2026-07-23T13:24:23Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:21365 2024-10-28T08:50:38Z ddc:004 open_access

RATE-Analytics: Next Generation Predictive Analytics for Data-Driven Banking and Insurance Collaris, Dennis Pechenizkiy, Mykola van Wijk, Jarke J. Visualization Visual Analytics Machine Learning Interpretability Explainability XAI We conducted the RATE-Analytics project: a unique collaboration between Rabobank, Achmea, Tilburg and Eindhoven University. We aimed to develop foundations and techniques for next generation big data analytics. The main challenge of existing approaches is the lack of reliability and trustworthiness: if experts do not trust a model or its predictions they are much less likely to use and rely on that model. Hence, we focused on solutions to bring the human-in-the-loop, enabling the diagnostics and refinement of models, and support in decision making and justification. This chapter zooms in on the part of the project focused on developing explainable and trustworthy machine learning techniques. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Dennis Collaris and Mykola Pechenizkiy and Jarke J. van Wijk 2024 Is Part Of OASIcs, Volume 124, Commit2Data (2024) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.Commit2Data.8 urn:nbn:de:0030-drops-213655 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Commit2Data.8 eng https://creativecommons.org/licenses/by/4.0/legalcode