AI Governance for Financial Services in Africa

AI governance

AI Governance for Financial Services in Africa

  • Pacfaie Courses
Course menu
Module 1: AI fundamentals for financial services professionals
  • Welcome: AI governance for financial services and how this course works
  • What AI is (and isn’t) in a bank or fintech
  • How a credit model learns
  • The AI lifecycle in a financial institution
  • Generative and agentic AI in financial services
  • How AI fails
  • Measuring performance: why accuracy can mislead
  • The Africa lens and ten questions to ask
  • Module 1 quiz
Module 2: AI across African financial services
  • Where AI sits across financial services
  • Mobile money and digital lending
  • Banks, microfinance and SACCOs
  • Fintech partnerships, embedded finance and open banking
  • Capital markets, asset management and pensions
  • Mapping opportunity and harm
  • Module 2 quiz
Module 3: Ethics, fairness and financial inclusion
  • Responsible AI principles for financial institutions
  • What fairness means in lending
  • Measuring fairness in credit
  • Responsible financial inclusion
  • Transparency, explanation and human review
  • Vulnerable customers, debt and collections
  • Module 3 quiz
Module 4: Financial services AI regulation in Africa
  • The regulatory landscape for AI in African finance
  • Data protection, credit reporting and AI
  • What financial supervisors expect
  • International laws and standards that reach African institutions
  • Mapping obligations for an AI use case
  • Assignment 1: A regulatory obligations map
  • Module 4 quiz
Module 5: Building an AI governance framework for financial institutions
  • What an AI governance framework is for
  • Roles, committees and three lines of defence
  • The AI inventory
  • Risk tiering
  • Proportionate controls for each tier
  • Governance for MFIs, SACCOs and fintechs
  • Module 5 quiz
Module 6: Data governance, privacy and alternative data
  • Data quality and representativeness
  • Alternative data for credit
  • Lawful basis, consent and partner data
  • Data protection impact assessments for financial AI
  • Credit bureaus, cloud and cross-border data
  • Privacy and security techniques for financial AI
  • Module 6 quiz
Module 7: Fair and explainable credit decisions
  • How AI is changing credit decisions
  • Proxy discrimination in credit
  • Affordability and responsible lending
  • Pricing, limits and cost transparency
  • Explaining credit decisions
  • A method for fair lending reviews
  • Assignment 2: A fair lending review
  • Module 7 quiz
Module 8: Model risk management for AI
  • What model risk is, and how AI changes it
  • Development standards and documentation
  • Independent validation of AI models
  • Validation challenges in African markets
  • Approval, change and overrides
  • Validating vendor and generative AI
  • Module 8 quiz
Module 9: Financial crime, fraud and AML
  • AI in AML and counter-terrorist financing
  • False positives, de-risking and exclusion
  • Fraud detection and scams
  • Identity, screening and deepfakes
  • Tipping off, accountability and AI-drafted reports
  • Governing financial crime AI
  • Module 9 quiz
Module 10: AI policy, procurement and shadow AI
  • Putting up an organisational AI policy
  • Drafting, approving and rolling out the policy
  • Buying AI: procurement and outsourcing
  • AI clauses in vendor contracts
  • Shadow AI in financial institutions
  • Responding to shadow AI
  • Writing acceptable-use rules for generative AI
  • Assignment 3: AI policy, procurement and shadow AI
  • Module 10 quiz
Module 11: Monitoring, evaluation and compliance assurance
  • Monitoring AI in use
  • Drift and AI incidents
  • Evaluating whether AI delivered
  • Internal compliance assurance
  • Three lines in practice and auditing AI
  • Reporting, inspection readiness and improvement
  • Assignment 4: A monitoring and compliance assurance plan
  • Module 11 quiz
Module 12: Final exam and capstone
  • Putting it all together: a 12-month roadmap
  • Final exam
  • Capstone: an AI governance programme for Savanna Financial Group
  • Where to go from here
Length
About 45 hours, self-paced
Lessons
87
Language
English

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Across Africa, AI now decides who gets a loan on their phone in minutes, which transactions are blocked as suspicious, and what a bank’s chatbot tells a customer at midnight. Done well, it can bring credit, savings and insurance to millions of people banks have never served. Done badly, it can lock people out, trap them in debt, and break the law at scale. This course trains financial services professionals to govern AI so it does the first and not the second.

Who it’s for

Risk, compliance, AML and legal officers, credit managers, model validators, product and data teams at banks, microfinance institutions, SACCOs, mobile money providers, digital lenders, fintechs, asset managers and pension funds, as well as internal auditors and financial supervisors. No technical background or coding is needed: everything is built up from first principles, with financial services examples throughout.

What you’ll be able to do

  • Explain how machine learning, generative AI and AI agents work in financial services, and how they fail.
  • Map where AI is used across banking, mobile money, digital lending, fintech, capital markets and pensions.
  • Apply fairness and financial inclusion principles to credit, pricing and customer treatment.
  • Identify the data protection, central bank, consumer credit and AML rules that apply in African markets, and international standards such as Basel and FATF expectations and ISO/IEC 42001.
  • Design an AI governance framework for a financial institution, and manage AI model risk.
  • Make credit decisions fair and explainable, and govern AI in fraud and AML.
  • Write an organisational AI policy, run risk-based AI procurement and bring shadow AI under control.
  • Monitor and evaluate AI systems in use and provide internal compliance assurance.

How it works

Twelve modules, about 45 hours in total, including assignments and the capstone, at your own pace. Each module mixes short readings with interactive practice set in fictional African banks, lenders and fintechs: scenarios, audits, sorting and policy-building. Practice is never marked.

Assessment: a quiz after each module, four applied assignments marked against a published rubric, a timed final exam, and a capstone in which you design AI governance for a fictional African financial group, with peer review and assessor marking.

Certificate

Complete every step to earn the Certificate in AI Governance for Financial Services, a verifiable digital certificate and Open Badge. Your capstone result (pass, merit or distinction) is shown on it.

Certificate and badge

Completed twelve modules covering AI fundamentals, AI across African financial services, fairness and financial inclusion, financial AI regulation in Africa, governance frameworks, data governance, fair and explainable credit, model risk management, financial crime and AML, AI policy, procurement and shadow AI, and monitoring, evaluation and compliance assurance; passed every module quiz, four rubric-marked applied assignments and a timed final exam; and completed an assessor-marked capstone.

Instructor

  • Pacfaie Courses
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