Course Outline
Day 1: Introduction to Big Data and AI in Banking
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Big Data Overview in Banking
- Definition and key characteristics of Big Data.
- The strategic importance of Big Data in the banking sector.
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Introduction to AI in Banking
- Overview of AI concepts and practical applications.
- The convergence of Big Data and AI.
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Regulatory Landscape
- Understanding banking regulations and examination procedures.
- The role of data and technology in fulfilling regulatory requirements.
Day 2: Big Data Technologies and Frameworks
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Big Data Tools and Technologies
- Overview of platforms including Hadoop, Spark, and others.
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Data Sources in Banking
- Identifying and leveraging internal and external data sources.
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Best Practices for Data Management
- Strategies for managing data quality, security, and governance.
Day 3: AI Techniques for Bank Examination Processes
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Fundamentals of Machine Learning and AI
- Core concepts in machine learning and AI.
- Differences between supervised and unsupervised learning.
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AI Applications in Bank Exams
- Use cases for risk assessment, fraud detection, and anomaly detection.
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Model Development and Evaluation
- Constructing predictive models for bank examinations.
- Key performance metrics and evaluation techniques.
Day 4: Data Analytics for Effective Examination
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Data Analytics Techniques
- Exploratory data analysis and visualization methods.
- Statistical methods and data mining techniques relevant to banking.
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Implementing Analytics for Examinations
- Using analytics to identify trends, patterns, and risks.
- Developing dashboards and reporting tools for regulatory assessments.
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Ethics and Compliance
- Ethical considerations surrounding the use of Big Data and AI in banking.
- Navigating compliance and regulatory challenges.
Day 5: Future Trends and Implementation Strategies
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Emerging Technologies in Banking Examination
- Overview of innovations impacting banking, such as blockchain and natural language processing.
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Implementation Planning
- Best practices for integrating Big Data and AI into bank examination processes.
- Roadmap for technology adoption and change management.
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Challenges and Solutions
- Discussion on current challenges in adopting new technologies.
- Strategies for overcoming barriers to AI and Big Data implementation.
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Wrap-Up and Conclusion
- Recap of key takeaways from the training.
- Q&A session and feedback collection.
Requirements
This program is designed to enable banking professionals to streamline examination processes, enhance data-driven decision-making, strengthen risk management, and successfully incorporate emerging technologies into their daily operations. Participants will gain valuable insights into the current Big Data and AI landscape in finance, allowing them to utilize these tools for improved operational efficiency and competitive advantage.
Testimonials (2)
training vibes, trainer knowledge, and insightful materials
Rizma Aulia Rachman - Lembaga Penjamin Simpanan
Course - Big Data and AI in Connection to Bank Examination Process
Exercise penggunaan AI dalam pekerjaan sehari-hari
