Anomaly Detection in Double-entry Bookkeeping Data by Federated Learning System with Non-model Sharing Approach

Sota Mashiko, Yuji Kawamata, Tomoru Nakayama +2

Anomaly detection is crucial in financial auditing, and effective detection requires large volumes of data from multiple organizations. However, journal entry data is highly sensit…