Wang, YunsenChiu, TiffanyVasarhelyi, Miklos A.2024-12-102024-12-102024https://hdl.handle.net/10272/24653Process mining is an efficient method that can analyze the full population of transactions using the event log of business processes. Conventional rule-based process mining techniques can detect anomalies; however, it tends to trigger a large number of false alarms. To improve the efficiency of anomaly detection using process mining, this study adopts a deep learning-based classification approach to detect anomalies in the traces of event logs. This approach contributes to the literature by proposing a non-rule-based process mining technique based on deep learning. Results demonstrate that the proposed non-rule-based process mining method can help auditors focus on transactional anomalieengAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/Process miningDeep learningAnomaly detectionFraudulent activitiesjournal article10.4192/1577-8517-v24_5open access53 Ciencias Económicas