I firmly believe in the transformative power of AI to revolutionize the financial industry. By fostering collaboration between academia and industry, we can unlock unprecedented opportunities for innovation, transparency, and efficiency. Our commitment to ethical AI practices ensures that these advancements benefit all stakeholders and contribute to a more inclusive and fair financial landscape
The Research Programme
The University of Twente - ING collaboration on Artificial Intelligence is part of a larger pan-European research programme on Digital Finance, where the University plays a leading role: In total, more than 360 researchers, 50 universities and 25 companies work together in various European research programmes.
UT - ING collaboration on Articial Intelligence - since 2021 (Lead: prof. dr. Jos van Hillegersberg)
MSCA Industrial Doctoral Network on Digital Finance (Coordinator: University of Twente (Joerg Osterrieder))
European COST Action on Fintech and Artificial Intelligence in Finance (Action Chair: Joerg Osterrieder)
The Funding Agencies
Horizon Europe
COST Assocation
Marie Sklodowska-Curie Actions
Swiss National Science Foundation
Swiss State Secretariat for Research
ING
The Research Grants
Action Chair COST FinAI
Scientific Grant Holder COST FinAI
Coordinator MSCA Doctoral Network on Digital Finance
SNF Narrative Digital Finance
SNF Network-based credit risk models
SNF Blockchain Fraud Detection
SERI Digital Finance
ING – UT Cooperation
The Research - Digital Finance
30 Individual Research Projects
25 Doctoral Candidates across Europe, of which 12+ affiliated with UT
PI or Co-PI of seven research projects
100% of research topics linked to UT
A European PhD Programme
The Research Projects
30 Individual Research Projects
25 Doctoral Candidates across Europe, of which 12+ affiliated with UT
PI or Co-PI of seven research projects
100% of research topics linked to UT
A European PhD Programme
A European Cooperation
51 Countries
300+ Researchers
100+ Institutes
The University of Twente
Faculty of Behavioural, Management and Social sciences
The MSCA Research
Towards a European Financial Data Space
Collaborative learning across data silos
Detecting anomalies and dependence structures in high dimensional, high frequency financial data
Predicting financial trends using text mining and NLP
Deep Generation of Financial Time Series
Artificial Intelligence for Financial Markets
Strengthening European financial service providers through applicable reinforcement learning
Developing industry-ready automated trading systems to conduct EcoFin analysis using deep learning algorithms
Challenges and opportunities for the uptaking of technological development by industry
Investigating the utility of classical XAI methods in financial time series
Towards Explainable and Fair AI-generated decisions
Audience-dependent explanations
Fair Algorithmic Design and Portfolio Optimization under Sustainability Concerns
Driving Digital Innovation with Blockchain Applications
Industry standard for blockchain
Fraud detection in financial networks
Risk index for cryptos
Sustainability of Digital Finance
Modelling green credit scores for a network of retail and business clients
A recommender system to re-orient investments towards more sustainable technologies and businesses
Experimenting with Green AI to reduce processing time and contributes to creating a low-carbon economy
Applications of Agent-based Models (ABM) to analyze finance growth in a sustainable manner over a long-term period
The MSCA Doctoral Training
Towards a European Financial Data Space
Foundations of data science
Synthetic Data Generation for Finance
Anomaly Detection in Big Data
Natural Language Processing with Transformers
Dependence Structures in High Frequency Financial Data
Artificial Intelligence for Financial Markets
Introduction to AI for financial applications
Reinforcement Learning in Digital Finance
Machine Learning in Industry
Deep Learning for Finance
Data-Centric AI
Towards Explainable and Fair AI-generated decisions
The need for eXplainable AI: methods and applications in finance
Cybersecurity in Digital Finance
AI Design in Digital Finance
Barriers in Digital Finance Adoption
Explainable AI in Finance
Driving Digital Innovation with Blockchain Applications
Introduction to Blockchain applications in finance
Digital Finance Regulation
History and Prospects of Digital Finance
Blockchains in Digital Finance
Sustainability of Digital Finance
Sustainable finance
Digital EIT Summer School - Disrupting Finance with Digital Technologies
Green Digital Finance
Multi-Criteria Decision Making in Sustainable Finance
The European COST Action on Fintech and AI in Finance
The Principles: European Research Network with a Global Reach
The Network: European COST Countries and International Partners
The Research: Inclusive, Interdisplinairy, Advancing Science and Technology
The Research
Research Output with an Impact (more than 6000 citations and over 100 publications anually)
Dissemination across Europe (more than 15 research events and over 1000 participants per year)
Interdisciplinary Cooperations with Diverse Stakeholders (40 European countries and more than 300 researchers from 51 countries globally)
Fintech and AI in Finance (more than 40 research funding applications)
Towards a Transparent Financial Industry
ING - UT: The Research
The Foundations - Data
The use of "meta labeling" technique
Federated Learning
Privacy-enhancing techniques for storing and analysing confidential data
Applications of synthetic data generation for Finance
The main applicaiton - Risk Management
Early warning systems for credit risk
Machine learning for credit scoring
Research on risk management related topics
Advanced Tools - Artificial Intelligence
Explainable Artificial Intelligence
Applications of Reinforcement learning
Business Models
The value of innovation projects in Finance
Networks of the client base
The Applications and Outlook
Statistics of applying models
Large Language Models for information retrieval from documents
