BACKGROUND:

• Rapid Advancements: The lightning-fast pace of technological advancements in AI, Blockchain, and Digital Banking.
• Ethical Concerns: The ethical dilemmas surrounding AI, including bias and fairness issues in algorithms.
• Data Privacy: The importance of data privacy and security in the age of AI and Digital Banking.
• Blockchain Security: The vulnerabilities and risks in Blockchain, such as smart contract vulnerabilities and cryptocurrency scams.
• Regulatory Challenges: The regulatory challenges and complexities associated with emerging technologies.
• Misuse and Consequences: Real-world consequences of AI misuse and its societal impact.
• Customer Trust: How Digital Banking risks can erode customer trust and adoption.
• Future Trends: The evolving landscape of emerging technologies and the importance of staying vigilant about future risks.

OBJECTIVES:

• Understand the fundamental concepts of AI and its applications in the banking industry.
• Gain a foundational understanding of artificial intelligence, including different AI types and their relevance in banking.
• Learn about the various types of banking data, their significance, and challenges associated with data in the banking sector.
• Acquire the skills needed to collect, preprocess, and clean banking data for analysis.
• Explore how machine learning is used in banking, including supervised and unsupervised learning techniques.
• Understand how AI can be applied for credit scoring, risk assessment, customer churn prediction, and fraud detection.
• Learn about NLP applications in banking, such as sentiment analysis and chatbots for customer support.
• Gain practical experience by working with ChatGPT.