Many startups spend too much money from the outset. Average restaurant startup costs vary from a…
Author: EHL.AI
Fraud detection in ERP systems using Scenario matching
ERP systems invariably provide controls, such as Segregation of Duties (SoD) These are insufficient, and it…
SNARE: A Link Analytic System for Graph Labeling and Risk Detection
Accounting irregularities raise significant risk for corporations and investors. Most of the well-known techniques for detecting…
Large Scale Detection of Irregularities in Accounting Data
Fraudulent financial reporting is a growing problem, says John Sutter. Sutter: Auditors are required to apply…
Transaction Mining for Fraud Detection in ERP Systems
Fraud continues to be a major threat to industry and government. Traditionally, organizations have focused on…
Data Mining Journal Entries for Fraud Detection: An Exploratory Study
Fraud detection has become a critical component of financial audits and audit standards have heightened emphasis…
A Business Process Mining Application for Internal Transaction Fraud Mitigation
Internal fraud has received a great deal of attention from interested parties like governments or non-profit…
Auditing Journal Entries Using Extreme Value Theory
The area of journal entries is deemed to pose a high risk of material misstatements to…
Visual Exploration of Journal Entries to Detect Accounting Irregularities and Fraud
Fraud investigators have recently recognized the importance of data visualization for fraud detection. Data visualization is…
Detection of Anomalies in Large-Scale Accounting Data using Deep Autoencoder Networks
Deep autoencoder neural networks can be used to detect anomalous journal entries. Experiments on two real-world…