Introduction to Data Science and AI in Banking and Finance

Course Objectives

This course offers a foundational understanding of how Data Science and Artificial Intelligence (AI) are reshaping the Banking and Financial Services Industry (BFSI). Participants will gain insights into key concepts, tools, and technologies driving AI and Data Science. The program explores their strategic role in enhancing innovation, efficiency, and customer experience through real-world applications such as fraud detection, credit scoring, customer segmentation, and algorithmic trading. Learners will also evaluate AI’s contribution to operational improvements, compliance, and data-driven decision-making. The course addresses critical ethical, privacy, and regulatory challenges, while highlighting future trends like blockchain-AI convergence, predictive analytics, and open banking APIs.

Pedagogy

The teaching methodology will involve a blend of theoretical learning and practical insights, including:

1. Interactive lectures to explain key concepts and frameworks.
2. Real-world case studies from leading financial institutions to understand AI/DS applications in action.
3. Hands-on demonstrations of predictive models and AI tools (where applicable).
4. Group discussions and Q&A sessions to encourage collaborative learning and critical thinking.
5. Short assessments and quizzes to reinforce learning outcomes after each module.

Programme Highlights

• A comprehensive introduction to Data Science and AI tailored specifically for the BFSI sector.
• Industry-relevant content focusing on high-impact use cases like fraud detection, credit risk, and customer analytics.
• Discussion of both opportunities and ethical challenges in AI implementation.
• Coverage of current and future trends such as RPA, blockchain integration, and AI-driven financial inclusion.
• Ideal for banking professionals, data analysts, fintech enthusiasts, and students aspiring to enter the financial technology space.