MSCA Individual Research Projects

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Strengthening European financial service providers through applicable reinforcement learning

  • Host institution: University of Twente.
  • Starting month: M3.
  • Duration: 36 months.
  • Pillar 1: Introduction to AI for financial applications (WWU, 4 ECTs), Work Package 2

Objectives

Reinforcement Learning (RL) has become popular for automating uncertain decision-making in complex environments. Deep reinforcement learning can make impressive algorithmic decisions in closed environments, but real-world applications in open environments are harder. This project examines how RL can advance digital finance.

Expected Results

The project will address several RL implementation issues in digital finance. Utility-based RL deliverables will improve financial decision-making by developing multi-criteria analysis, extreme scenarios, and risk management methods. RL in decision-support will be optimised for explainability, regulatory compliance, model abstractions, and human judgement. We will also examine technological challenges like Digital Twin environments, machine learning pipelines, and digital finance ecosystem integration.

Planned Secondments

  • CAR, Altin Kadareja (CEO), M6, 18 months, applied research on Fintech innovations with Deep learning
  • ECB, Lukasz Kubicki, M27, 4 months, training on EU principles, supervision policies and research

Total Timeframe

Modelling green credit scores for a network of retail and business clients

  • Host institution: University of Twente.
  • Starting month: M6.
  • Duration: 36 months.
  • Pillar 1: Sustainable finance (UNA, 4 ECTs), Work Package 5

Objectives

Some markets use green credit scores to assess SME credit risk in sustainable and circular economies. Simultaneously, network customers' default likelihood has been studied. This study develops and deploys green credit score models that account for customers' networks. We show the impact and give financial institutions methods to improve credit risk assessment and access.

Expected Results

Green credit score models will be developed and implemented. These models inform SMEs about their carbon footprint, their main risks in a low-carbon economy, and how to mitigate them. SMEs leading on sustainability could gain easier access to capital by demonstrating positive relationships between creditworthiness and sustainability, creating a fairer credit risk assessment that explicitly factors in sustainability metrics and encouraging low-carbon measures.

Planned Secondments

  • SWE, Prof. Dr. Tadas Gudaitis, M12, 18 months, ESG and credit score modelling
  • ECB, Lukasz Kubicki, M33, 4 months, exposure to globally leading central bank, research training on EU principles, supervision

Total Timeframe

Industry standard for blockchain

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

A recommender system to re-orient investments towards more sustainable technologies

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M12
  • Duration: 36 months
  • Pillar 1: Sustainable finance (UNA, 4 ECTs), Work Package 5
  • Work Packages: WP5, WP6, WP7, WP8

Objectives

Recommender systems are well-known information filtering systems that suggest items most relevant to a user. To our knowledge, there are none that suggest investments in sustainable technologies and businesses. This project will develop and deploy a recommender system to help financial institutions and their clients invest in sustainable technologies.

Expected Results

The project informs user groups about investment sustainability. Sustainability KPI mapping and evaluation are project deliverables. The recommender system's explainability is crucial. Thus, the recommendations will be tailored to multiple user classes with appropriate explanations and interpretations. The system recommends sustainable investments, monitors portfolio performance, and dynamically updates financial and sustainable KPIs.

Planned Secondments

  • RAI, Dr. Stefan Theußl, M24, 18 months, research exposure in a global business environment,
  • ARC, Prof. Dr. Ioannis Emiris, M18, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Fraud detection in financial networks

  • Host institution: WU Vienna University of Economics and Business, Austria (WWU)
  • Starting month: M3
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4
  • Work Packages: WP4, WP6, WP7, WP8

Objectives

Detecting fraud is currently one of the most important topics in Finance. However, it is also one of the most complex, given that fraudsters typically represent and generate a highly dynamic system, requiring that the boundaries and objectives of any system designed to detect and reduce fraud be constantly adapted to new extrinsic structures. This enables the definition of not only a static fraud detection system, but also a dynamic AI learning system, particularly in relation to network analysis.


Expected Results

On a meta-level, a set of Machine Learning and Artificial Intelligence models will be defined to enable a research-based approach that can be applied directly in financial institutions. The models are defined in such a way that the outcomes of the learning process within the institutions can be used to define and design new algorithms from a scientific standpoint. The work on network algorithms during the process of designing Machine Learning environments, will result in the publication of seminal papers.

Planned Secondments

  • RAI, Dr. Stefan Theußl, M6, 18 months, research exposure in a global business environment
  • ECB, Dr. Lukasz Kubicki, M27, 4 months, exposure to globally leading central bank, research training on EU principles, supervision


Total Timeframe

Collaborative learning across data silos

  • Host institution: WU Vienna University of Economics and Business, Austria (WWU)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Foundation of data science (BBU, 4 ECTs), Work Package 1

Objectives

Connecting several dozen different data pipeline components and integrating an excessive number of APIs to leverage siloed data is a significant barrier to the comprehensive implementation of AI-based systems in finance. Currently, very little research is devoted to addressing all of the challenges associated with training, testing, and deploying cutting-edge ML and DL methods while leveraging siloed data. We will concentrate on the data challenges that finance service providers face by proposing solutions to streamline data collection, resolve data quality issues, and structure data to support downstream processes.

Expected Results

APIs for integrating Machine Learning and Deep Learning algorithms into FinTech processes necessitate careful abstraction of the specified input and output, which is the responsibility of the researchers to simplify and aggregate the complexity. This project produced a large number of API definitions that are closely related to research papers in the fields of theory of Artificial Intelligence and Machine Learning, as well as theory of Finance applications in various sub-fields such as security and compliance. The API specification itself should not only be integrated into financial institutions' business processes, but should also provide fruitful input for new research papers that are of interest to readers and users of all involved fields of research.

Planned Secondments

  • SWE, Prof. Dr. Tadas Gudaitis, M18, 18 months, research on prototype implementations, applied research
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Risk index for cryptos

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Detecting anomalies and dependence structures in high dimensional, high frequency financial data

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Audience-dependent explanations

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Experimenting with Green AI to reduce processing time and contributes to creating a low-carbon economy

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Applications of Agent-based Models (ABM) to analyse finance growth in a sustainable manner over a long-term period

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Developing industry-ready automated trading systems to conduct EcoFin analysis using deep learning algorithms

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Predicting financial trends using text mining and NLP

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Challenges and opportunities for the uptaking of technological development by industry

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Deep Generation of Financial Time Series

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Investigating the utility of classical XAI methods in financial time series

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe

Fair Algorithmic Design and Portfolio Optimization under Sustainability Concerns

  • Host institution: University of Twente, The Netherlands (UTW)
  • Starting month: M9
  • Duration: 36 months
  • Pillar 1: Introduction to Blockchain applications in finance (HUB, 4 ECTs), Work Package 4

Objectives

Cryptocurrencies and other digital assets have proliferated in recent years, elevating blockchain technology. Decentralised finance requires it. Blockchain is well-established in digital finance, but it lacks maturity and scalability. This project leverages the extensive and diverse DIGITAL network, which includes financial industry leaders, to set a blockchain industry standard.

Expected Results

The project will map and categorise blockchain technology literature and practice to create an industry standard. DIGITAL includes the ECB, multinational banks, and leading digital finance tech companies. This combination lets us analyse blockchain and find commonalities and desires that could lead to a standard. We will work on several blockchain use cases, inspired by industrial partners, to ensure that the results do not stall at a normative framework level but trickle down to concrete and relevant demonstrations of the standard implemented in digital finance.

Planned Secondments

  • DEL, Alberto Ferrario, M18, 18 months, business modelling, research on use-cases and prototypes
  • FRA, Prof. Dr. Ralf Korn, M12, 4 months, applied industry-research, exposure to world-leading research centre and infrastructure

Total Timeframe