Strategic AI Fundamentals for Banking

Program Description

RATIONALE

Artificial Intelligence is reshaping Ghana’s banking and financial services sector — from AI driven credit scoring to real time fraud detection and chatbot based customer service. However, adoption is not without challenges: Regulatory compliance, Ethical risks such as algorithmic bias, opaque decision making, and privacy breaches, and Organizational readiness gaps — many institutions face resistance to change, lack of AI literacy, and uncertainty about job security. This course equips decision makers to strategically plan, evaluate, and govern AI initiatives that are compliant, ethical, and aligned with Ghana’s financial sector realities.

LEARNING OBJECTIVES 

• Explain AI fundamentals and their relevance to Ghana’s banking sector.
• Identify high impact AI use cases in compliance, risk management, and customer engagement.
• Map AI initiatives to Bank of Ghana regulatory requirements and the Data Protection Act.
• Evaluate ethical risks (bias, transparency, accountability) and apply mitigation tools such as Explainable AI (XAI) and bias detection frameworks.
• Design a high level AI adoption roadmap that includes governance, change management, and staff upskilling.
• Integrate local case studies to illustrate AI’s benefits and pitfalls in Ghana’s financial ecosystem.

COURSE CONTENTS

Module 1: The AI Landscape

o   What AI is (and isn’t) — AI vs. Machine Learning vs. Automation

o   Global AI trends and market impact

o   AI adoption in Africa & Ghana — key statistics and examples

Module 2: Strategic Relevance of AI

o   AI as a driver of competitive advantage

o   AI in digital transformation roadmaps

o   Banking & finance use cases: fraud detection, credit scoring, RegTech, customer analytics

Module 3: Fundamentals for Decision Makers

o   Core AI concepts: data, algorithms, models, training, inference

o   Types of AI: Narrow AI, Generative AI, Predictive AI

o   Capabilities and limitations — what AI can and cannot do

Module 4: Ghanaian Banking Sector Context

o   Bank of Ghana directives relevant to AI (e.g., cybersecurity, AML/CFT compliance)

o   Data Protection Act 2012 (Act 843) — implications for AI projects

o   Local infrastructure and data readiness challenges

Module 5: Identifying AI Opportunities    

o   Framework for spotting high value AI use cases

o   Aligning AI initiatives with business goals and regulatory requirements

o   Case study: AI driven SME credit scoring in Ghana

Module 6: AI Risks, Ethics & Governance

o   Governance, Risk & Regulation

o   Data privacy: GDPR, Ghana Data Protection Act

o   ISO/IEC 27001 & ISO/IEC 38505-1 for AI governance

o   Ethical AI: bias, fairness, transparency

o   Group exercise: Risk assessment for AI-powered banking services

o   Panel discussion: Aligning AI adoption with Bank of Ghana directives

Module 7: Building an AI Strategy

o   Components of an AI strategy: vision, governance, data, talent, partnerships

o   AI maturity models — assessing organizational readiness

o   Change management and staff upskilling

Module 8: Measuring AI Impact

o   KPIs for AI projects (ROI, efficiency gains, risk reduction)

o   Proof-of-concept vs. full scale deployment

o   Continuous monitoring and improvement

Module 9: Local Case Studies & Group Discussion

o   Fraud detection in mobile money transfers

o   Chatbot deployment for customer service

o   RegTech compliance monitoring

o   Group exercise: Map a potential AI use case to compliance and ethics requirements

Module 10: Action Planning

o   Steps to initiate an AI project in your organization

o   Stakeholder engagement strategies

o   Building a cross functional AI governance team

Module 11: Wrap Up & Assessment

o   Summary of key takeaways

o   Q&A session

o   Post course assessment or reflection activity