@inbook{a6156527b9a6461d904cb2a29a53ef40,
title = "RATE-Analytics: Next Generation Predictive Analytics for Data-Driven Banking and Insurance",
abstract = "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.",
keywords = "Visualization, Visual Analytics, Machine Learning, Interpretability, Explainability, XAI, Explain-ability",
author = "Dennis Collaris and Mykola Pechenizkiy and {van Wijk}, {Jarke J.}",
year = "2024",
month = oct,
day = "28",
doi = "10.4230/OASIcs.Commit2Data.8",
language = "English",
series = "OpenAccess Series in Informatics (OASIcs)",
publisher = "Schloss Dagstuhl - Leibniz-Zentrum f{\"u}r Informatik",
pages = "8:1--8:11",
editor = "Haverkort, {Boudewijn R.} and {de Jongste}, Aldert and {van Kuilenburg}, Pieter and Vromans, {Ruben D.}",
booktitle = "Commit2Data",
}