Internal and external auditors
• CFOs and other senior finance executives
• Investment fund managers
• Financial technology (fintech) professionals
• Business development officers

Objectives

• Understand the core concepts of loan loss provisioning.
• Master the principles of IFRS 9 and CECL.
• Analyze the key risk variables in a loan portfolio.
• Learn to build and validate advanced provisioning models.
• Use quantitative tools for portfolio optimization.
• Understand the regulatory framework governing these practices.
• Develop a framework for loan loss provisioning.
• Assess the impact of macroeconomic shocks on a loan portfolio.
• Understand the ethical implications of provisioning.
• Use machine learning for predictive modeling.

Course Modules

Module 1: Foundations of Loan Loss Provisioning

• The importance of provisioning in financial reporting
• The unique challenges of provisioning
• The difference between incurred and expected loss models
• The role of technology in provisioning
• The impact of a changing economic environment

Module 2: IFRS 9 and CECL

• The principles of IFRS 9
• The principles of CECL
• The differences and similarities between IFRS 9 and CECL
• The challenges of implementing these standards
• The impact on financial institutions

Module 3: Data and Analytics for Provisioning

• The importance of a clean and reliable dataset
• The use of internal and external data
• The role of alternative data
• The challenges of working with limited historical data
• The use of data visualization tools

Module 4: Econometric Models for Provisioning

• The principles of an econometric model
• The use of time series analysis and regression
• The importance of a reliable dataset
• The validation and back-testing of models
• The challenges of working with limited historical data

Module 5: Machine Learning for Provisioning

• The principles of a machine learning model
• The use of statistical methods and machine learning
• The importance of a reliable dataset
• The validation and back-testing of models
• The challenges of working with limited historical data

Module 6: Scenario Analysis and Stress Testing

• The concept of scenario analysis
• The role of stress testing in risk management
• The benefits for both lenders and regulators
• The importance of a robust technology platform
• The challenges of implementing these solutions

Module 7: The Regulatory and Legal Landscape

• An introduction to key financial regulations
• The role of regulators in overseeing provisioning
• The legal challenges of cross-border transactions
• The importance of a robust compliance program
• The ethical implications of financial transactions

Module 8: Hedging and Mitigation Strategies

• The types of hedging instruments for loan loss risk
• The use of credit insurance
• The importance of a robust hedging strategy
• The challenges of implementing a dynamic hedging program
• The role of derivatives in managing risk

Module 9: Portfolio Risk Management

• The concept of portfolio risk management
• The role of diversification in reducing risk
• The types of portfolio optimization techniques
• The importance of a data-driven approach
• The challenges of a rapidly changing market

Module 10: Capstone Project Part 1: Design

• Defining a specific portfolio of loans for modeling
• Mapping the data requirements and model architecture
• Outlining the key technical and analytical requirements
• Creating a detailed project plan
• Presenting the design to a mock review board

Module 11: Capstone Project Part 2: Development

• Implementing a loan loss provisioning model
• Using the model to evaluate a sample of loans
• Analyzing the model's performance on key metrics
• Building a presentation to explain the analysis
• Documenting all assumptions and data sources

Module 12: Capstone Project Part 3: Presentation

• Presenting the full analysis of the chosen loan portfolio
• Discussing the risks and benefits of the model
• Proposing a plan for model improvement
• Q&A and peer feedback session
• Receiving expert recommendations and insights

Module 13: Emerging Trends

• The use of blockchain in provisioning
• The role of AI in risk assessment
• The evolution of lending instruments
• The impact of new data sources on risk assessment
• The future of provisioning

Module 14: Case Studies

• A case study of a major bank's provisioning division
• A case study of a microfinance institution's risk management
• A case study of a financial institution's regulatory challenges
• The lessons learned from past credit cycles
• The importance of a robust framework

Module 15: Course Certification

• A final comprehensive assessment
• A final review of key concepts and objectives
• Issuance of a certificate of completion
• Post-course career guidance and networking
• A final Q&A with instructors

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.