Work

Tri-Layer Anomaly/ Fraud Detection Framework for Audit and Business Analytics

Year: 2025

Type: article

Abstract: This whitepaper introduces the "Tri-Layer Anomaly/Fraud Detection Framework," a practical, multi-layered approach designed by Charm Myae Aung to enhance anomaly and fraud detection in audit and business analytics. Implemented in KNIME Analytics Platform, the framework combines statistical methods, machine learning, and time series analysis to detect irregularities across structured business datasets. Its strength lies in its adaptability to various audit scenarios, improving the precision and efficiency of anomaly and fraud detection.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15540277

Author: Charm Myae, Aung

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6911969176

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