The financial landscape is being reshaped by the emergence of a hybrid lending model, which combines a traditional underwriting with a machine learning and an alternative data. This innovative approach promises a faster and a more accurate credit decision, but it also introduces a new class of a model risk that a traditional framework is not prepared to address. A failure to a properly oversee a hybrid lending model can lead to a significant financial loss, a regulatory fine, and a reputational damage. An effective risk oversight is critical to harnessing a power of an innovative lending while mitigating a potential downside.

This training program is meticulously designed to provide a comprehensive understanding of a risk modeling in a hybrid lending ecosystem. You will learn to move beyond a conventional risk assessment and develop a robust framework that integrates a traditional and an alternative data into your analysis. The curriculum covers everything from an innovative data collection strategy to the role of a machine learning and its associated risks. By the end of this course, you will be equipped to identify, measure, and mitigate a risk in a hybrid lending ecosystem, helping your organization to make a sound financial decision while contributing to a secure and a resilient operation.

Duration: 10 days

Target Audience:

• Risk and credit analysts
• Senior management and business leaders
• Compliance and governance professionals
• Internal and external auditors
• Data scientists and modelers
• Consultants specializing in a risk management
• Anyone interested in the intersection of a finance and a risk management

Objectives:

• Understand the core concepts of a hybrid lending model and its unique risk profile
• Learn to identify and quantify a financial and a non-financial risks
• Master the principles of an integrated risk management framework for a hybrid lending
• Gain proficiency in applying specialized risk assessment techniques
• Understand and mitigate the risks of a data privacy and its implications
• Learn to navigate the regulatory and reporting requirements for a hybrid lending
• Develop skills in communicating and reporting on a hybrid lending risk
• Prepare for a future change in a data and its impact on a risk
• Implement a continuous monitoring system for a hybrid lending
• Learn to use a data and an analytics for a more accurate risk assessment

Course Modules:

Module 1: Foundations of a Hybrid Lending Model

• The history and evolution of a hybrid lending model
• The different types of a hybrid lending model
• The unique risk profile of a hybrid lending model
• The key stakeholders in a hybrid lending model
• The importance of a clear and a consistent definition of "hybrid lending"

Module 2: The Use of a Data and an Analytics

• The importance of a data-driven approach
• The use of a behavioral segmentation
• The role of a customer journey
• The importance of a continuous monitoring
• The challenges of a data availability and a reliability

Module 3: The Role of a Machine Learning

• The importance of a machine learning
• The role of a supervised and an unsupervised learning
• The challenges of an explainable AI
• The importance of a model interpretability
• The impact of a machine learning on a model performance

Module 4: The Use of a Financial Modeling

• The importance of a financial model
• The use of a discounted cash flow
• The challenges of a valuation
• The importance of a clear and a consistent assumption
• The impact of a model on a business decision

Module 5: The Role of a Cross-Functional Team

• The importance of a collaboration between an engineer and a cybersecurity expert
• The role of a communication and a feedback
• The challenges of a different goal
• The importance of a clear and a consistent process
• The impact of a team on a project success

Module 6: The Use of a Digital Twin

• The importance of a digital twin
• The use of a digital twin in a risk assessment
• The challenges of a data synchronization
• The importance of a clear and a transparent model
• The impact of a digital twin on a business process

Module 7: The Role of a Threat Intelligence

• The importance of a threat intelligence
• The role of a threat intelligence in a risk assessment
• The challenges of a data overload
• The importance of a clear and a consistent threat model
• The impact of a threat intelligence on a business decision

Module 8: Stress Testing and Scenario Analysis

• The importance of a stress test
• The use of a hypothetical and a historical scenarios
• The role of a reverse stress test
• The importance of a clear and an actionable result
• The challenges of communicating stress test results to stakeholders

Module 9: The Use of a New Data Source

• The importance of a social media data
• The role of a geospatial data
• The challenges of a satellite imagery
• The importance of a new data source
• The impact of a data source on a risk

Module 10: The Role of a Policy and a Regulation

• The importance of a clear and a consistent policy
• The role of a regulatory compliance
• The challenges of a cross-border regulation
• The importance of a clear and a transparent reporting
• The risks of a non-compliance and a penalties

Module 11: The Use of a Supply Chain Risk Management

• The importance of a supply chain risk
• The role of a vendor management
• The challenges of a third-party risk
• The importance of a clear and a transparent process
• The impact of a supply chain risk on a business

Module 12: The Use of an Incident Response

• The importance of an incident response plan
• The role of a communication and a collaboration
• The challenges of a real-time response
• The importance of a clear and a consistent process
• The impact of an incident on a business

Module 13: The Use of an Innovative Financial Instrument

• The importance of a cyber insurance
• The role of a blockchain
• The challenges of a smart contract
• The importance of a new product
• The impact of a new product on a risk

Module 14: Case Studies and Best Practices

• A deep dive into successful hybrid lending model risk management projects
• The challenges of a real-world implementation
• The importance of a strong cross-functional team
• The role of a leadership in adopting a data-driven culture
• Lessons learned from the field

Module 15: Final Project and Discussion

• A hands-on project to build a hybrid lending model risk framework
• The role of a new technology (e.g., quantum computing)
• The future of a hybrid lending model
• The importance of a continuous learning mindset
• A final discussion on a remaining challenge and an opportunity

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.