This repository contains a zipped dataset of digital onboarding event logs used in the research paper titled "Using Process Mining to Reduce Fraud in Digital Onboarding," published by MDPI Fintech.
Digital onboarding is an essential process for financial institutions, allowing them to verify the identity of new customers and establish a relationship with them. However, this process can be vulnerable to fraud and other malicious activities, leading to financial losses and reputational damage for the financial institution.
To address this issue, the research paper "Using Process Mining to Reduce Fraud in Digital Onboarding" proposes a process mining approach to identify potential fraud and reduce its occurrence during digital onboarding.
The dataset in this repository consists of event logs collected from the digital onboarding process of a financial institution. The event logs contain information about each step of the process, including the time and date of the activity, the user ID, and the activity performed.
The dataset is provided in a zipped format and can be extracted using any standard compression software. The dataset contains a single file in CSV format.
Researchers and practitioners can use this dataset to replicate the experiments conducted in the research paper or to perform their own analysis of digital onboarding processes. The dataset can be loaded into process mining software, such as ProM or Disco, for analysis.
If you use this dataset in your research, please cite the following paper:
BibTeX entry:
@article{silva2023using,
title={Using Process Mining to Reduce Fraud in Digital Onboarding},
author={Silva, Matheus Camilo da and Tavares, Gabriel Marques and Gritti, Marcos Cesar and Ceravolo, Paolo and Barbon Junior, Sylvio},
journal={FinTech},
volume={2},
number={1},
pages={120--137},
year={2023},
publisher={MDPI}
}The dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Please see the LICENSE file for more information.