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SEMINAR DESCRIPTION

 

"Today companies have widely adopted big data analytics to uncover hidden patterns that can help them make more-informed business decisions. BIB has brought to Hungary the “Modelling Big Data” course provided by Panthera Solutions, where financial practitioners receive practical guidance on how to properly use and analyze Big Data."

TARGET GROUPS

 

• (Multi-) Family Offices
• Wealth Managers
• Private Banks
• Regional Banks
• Trusts
• Finance Director
• Financial Analyst
• Corporate Treasurer
• Management Consultant
• Performance Manager
• Legal & tax advisor

 

ONLINE-COURSE DESCRIPTION

Today companies have widely adopted big data analytics to uncover hidden patterns that can help them make more-informed business decisions. BIB has brought to Hungary the “Modelling Big Data” course provided by Panthera Solutions, where financial practitioners receive practical guidance on how to properly use and analyze Big Data.
The vast proliferation of data and increasing technological advances continue to transform the way industries operate and compete. Financial companies, in particular, have widely adopted big data analytics to gain further insights on their environment and eventually make better investment decisions. This Online-seminar introduces common big data tools for practitioners and show them how to handle big datasets and apply big data methodologies in a range of problems from scenario analysis for risk management to
forecasting loan default with machine learning.

 

LEARNING GOALS

 

With this seminar, corporations will now understand which big data tools suit them best. All together, participants get empowered through practical tools that can be applied back at their desk to fit their particular needs

1. MAKING BIG DATA
STRESS TESTING AND SCENARIO ANALYSIS IN RISK MANAGEMENT

• Definition and classification of risk
• Scenarios planning
• Scenarios pre-requirements
• Feeding and adapting the scenarios

CASE STUDY IN EXCEL/VBA
Monte-Carlo simulations based risk measures

2. DOWNSIZING BIG DATA
REDUCING NOISE WITH EXPLORATORY DATA ANALYSIS

• Re-assessing dependencies among variables
• Principal Component Analysis
• Capturing interactions and contagion
• The cognitive advantages of data visualization
• Graphical representation of networks

CASE STUDY IN R
Risk factor clustering

3. FORECASTING WITH BIG DATA I
FORECASTING TIME SERIES

• Machine learning vs. simple rules
• Big data and financial statement analysis.
• Comparing five valuation models

CASE STUDY IN EXCEL/VBA
Firm and project valuation

4. FORECASTING WITH BIG DATA II
FORECASTING LOAN DEFAULT

• Assessing credit risk
• Variables selection
• Machine learning vs. simple rules II

CASE STUDY IN R
Predicting loan defaults

Download course description in PDF.

DURATION

Four days, each day from am. 9:00-12:00

 

Price: 

 615 EUR + VAT