UTFacultiesBMSING-UTING-UT Collaboration

The UT - ING collaboration

M. Baak, Data Science – Wholesale Banking

This partnership leverages cutting-edge academic research and practical industry insights to drive forward innovative AI solutions in finance. By combining our strengths, we are able to tackle complex challenges and create impactful advancements that benefit both the academic community and the financial sector.

M. Baak, Data Science – Wholesale Banking

This collaboration strategically positions ING and the University of Twente to pursue AI-related research, aiming to advance the frontier of AI in Finance through innovative applications in data analysis, risk management, and business integration. 

Collaboration in Research

Research by UT Students

The collaboration has yielded 8 successfully completed Master's theses, and one is presently underway. The topics range from Explainable AI (XAI), AI models for Early Warning Systems (EWS), AI models for credit risk assessment, incorporating ESG factors in credit rating, and improving automated information extraction from sustainability reports.

Additionally, a project led by a PhD Candidate Leixin Zhang on obtaining a reliable confidence scores for generated answers in a Retrieval-Augmented Generation (RAG) pipeline.

Research Projects

The team is leading or involved in several large European research projects focussing on Artificial Intelligence within the financial sector.

Collaboration in Education

Our collaboration extends into the classroom, where ING actively contributes to 10 courses at the University of Twente by delivering guest lectures and supplying industry problems for student projects.

Funding

ING has committed to investing in public-private partnerships through Kickstart AI by jointly sponsoring academic positions, in our case for position of Assoc. Dr. Joerg Osterrieder at the UT. European Research projects FinAI and Digital Finance have received funding through the COST and Marie Skłodowska-Curie Actions.

Output & Impact