The Impact of Big Data Technologies and IFRS 9 on Improving Credit Audit Quality in Iraqi Banks: A Field Analytical Study for the Period (2018-2022)

Abstract

This study measures the effect of internal auditors' awareness of big data technologies on credit audit efficiency and financial disclosure quality in light of IFRS 9, and analyzes the main barriers to adopting these technologies in the Iraqi banking accounting environment. A descriptive-comparative-analytical approach was applied to a purposive sample of 48 internal auditors across four Iraqi economic institutions - only one of which is a commercial bank, with the remaining three engaged in credit-related dealings with banks - a composition that limits generalization of the field results to the Iraqi banking sector as a whole. A validated 24-item questionnaire covering three dimensions was used, with content validity confirmed by an expert panel and construct validity established through item-total correlations (0.61-0.79); reliability reached a Cronbach's alpha of 0.87. One-sample t-test and correlation/regression results showed a statistically significant positive relationship between auditors' awareness of big data technologies and credit audit efficiency (sample mean 88.63 versus a hypothetical mean of 72). Regional benchmarking revealed a wide credit gap, with private-sector credit-to-GDP in Iraq at 6.7% against a regional average of 48.6%. The study recommends mandating the Expected Credit Loss (ECL) model under IFRS 9 and establishing a national credit information system