COST FinAI PhD School on Fintech and AI in Finance 2024

June 10 - 14, 2024

Enschede, the Netherlands

Summary

Welcome to the COST FinAI PhD School on Fintech and AI in Finance 2024!

We are excited to announce a further edition of this COST Action CA19130 Training series. This meeting is organized by the COST Action CA19130 on Fintech and AI in Finance, under the auspices of COST - European Cooperation in Science and Technology. The event will showcase the Action's expertise with a focus on integrating advanced computational technologies with financial practices. Expert speakers will delve into the transformative potential of Generative AI in finance, discussing its role in automation and decision-making. Topics include the deployment of chatbots and large language models in financial technologies, highlighting innovations in customer interaction and financial advising.

Some facts about the COST Action 19130

- 51 countries

- 200+ researchers from 100+ universities

- Funded by the Horizon Europe Framework Programme of the EU

Keywords

Fintech, Artificial Intelligence in Finance, Transparency in Finance, Machine Learning, Blockchain, Cryptocurrencies.

This event is based upon work from COST Action 19130, supported by COST (European Cooperation in Science and Technology), www.cost.eu.

Day 1-5:

10. June 2024, 09:30 – 14. June 2024, 14:00

University of Twente, Ravelijn, Hallenweg 17, 7522 NH Enschede, the Netherlands

Joerg Osterrieder, Associate Professor of Finance and Artificial Intelligence at University of Twente (Netherlands) and Professor of Sustainable Finance at BFH (Switzerland)
Lennart John Baals, University of Twente, and Bern University of Applied Science (BFH)
Christina Kolb, Assistent Professor, Cyber Security and Resilience, University of Twente
Ioana Coita, Lecturer, University of Oradea (Romania)
Roman Matkovskyy, Associate Professor, Finance and Accounting, Rennes School of Business
Marcos Machado, Assistent Professor in Business and Information Systems, University of Twente
Liana Stanca, Professor, Babeș-Bolyai University (Romania)
Karolina Bolesta, Lecturer in Economics, SGH Warsaw School of Economics and Procter & Gamble (Poland)
Karsten Wenzlaff, Lecturer for Business Administration, specifically digital markets (Germany)

The event is hybrid and open to everyone upon registration.

You can register here as on-side participant and via the Zoom registration for online participation.

Physically

Day 1 - Day 5:

June 10th – June 14th, 2024.

University of Twente, Ravelijn Building, Hallenweg 17, 7522 NH Enschede, Netherlands

Remotely (Zoom)

Day 1 - Day 5:

June 10th – June 14th, 2024.

09:30 – 17:00, Amsterdam time.

Please register here.

Artificial Intelligence and Deep Reinforcement Learning in Finance

This lecture offers a comprehensive introduction to Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) applications in the finance industry. The course covers fundamental AI techniques, their financial applications, and the unique challenges faced in the industry. Participants will gain insights into various AI-driven solutions such as algorithmic trading, credit scoring, fraud detection, and portfolio optimization. The course also delves into the rapidly evolving field of DRL, exploring key algorithms, their underlying principles, and applications in finance, such as algorithmic trading, risk management, and option pricing.

A hands-on workshop will provide participants with practical experience in implementing a DRL model for algorithmic trading. The workshop covers essential steps, including data preprocessing, feature engineering, DRL model implementation, and performance evaluation. Participants will have the opportunity to work with real-world financial data and apply their learnings to develop a trading strategy using DRL.

This lecture is designed for PhD students and early-career researchers interested in the intersection of AI, DRL, and finance. By the end of the course, participants will have a solid understanding of AI applications in finance, DRL techniques, and the practical know-how to implement and evaluate DRL-driven financial strategies.

1. Introduction

1.1. Welcome and overview
1.2. Basics of finance and financial markets
1.3. Introduction to Artificial Intelligence (AI) and Machine Learning (ML)
1.4. Role of AI and ML in finance

2. Artificial Intelligence in Finance

2.1. Overview of AI techniques in finance 2.1.1. Supervised learning 2.1.2. Unsupervised learning 2.1.3. Reinforcement learning
2.2. AI applications in finance 2.2.1. Algorithmic trading 2.2.2. Credit scoring and risk assessment 2.2.3. Fraud detection 2.2.4. Portfolio optimization 2.2.5. Financial forecasting 2.2.6. Chatbots and customer service
2.3. Key considerations and challenges 2.3.1. Data quality and availability 2.3.2. Model interpretability and explainability 2.3.3. Ethical and regulatory issues

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MSCA Network Events

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Research Seminar: Explainable AI Methods for Financial Time Series (WP3)

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