Course Outline
Day 1: Introduction to Big Data and AI in Banking
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Big Data Overview in Banking
- Defining Big Data and its key characteristics
- The strategic importance of Big Data in banking
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AI Integration in Banking
- Fundamental concepts and use cases of AI
- The synergy between Big Data and AI
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Regulatory Context
- Navigating bank regulations and audit procedures
- The role of data and technology in ensuring regulatory compliance
Day 2: Big Data Technologies and Frameworks
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Tools and Platforms for Big Data
- Introduction to Hadoop, Spark, and other major Big Data ecosystems
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Data Sources in the Banking Sector
- Identifying and maximizing the value of internal and external data
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Best Practices for Data Management
- Ensuring data quality, security, and governance
Day 3: AI Techniques for Bank Examination Processes
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Fundamentals of Machine Learning and AI
- Core principles of machine learning and AI
- Distinguishing between supervised and unsupervised learning
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AI Applications in Banking Audits
- Utilizing AI for risk assessment, fraud detection, and anomaly identification
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Model Development and Assessment
- Constructing predictive models for banking audits
- Critical performance metrics and evaluation methods
Day 4: Data Analytics for Effective Examination
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Analytical Techniques
- Exploratory data analysis and visualization strategies
- Statistical methods and data mining techniques pertinent to banking
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Deploying Analytics for Audits
- Leveraging analytics to uncover trends, patterns, and risks
- Creating dashboards and reporting tools for regulatory reviews
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Ethics and Compliance
- Ethical challenges associated with Big Data and AI in banking
- Strategies for navigating compliance and regulatory hurdles
Day 5: Future Trends and Implementation Strategies
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Emerging Technologies in Banking Audits
- Overview of innovations shaping banking (e.g., blockchain, natural language processing)
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Implementation Planning
- Best practices for integrating Big Data and AI into audit workflows
- Establishing a roadmap for technology adoption and managing change
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Challenges and Solutions
- Addressing current obstacles in adopting new technologies
- Strategies to overcome barriers to AI and Big Data implementation
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Conclusion and Wrap-Up
- Summary of key learning outcomes
- Q&A session and feedback collection
Requirements
This initiative is designed to enable banking experts to streamline audit processes, strengthen data-driven decision-making, refine risk management, and seamlessly incorporate advanced technologies into their daily operations. Attendees will gain a comprehensive understanding of the current Big Data and AI landscape in finance, allowing them to harness these technologies for enhanced efficiency and market competitiveness.
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
