U. Obazee

This study investigated artificial intelligence applications in relation to financial reporting quality among deposit money banks in Nigeria. The specific objectives were to examine the extent to which artificial intelligence accounting, artificial intelligence data analytic, artificial intelligence auditing and artificial intelligence predictive applications have influence on financial reporting quality of deposit money banks in Nigeria. This study was a field survey for the year 2025. A total of 2,839 accountants, auditors and management staff constituted the population size, while 351 staff of deposit money banks in Benin City of Edo state formed the sample size by employing stratified and purposive sampling selection techniques. It was a quantitative research design and the main instrument used in collecting data was questionnaire administration. The statistical techniques employed include descriptive statistics, Pearson correlations, variance inflation factor and least squares regression method. The study found that artificial intelligence accounting, data analytic and predictive applications have significant positive t-statistics value of 2.480, 2.441 and 2.796 with a probability value of 0.010 (1%), 0.010 (1%) and 0.005 (0.5%) respectively. It was also revealed that artificial intelligence auditing applications has no significant influence on financial reporting quality among deposit money banks in Nigeria but has positive t-statistics value of 1.634 with a probability value of 0.103 (10%). Thus, the study concluded that artificial intelligence applications in accounting, data analytics, auditing and predictive analytics are critical in facilitating enhancement in financial reporting quality among deposit money banks. It therefore recommended that organisations should take advantages of artificial intelligence innovation by training and developing their accountants, auditors and senior managers in areas of financial transactions analyses and prediction to enhance financial reporting quality for the interest of stakeholders.

The broad objective of the study was to investigate the relationship between board diversity and corporate tax aggressiveness in Nigeria. The longitudinal research design was used in investigating the extent of tax aggressive practices of the oil and gas companies. This was appropriate for this study because it revealed the relationship among variables in the same group of individuals over an extended period of time so as to establish more robust results. The secondary source of data was used and data were sourced from the Nigerian Exchange (NGX) as at 31st December, 2022 for various years. The study covered a time frame of twelve (12) years from 2011 to 2022. The Panel Least Squares (PLS) estimation technique was adopted for analysis purpose. This was carried out with the aid of the E-views (10.0) software and Excel package. Findings obtained revealed that board independence (BIND) and board ethnic diversity (ETD) have positive and significant relationship with effective tax rate (ETR), board gender diversity has a negative and significant relationship with ETR while board national diversity (NAD), board meeting (BMEET), firm age (FAGE), and firm size (FSIZE) have no significant relationship with ETR. The study concludes that only BIND, GEND, and ETD are good predictors of corporate tax aggressiveness in Nigeria. This study thus recommends that the composition of the board should comprise more non-executive and independence directors, qualified and skillful female directors, and more foreign directors so as to enable the board to perform its supervisory and monitoring roles as expected. This study also recommends that further empirical studies should be conducted using other sectors such as education, service as well as information and communication technology (ICT)