Course Outline
Artificial Intelligence in the FinTech Landscape
- Evolution of FinTech: from digitization to intelligent systems
- Where AI generates value: personalization, automation, and fraud detection
- Case studies from innovative banks and AI-first platforms
Open Banking and API Infrastructure
- PSD2, Open Finance, and global Open Banking frameworks for government
- APIs for account aggregation, payments, and data services in the public sector
- Building and testing API integrations using Postman for government applications
Machine Learning for FinTech Innovation
- Supervised and unsupervised machine learning for credit assessment, Know Your Customer (KYC) processes, and recommendation engines in financial services
- Data sources in FinTech: transaction streams and behavioral data for government use
- Designing low-latency machine learning pipelines for real-time decision-making in the public sector
Conversational AI and Embedded Finance
- Utilizing large language models (LLMs) and chatbots for digital advisory and support services for government
- Voice assistants and natural language interfaces in public sector applications
- AI in embedded lending, insurance, and savings products for government financial initiatives
RegTech, Ethics, and Compliance
- AI in identity verification and Anti-Money Laundering (AML) monitoring for government agencies
- Fairness, bias, and explainability in financial AI systems for public sector operations
- Ethical considerations in data use and automation for government services
Prototyping AI-Enhanced FinTech Products
- Rapid prototyping tools and FinTech sandboxes for government projects
- Mapping user journeys and value-added features with AI for public sector applications
- Design thinking for responsible and inclusive finance in the public sector
Future of AI and Open Finance
- Trends in autonomous finance and predictive banking for government services
- AI governance and evolving regulatory landscapes for government oversight
- Strategic planning for AI-first product roadmaps in the public sector
Summary and Next Steps
Requirements
- An understanding of financial products and digital platforms for government
- Experience with data-driven product design or development
- Interest in API-based architectures and artificial intelligence applications
Audience
- Product Managers
- FinTech Founders
- Strategy Leads
Testimonials (3)
The background / theory of LLMs, the exercise
Joanne Wong - IPG HK Limited
Course - Applied AI for Financial Statement Analysis & Reporting
it has opened my mind to new tool that can help me in creating automation
Alessandra Parpajola - Advanced Bionics AG
Course - Machine Learning & AI for Finance Professionals
I very much appreciated the way the trainer presented everything. I understood everything even if Finance is not my area, he made sure that every participant was on the same page, while keeping up with the time left. The exercises were placed at good intervals. Communication with the participants was always there. The material was perfect, not too much, not too little. He elaborated very well on a bit more complicated subjects so that it can be understood by everyone.