In contemporary organizations, Journal Entries serve as fundamental components of financial statements and hold valuable information. Nevertheless, these entries are frequently generated and managed by employees who have access to sensitive financial data. As a result, they become a significant source for carrying out fraudulent activities. Implementing robust data analytics and continuous monitoring models has become crucial in preventing fraud and mitigating associated risks. These models aid organizations in identifying anomalies within their accounting systems. However, designing an effective data analytics model requires careful consideration of various factors, particularly the selection of Key Risk Indicators (KRIs) and the technical execution of the model.