Work Package 2
Artificial Intelligence for Financial Markets
Leading institution
Overview
AI has improved decision making in numerous areas, including risk management, compliance, trading strategies and personalised banking and advice, and yet, adoption of AI-based tools in practice has still been rather slow. With DIGITAL, we will describe the primary challenges and opportunities for industry's adoption of technological development, encourage a larger deployment of state-of-the-art ML models in real-world financial applications and simulate the market environment in Reinforcement Learning (RL) applications for market applications.
In this research topic, the emphasis will be placed on the deployment of complex AI models to pertinent financial problems. For financial applications such as risk management, trading strategies, and client-centric financial products, AI models trained and tested in closed, academic settings have shown great promise. Yet, real-world applications (in open environments) are more challenging. Using industry-ready use cases, we will demonstrate the viability of novel dynamic rating models, automated trading platforms, and market environments for RL agents in real-industry settings for the first time. This research will provide first-of-its-kind qualitative analysis of the primary obstacles to deploying innovative technologies in industry and propose new solutions for resolving these obstacles which in turn is a crucial step towards a widespread adoption of complex models in the financial sector.
Research topics
Under this research stream, TWO doctoral candidates will tackle the following research projects:
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Towards a European Financial Data Space (WP1)IRP6 - Collaborative learning across data silos IRP8 - Detecting anomalies and dependence structures in high dimensional, high frequency financial data IRP13 - Predicting financial trends using text mining and NLP IRP15 - Deep Generation of Financial Time Series Work Package 1 Page
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Artificial Intelligence for Financial Markets (WP2)IRP12 - Developing industry-ready automated trading systems to conduct EcoFin analysis using deep learning algorithms IRP14 - Challenges and opportunities for the uptaking of technological development by industry Work Package 2 Page
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Towards explainable and fair AI-generated decisions (WP3)IRP1 - Strengthening European financial service providers through applicable reinforcement learning IRP9 - Audience-dependent explanations IRP16 - Investigating the utility of classical XAI methods in financial time series IRP17 - Fair Algorithmic Design and Portfolio Optimization under Sustainability Concerns Work Package 3 Page
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Driving digital innovations with Blockchain applications (WP4)IRP3 - Machine learning for digital finance IRP5 - Fraud detection in financial networks IRP7 - Risk index for cryptos Work Package 4 Page
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Sustainability of Digital Finance (WP5)IRP2 - Modelling green credit scores for a network of retail and business clients IRP4 - A recommender system to re-orient investments towards more sustainable technologies and businesses IRP10 - Experimenting with Green AI to reduce processing time and contributes to creating a low-carbon economy IRP11 - Applications of Agent-based Models (ABM) to analyse finance growth in a sustainable manner over a long-term period Work Package 5 Page
News
To get an overview of all our research topics, click here.