V1I3P9

Audit Technology Adoption and Its Influence on Detecting Financial Reporting Fraud and Misstatements

Sodiq Ogunmola^1*

Abstract

The most adoptions of modern audit tools such as data analytics, machine learning (ML), artificial intelligence (AI) and computer-assisted audit techniques (CAATs) have acted like game-changers in detecting financial reporting fraud and misstatements. On the contrary, many traditional audit methods include a high degree of manual sampling along with judgment from the concerned professional that could not be sufficient to identify very complex or highly subtle fraudulent activities. This will include a full literature review of previous studies published on audit technology adoption and how these impacts detecting financial fraud along with efficacy challenge, and limitation; as well as points about methodology section for implementing these technologies to auditing practice and how such data driven approaches further enhance audit effectiveness, efficiency, and reliability. From findings, there is indication that there is considerable improvement regarding fraud detection capability in an organization via adoption of audit technology, yet auditors should be mindful of technological reliance complemented by use of human judgment, ethics, and data governance.

Keywords:

Audit Technology, Financial Fraud Detection, Misstatements, Data Analytics, Machine Learning, Artificial Intelligence, CAATs, Internal Control