Libra: A One-Tool Solution for MLD4 Compliance
At a glance
- Project leader : Dr. Dandolo Flumini
- Project team : Mohammadreza Amirian, Fernando Benites de Azevedo e Souza, Dr. Mark Cieliebak, Prof. Dr. Rudolf Marcel Füchslin, Dr. Stefan Glüge, David Graf, Dr. Lukas Lichtensteiger, Dr. Thilo Stadelmann, Lukas Tuggener
- Project budget : CHF 795'250
- Project status : completed
- Funding partner : CTI
- Project partner : Deep Impact AG
- Contact person : Dandolo Flumini
Description
Compared with earlier regulations, the 4th European Money Laundering Directive (MLD4) imposes rigorously increased requirements. It compels obliged entities to conduct in depth screenings of customers and their associations. The Libra Project aims at providing a one tool solution for meeting MLD4 compliance. The project will in particular offer a cloud based “Google-like” search experience to bring up reliable information on persons of interest and their surroundings.
Publications
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Wehrli, Samuel; Hertweck, Corinna; Amirian, Mohammadreza; Glüge, Stefan; Stadelmann, Thilo,
2021.
Bias, awareness, and ignorance in deep-learning-based face recognition.
AI and Ethics.
2(3), pp. 509-522.
Available from: https://doi.org/10.1007/s43681-021-00108-6
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Glüge, Stefan; Amirian, Mohammadreza; Flumini, Dandolo; Stadelmann, Thilo,
2020.
How (not) to measure bias in face recognition networks [paper].
In:
Schilling, Frank-Peter; Stadelmann, Thilo, eds.,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Cham:
Springer.
Lecture Notes in Computer Science ; 12294.
Available from: https://doi.org/10.1007/978-3-030-58309-5_10
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Benites de Azevedo e Souza, Fernando; Duivesteijn, Gilbert François; von Däniken, Pius; Cieliebak, Mark,
2020.
TRANSLIT : a large-scale name transliteration resource [paper].
In:
Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020).
12th Language Resources and Evaluation Conference (LREC) 2020.
European Language Resources Association.
pp. 3258-3264.
Available from: https://doi.org/10.21256/zhaw-20082
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Stadelmann, Thilo; Amirian, Mohammadreza; Arabaci, Ismail; Arnold, Marek; Duivesteijn, Gilbert François; Elezi, Ismail; Geiger, Melanie; Lörwald, Stefan; Meier, Benjamin Bruno; Rombach, Katharina; Tuggener, Lukas,
2018.
Deep learning in the wild [paper].
In:
Proceedings of the 8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR).
8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Siena, Italy, 19-21 September 2018.
IAPR.
Available from: https://doi.org/10.21256/zhaw-3872