Applications of Artificial Intelligence in Forensic Auditing: Tools, Challenges, and Opportunities for Fraud Detection

Valencia-Arias, Alejandro; Raunelli Sander, Juan Manuel; Tuesta Torres, Edgar Roland; Gaviria Rodríguez, Diana Yanet; Arango Arango, Juan Guillermo; Valencia, Jackeline

doi:10.22059/ijms.2026.399766.677862

Applications of Artificial Intelligence in Forensic Auditing: Tools, Challenges, and Opportunities for Fraud Detection

Articles in Press

Document Type : Review article

Authors

Alejandro Valencia-Arias ¹

Juan Manuel Raunelli Sander ²

Edgar Roland Tuesta Torres ³

Diana Yanet Gaviria Rodríguez ⁴

Juan Guillermo Arango Arango ⁵

Jackeline Valencia ⁶

¹ Escuela de Ingeniería Industrial, Universidad Señor de Sipán, Perú, 14000

² Facultad de Ingeniería Arquitectura y Urbanismo, Universidad Señor de Sipán, Perú, 14001

³ Escuela de Posgrado USS, Universidad Señor de Sipán, Perú, 14001

⁴ Facultad de Ciencias Económicas y Administrativas, Instituto Tecnológico Metropolitano, Colombia, 50010

⁵ Ciencias Básicas, Instituto Tecnológico Metropolitano, Colombia, 50010

⁶ Vicerrectoría de Investigación y postgrado, Universidad de Los Lagos, Chile, 5290000

10.22059/ijms.2026.399766.677862

Abstract

In an environment where financial crimes are characterised by increasingly complex structures, artificial intelligence is positioned as a technology with the potential to redefine forensic auditing. The present study employs a systematic review in accordance with the PRISMA 2020 protocol, with the objective of analysing how the incorporation of AI techniques transforms this practice beyond its operational functions. The analysis reveals a high level of disciplinary fragmentation and the absence of a cohesive conceptual framework, which hinders the consolidation of knowledge. It is imperative to comprehend that AI-assisted forensic auditing should not be perceived as an independent technical apparatus, but rather as a praxis that functions within the confines of institutional, ethical, and epistemological frameworks. This standpoint enables us to examine the conditions that legitimise its adoption, as well as the limits of its effectiveness. The study calls for a re-evaluation of the principles that guide forensic auditing in digital contexts. This is because intelligent systems are now being used, which demands new forms of analysis, control and accountability. The study does not propose immediate answers.

Keywords

Artificial intelligence

forensic auditing

fraud detection

intelligent systems

algorithmic governance

Subjects