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Course Outline
Day 1: Introduction to Big Data and AI in Banking
- •Overview of Big Data in Banking
o Definition and characteristics of Big Data
o Importance of Big Data in the banking sector - Introduction to AI in Banking
o Overview of AI concepts and applications
o The intersection of Big Data and AI - Regulatory Landscape
o Understanding bank regulations and examination processes
o Role of data and technology in meeting regulatory requirements
Day 2: Big Data Technologies and Frameworks
- Big Data Tools and Technologies
o Overview of Hadoop, Spark, and other Big Data platforms - Data Sources in Banking
o Identifying and leveraging internal and external data sources - Data Management Best Practices
o Managing data quality, security, and governance
Day 3: AI Techniques for Bank Examination Processes
- Machine Learning and AI Fundamentals
o Key concepts in machine learning and AI
o Supervised vs. unsupervised learning - Applications of AI in Bank Exams
o Risk assessment, fraud detection, and anomaly detection - Model Development and Evaluation
o Building predictive models for bank examination
o Key performance metrics and evaluation techniques
Day 4: Data Analytics for Effective Examination
- Data Analytics Techniques
o Exploratory data analysis and visualization
o Statistical methods and data mining techniques relevant to banking - Implementing Analytics for Examinations
o Using analytics to identify trends, patterns, and risks
o Developing dashboards and reporting tools for regulatory assessments - Ethics and Compliance
o Ethical considerations of using Big Data and AI in banking
o Navigating compliance and regulatory challenges
Day 5: Future Trends and Implementation Strategies
- Emerging Technologies in Banking Examination
o Overview of innovations influencing banking (e.g., blockchain, natural language processing) - Implementation Planning
o Best practices for integrating Big Data and AI in bank examination processes
o Roadmap for technology adoption and change management - Challenges and Solutions
o Discussion on current challenges in adopting new technologies
o Strategies for overcoming barriers to AI and Big Data implementation - Wrap-Up and Conclusion
o Recap of key takeaways from the training
o Q&A session and feedback collection
Requirements
This program aims to empower banking professionals to optimize examination processes, enhance data-driven decision-making, improve risk management, and effectively integrate emerging technologies into their operations. Participants will gain insights into the current landscape of Big Data and AI in finance, enabling them to leverage these tools for greater operational efficiency and competitive advantage.
35 Hours
Testimonials (5)
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
Deepthi - Invest Northern Ireland
Course - IBM Cognos Analytics
Practical exercises with our data
Marcel Richard - Lang Energie AG / Osterwalder Zurich AG
Course - Business Intelligence and Data Analysis with Metabase
Machine Translated
Share example of application
Course - Alteryx for Data Analysis
Very clearly articulated and explained
Harshit Arora - PwC South East Asia Consulting
Course - Alteryx for Developers
Linear regression - the algorithm to predict the trend
