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This study aims to investigate the moderating role of natural language processing natural language processing (NLP) on the relationship between AI-empowered AIS (data gathering, data analysis, risk assessment, detection, prevention and Investigation) and auditing and fraud detection.

Quantitative methodology was adapted through a questionnaire. In total, 221 individuals represented the population of the study, and SPSS was used to screen primary data. The study indicated the acceptance of the hypothesis that “Artificial Intelligence in AIS has a statistically significant influence on auditing and fraud detection,” showing a strong correlation between auditing and fraud detection. The study concluded that NLP moderates the relationship between AI in AIS and auditing and fraud detection.

The study’s implications lie in its contribution to the development of theoretical models that explore the complementary attributes of AI and NLP in detecting financial fraud.

A cross-sectional design is a limitation.

NLP is a useful tool for developing more efficient methods for detecting fraudulent activities and audit risks.

The study’s originality stems from its focus on the use of AI-empowered AIS, a relatively new technology that has the potential to significantly impact auditing and fraud detection processes within the accounting field.

Narrative disclosures offer further elucidation of a company's financial performance beyond what is presented in numerical format. This can assist stakeholders in gaining a deeper comprehension of the elements that impact reported earnings, thereby improving the quality of financial information. The current research explores the impact of narrative disclosure on the earnings quality of firms listed on the Amman Stock Exchange (ASE).

Appropriating an index to measure the narrative disclosure level in the research sample firms, the research utilizes an analysis of the textual content of nonfinancial reports and statements issued by the management of the ASE-listed nonfinancial firms between 2013 and 2022. The financial statements issued in the annual financial reports are also adopted to extract data on earnings quality and the controlling variables. The analysis of the data and attainment of the findings necessitate using the panel data.

It is indicated that narrative disclosure affects earnings quality. To be precise, the greater the narrative disclosure, the lower the absolute value of the voluntary discretionary accruals and thus the higher the quality of accounting earnings.

The findings contribute to new research on disclosure issues, particularly narrative disclosure, which enhances reader confidence in financial and nonfinancial reports and prevents misleading and manipulated information.

This research helps decision-makers understand the relationship between reports, statements and earnings quality in a firm. It's unique in exploring this relationship, especially in developing countries. The study is the first of its kind in Jordan, known for its economic stability and strategic location in the Middle East, making its findings applicable to similar environments.