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Work Package 4
Driving Digital Innovations with Blockchain Applications

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Overview

Blockchain is another driver of the technological change of the financial ecosystem, though there are no systematic studies that assess whether the benefits outweigh the costs. DIGITAL will analyse the efficiency of financial service providers that adopt the blockchain technology, contribute to more robust and efficient financial markets by understanding how to tokenize financial assets, reduce the risk of fraud and highly volatile crypto assets and establish a global, industrial standard for the architecture of blockchain-based financial systems.

The research will focus on developing Blockchain-based use cases and designing systematic studies aimed at advancing financial digital innovation. These studies will serve as a crucial input for a new infrastructure that will be utilised in a wide variety of IT domains. This infrastructure will account for the integration of multiple data sources, define a standard dictionary, eliminate ambiguity, and enable other teams to access all customer data from a centralised repository, thereby ensuring interoperability. Defining and monitoring efficiency measures will ensure the quality of the proposed frameworks. In addition, a qualitative evaluation will be conducted based on the comparison of our proposed frameworks that go beyond the state of the art of traditional standard approaches. This is intended to serve as the basis for a new blockchain-based financial infrastructure and as a European industry standard for blockchain applications. In addition, the research will also focus on proposing novel risk management solutions to some of the main concerns around blockchain applications in finance, like fraud detection and financial stability.

WP 4 Team

Research topics

Under this research stream, THREE doctoral candidates will tackle the following research projects:

  • 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
  • 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
  • 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
  • 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
  • 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

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To get an overview of all our research topics, click here.

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