Determinants of Financial Statement Fraud: ADO Framework

Abstract

Purpose: The primary objective of this study is to explore the factors that contribute to the detection of Financial Statement Fraud (FSF) and to propose future research directions in the field of Financial Statement Fraud Detection (FSFD).

Design/Methodology/Approach: This study identifies the key determinants of fraud and organizes the findings using the Antecedents, Decision, and Outcomes (ADO) framework. This structured approach provides meaningful insights and offers clear directions for advancing research in the field.

Findings: The study uncovers eleven critical factors shaping FSFD, emphasizing four pivotal decisions that drive effective fraud detection. It also highlights ten key outcomes of FSFD, including enhanced governance, transparency, investor protection, risk optimization, and a stronger ethical framework. Additionally, the research introduces a conceptual framework, offering a deeper understanding of FSFD and pointing to essential areas for future exploration.

Research Implications: This study provides valuable insights for auditors by unraveling the complexities of fraud. By identifying the key factors influencing fraud detection and prevention, it enhances auditing practices, thereby promoting financial integrity and transparency.

Originality: This paper is one of the first to integrate the ADO framework to examine the factors impacting FSF detection. It proposes a comprehensive conceptual framework, offering vital insights into the dynamic evolution of FSFD and suggesting essential areas for future exploration.