Introduction

The rapid digitization of financial services has created new avenues for innovation and accessibility, but it has also introduced sophisticated methods for committing loan fraud. As fraudsters become more adept at manipulating digital documents and exploiting vulnerabilities in online systems, traditional fraud detection methods are proving to be inadequate. Digital forensics provides a crucial line of defense by enabling financial institutions to meticulously analyze electronic evidence, trace fraudulent activities, and build a solid case for prosecution. This course is designed to equip you with the essential skills to combat these modern threats effectively.

This comprehensive program will guide you through the principles and practices of digital forensics tailored specifically for the financial sector. You will learn how to identify, collect, and preserve digital evidence from a variety of sources, including email communications, a variety of documents and transaction logs. The course will also cover the latest tools and techniques for analyzing this evidence to uncover hidden patterns of fraud, from identity theft to synthetic identities and sophisticated document forgery. By the end of this training, you will be proficient in using advanced forensic techniques to protect your institution from financial loss and maintain the integrity of your lending operations.

Duration: 10 Days

Target Audience

• Financial risk analysts
• Credit risk managers
• Fraud investigators
• Regulatory compliance officers
• Cybersecurity professionals
• Internal and external auditors
• Legal and compliance officers
• Financial technology (fintech) professionals
• Law enforcement personnel
• Anti-money laundering (AML) officers

Objectives

• Understand the core concepts of digital forensics and its risks.
• Master the principles of a fair and transparent investigation.
• Analyze the key metrics in a digital forensics investigation.
• Learn to build and validate advanced forensic models.
• Use quantitative tools for fraud detection.
• Understand the regulatory framework governing these practices.
• Develop a framework for digital forensics analysis.
• Assess the impact of digital fraud on a lending portfolio.
• Understand the ethical implications of financial transactions.
• Use machine learning for predictive modeling.

Course Modules

Module 1: Foundations of Digital Forensics

• The importance of a transparent and fair investigation
• The unique challenges of digital banks
• The difference between traditional and algorithmic lending
• The role of technology in lending risk
• The impact of a changing economic environment

Module 2: Defining and Measuring Fraud

• The principles of a fair investigation
• The use of internal and external data
• The role of decentralized finance (DeFi)
• The challenges of working with limited historical data
• The use of data visualization tools

Module 3: Data and Analytics for Fraud Detection

• 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 Fraud Detection

• 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 Fraud Detection

• 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 digital banks
• The legal challenges of cross-border transactions
• The importance of a robust compliance program
• The ethical implications of financial transactions

Module 8: Fraud Mitigation Strategies

• The types of fraud mitigation instruments
• The use of credit insurance
• The importance of a robust fraud mitigation strategy
• The challenges of implementing a dynamic fraud mitigation program
• The role of derivatives in managing risk

Module 9: Portfolio Fraud Management

• The concept of portfolio fraud 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 lending portfolio 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 digital forensics model for a chosen asset
• Using the model to evaluate a sample of transactions
• 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 lending 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 lending
• The role of AI in risk assessment
• The evolution of lending instruments
• The impact of new data sources on risk assessment
• The future of lending risk

Module 14: Case Studies

• A case study of a major digital bank
• A case study of a fintech'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

Module 16: Additional Tools and Techniques

• An introduction to model explainability tools
• The use of counterfactual explanations
• The importance of a human-in-the-loop
• The challenges of using these tools in production
• The future of ethical AI

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.