Automated Transaction Monitoring

Bachelor thesis (2019)

Authors

B. Kostense Electrical Engineering, Mathematics and Computer Science
R. Hageman Electrical Engineering, Mathematics and Computer Science
H.J. van der Wilk Electrical Engineering, Mathematics and Computer Science
B. van Walraven Electrical Engineering, Mathematics and Computer Science

Contributors

S.Y. van den Oever Computer Science & Engineering-Teaching Team - EEMCS (mentor)
O.W. Visser Computer Science & Engineering-Teaching Team - EEMCS (graduation committee member)
H. Wang (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2019 Bastijn Kostense, Rico Hageman, Hilco van der Wilk, Bram van Walraven
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Published Date

03-07-2019

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

For the past 10 weeks, we have been tasked with improving the performance of the transaction monitoring system of bunq, an internationally active mobile bank. bunq has requested that we improve this system by automating the training of the machine learning model, providing better input data for this model and creating additional machine learning models. During this project, we have been working at the offices of bunq on this system. This thesis will give an overview of our research, software design process and implementation.

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