Training on AI Applications in Banking Regulation and Monetary Policy Using Llama 3
Learn to apply AI and Llama 3 in banking regulation and monetary policy through hands-on technical training.
Next intake
20 Jul 2026 · Nakuru
Duration
5 days
Live instruction
Delivery
Physical + Virtual
Cohort based
Level
Advanced
Working professionals
Certification
NITA reimbursable
For Kenyan cohorts
Language
English
All materials
About this programme
This intensive course equips participants with practical skills in applying Artificial Intelligence, including Llama 3 models, to strengthen banking regulation, compliance monitoring, and monetary policy analysis. Participants will explore how AI can support regulatory reporting, risk detection, policy simulations, and data driven decision making within financial institutions and regulatory environments.
Through demonstrations, case studies, and hands on practical sessions, the program combines AI fundamentals with real world financial applications. Participants will gain experience using Llama 3 for regulatory text analysis, compliance automation, financial risk monitoring, and policy evaluation strategies.
Duration
5 Days
Who Should Attend
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Central bank officials and regulators
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Financial risk and compliance professionals
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Economists and monetary policy analysts
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Data scientists and AI engineers in finance
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Banking sector IT and innovation managers
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Policy researchers and financial consultants
What you'll walk away with
By the end of this training, participants will be able to:
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Understand AI and large language models (LLMs) in financial regulation.
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Use Llama 3 for analyzing regulatory texts and monetary policy documents.
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Apply AI models for systemic risk detection and compliance monitoring.
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Simulate monetary policy outcomes using AI-powered data modeling.
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Evaluate real-world case studies of AI in central banking and regulatory contexts.
What we cover, module by module
Module 1: Introduction to AI in Banking Regulation & Monetary Policy
- AI landscape in financial governance
- Role of large language models (LLMs) in compliance and regulation
- Overview of modern AI architectures (e.g., LLMs like Llama 3)
- Case Study: Adoption of AI in regulatory oversight by central banks
- Practical: Identifying AI use cases in regulatory and policy environments
Module 2: Natural Language Processing (NLP) for Regulatory Texts
- Parsing and summarizing complex financial regulations
- Automating compliance checks using AI models
- NLP tools for regulatory analysis
- Case Study: Automating regulatory reporting and compliance review
- Practical: Analyzing and summarizing regulatory documents using AI tools
Module 3: AI for Risk Detection & Compliance Monitoring
- Identifying systemic and institutional risks using AI
- Fraud detection and early warning systems
- AI-driven compliance monitoring frameworks
- Case Study: AI-based risk detection in financial institutions
- Practical: Designing a risk monitoring and alert system
Module 4: AI Applications in Monetary Policy
- Forecasting macroeconomic indicators using AI
- Scenario simulation and policy modeling
- AI-assisted analysis of inflation and interest rates
- Case Study: Central bank use of AI in economic forecasting
- Practical: Developing an AI-supported macroeconomic analysis model
Module 5: Implementation, Governance & Strategic Application
- Real-world AI applications in central banks and regulators
- Ethical considerations, explainability, and data governance
- Implementation challenges and best practices
- Case Study: AI-driven regulatory transformation in financial institutions
- Practical: Designing an AI-driven regulatory and monetary policy framework
Where the change lands
Organizational Impact
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Enhanced capacity in applying AI for regulatory compliance
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Improved detection of systemic financial risks
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Data-driven support for monetary policy formulation
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Strengthened adoption of emerging technologies in financial governance
Individual Impact
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Practical skills in using Llama 3 for regulatory and economic analysis
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Improved understanding of AI’s role in banking supervision
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Hands-on ability to build AI-powered models for policy insights
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Competitive advantage in AI-driven financial regulation
Dates and locations
Upcoming intakes
Every intake is limited to a small cohort. Booking closes when a date fills or three weeks before the start, whichever comes first.
| City | Starts | Ends | Delivery | Book |
|---|---|---|---|---|
NakuruNext | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Kigali | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Accra | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Kisumu | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Johannesburg | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Dakar | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
- NakuruNext
20 Jul → 24 Jul·In-Person
Book this intake - Kigali
20 Jul → 24 Jul·In-Person
Book this intake - Accra
20 Jul → 24 Jul·In-Person
Book this intake - Kisumu
27 Jul → 31 Jul·In-Person
Book this intake - Johannesburg
27 Jul → 31 Jul·In-Person
Book this intake - Dakar
27 Jul → 31 Jul·In-Person
Book this intake
Common questions.
Still not sure? Send us a note and a facilitator will get back to you within a business day.
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Course finder
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For corporate teams
Training 10+ professionals?
We deliver Training on AI Applications in Banking Regulation and Monetary Policy Using Llama 3 in-house at your offices, at a venue we arrange, or fully virtual. Customise the curriculum against your KPIs, and get a bespoke price for the cohort size you need.