@inproceedings{0de1b723cff94d6789fb2156f3bbb104,
title = "User-adaptable natural language generation for regression testing within the finance domain",
abstract = "Reporting duties and regression testing within the financial industry produce huge amounts of data which has to be sighted and analyzed by experts. This time-consuming and expensive process does not fit to modern, agile software developing practices with fast update cycles. In this paper, we present a user-adaptable natural language generation system that supports financial experts from the insurance industry in analysing the results from regression tests for Solvency II risk calculations and evaluate it with a group of experts.",
keywords = "Finance, Natural Language Generation, Regression Testing",
author = "Anupama Sajwan and Florian Matthes and Daniel Braun",
note = "Publisher Copyright: Copyright {\textcopyright} 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.; 22nd International Conference on Enterprise Information Systems, ICEIS 2020 ; Conference date: 05-05-2020 Through 07-05-2020",
year = "2020",
doi = "10.5220/0009563306130618",
language = "English",
series = "ICEIS 2020 - Proceedings of the 22nd International Conference on Enterprise Information Systems",
publisher = "SciTePress",
pages = "613--618",
editor = "Joaquim Filipe and Michal Smialek and Alexander Brodsky and Slimane Hammoudi",
booktitle = "ICEIS 2020 - Proceedings of the 22nd International Conference on Enterprise Information Systems",
}