Accounting Controls and Financial Data Quality in Credit Unions

Abstract

This study investigates the influence of accounting control elements on the qualitative attributes of financial information inside credit unions in Northeastern Thailand. The research employed a sequential mixed-methods approach and multiple regression analysis to investigate the effects of five control types: preventative, detective, corrective, directive, and compensating, utilizing data from 181 CU executives. Findings indicate a multifaceted relationship between controls and data quality. Detective and compensating controls, bolstered by standardized accounting software, were the most robust and consistent positive indicators of data quality, relevance, and completeness. While preventative controls are a robust indicator of reliability, they had a negative correlation with timeliness (β=−0.576). Excessive preventive measures hinder operations by obstructing bureaucracy. The study concluded that effective financial governance requires credit unions to transition from rigid control frameworks to a strategic integration that prioritizes detection and technological compensation to enhance data quality while maintaining efficiency. The results guide regional collaborative resource distribution and policy enhancement.