AI and Advanced Analytics Applied at Raffeisen Bank International AG

Overview

Explore AI and advanced analytics applications in banking, focusing on Raffeisen Bank International's innovative approaches to data-driven decision-making and customer service enhancement.

Syllabus

• Introduction to AI in Banking
Overview of AI and Advanced Analytics
History and Evolution in Banking
Key Technologies: Machine Learning, NLP, Computer Vision
• Raffeisen Bank International AG: A Case Study
Company Overview
Strategic Goals and Innovation in AI
Key Projects and Initiatives
• Data-Driven Decision-Making
Data Collection and Management
Analytical Techniques for Predictive Modeling
Case Study: Credit Scoring and Risk Assessment
• Enhancing Customer Service with AI
Personalization and Recommendation Systems
Customer Feedback Analysis
Chatbots and Virtual Assistants
• Fraud Detection and Prevention
Techniques in Anomaly Detection
Real-Time Monitoring Systems
Implementation Challenges and Solutions
• Regulatory and Ethical Considerations
Compliance in AI Applications
Ethical AI Use in Banking
Data Privacy and Security Measures
• Emerging Trends and Future Directions
AI in Digital Transformation
Open Banking and AI Integration
The Future of AI in Financial Services
• Practical Workshop
Hands-On with AI Tools and Technologies
Developing a Simple Predictive Model
Use Cases: From Concept to Implementation
• Conclusion and Key Takeaways
Recap of Key Learnings
Impact of AI Innovations on Banking
Resources for Further Learning and Development

Subjects

Conference Talks