Program Overview
Financial Institutions have always been considered to be operating in heavy data industry. Thus, the majority of contemporary banks, insurance companies and other institutions are attempting to embrace advanced analytics and adopt more data-driven approach for decision making as the analytics is a game-changer in transforming business processes and conducts to identify potential opportunities and threats. Data drives the modern financial industry through various ways, starting from boosting cybersecurity all the way through the personalized offerings and increased customer satisfaction.
Big Data Analytics, Artificial Intelligence and Machine Learning For Financial Institutions in Tokyo, Japan program introduces its attendees with Big Data Analytics, providing the comprehensive coverage of feasible data strategies resulting in valuable and successful business outcomes within the financial industry.
Target Audience
The program is the best suit for:
- Banking Professionals
- Financial Analysts and Managers
- Financial Decision Makers
- Business development Executives
- Data Officers and Analysts
- IT Personnel
- Management Consultants.
Program Objectives
Upon the successful completion of this intensive training course, the participants will:
- Relate Key Business Processes to Financial Statements
- Comprehend the Impact of Technology on Financial Auditing
- Identify the dynamics of big data, analytics and data science in various financial applications
- Help shape organization’s big data strategy
- Determine the key success factors for effective big data strategy within the organization.
Program Contents
- Core Concepts of Big Data and Machine Learning
- Impact of Big Data and Financial Analytics on Financial Services Sector
- Solving Finance Tasks through Big Data/Machine Learning
- Effective Big Data Strategy
- The Need for the Big Data Strategy: Opportunities and Considerations
- Key Aspects of Big Data Strategy: Data, Identification, Learning techniques, Modelling, Tools, Capability & Adaptation
- Big Data Projects Framework
- Acquiring Data from right sources
- Implementing Data Governance Standards
- Optimizing Business Outcomes through Big Data/Machine Learning
- Storing, Transforming and Modelling the Data
- Building human resource capabilities for Data Analytics; choosing the right talent pool
- Choosing the correct business metrics to indicate success/failure of a big data project
- Introduction to common organizational hurdles
- Keys to effective use of Big Data
- Big Data Applications in Finance: Churn Prediction and Prevention, Loan Default Prediction, Quantitative trading, Sentiment Analysis, Market Segmentation, Anomaly Detection, Risk Management and Control
- Financial Services of Future
- The competitive advantage of Big Data
- Data Accuracy and reliability
- Machine learning usages
- Interpreting Machine Learning Predictions
- Machine Learning Transparency and Documentation
- Cybersecurity Risks.
Program Methodology
This program is a short term extensive training course with highly practical focus. The presenter will apply modern adult learning techniques in order to maximize the effectiveness of the session delivery and achieve successful results. The methods deployed will include open presentation, group discussions and individual assignments and case studies. At the end of each session the trainer will request for feedback and consider comments received for the coming days in order to improve results and ensure the maximum understanding of material covered for delegates.