How big data tax governance reduces excessive deposits and loans? Evidence from Chinese listed firms

Purpose The prevalence of excessive deposits and loans in corporations signals potential financial misconduct and poses systemic risks. This study aims to investigate how a technology-driven tax administration reform can serve as an external governance mechanism to mitigate this issue. The authors argue that by enhancing transaction-level transparency, such digital infrastructures can curb firms’ ability to maintain opaque and risky financial structures. Design/methodology/approach This paper develops a multiperiod difference-in-differences model grounded on the quasi-natural experiment of Golden Tax Project III (GTP III). In addition, controls the year-fixed effect and industry-fixed effect, clustering at the firm level. This model is used to gauge the influence of big data tax governance on enterprises’ excessive deposits and loans. Findings Using a difference-in-differences model on Chinese A-share firms from 2010 to 2021, the authors find that the staggered implementation of China’s “Golden Tax Project III” (GTP III) significantly reduces the likelihood of a firm exhibiting an excessive deposits and loans structure. The authors identify reduced agency costs, enhanced information transparency and decreased tax avoidance as the key underlying mechanisms. Practical implications The findings offer a blueprint for global policymakers, regulators and investors. The authors propose that similar digital tax audit infrastructures can be leveraged as an early-warning system to detect financial irregularities and liquidity risks, thereby improving market stability and corporate oversight beyond the confines of tax collection. Originality/value To the best of the authors’ knowledge, this study is the first to conceptualize GTP III as an exogenous, large-scale shock to corporate opacity and to document that a state-operated, data-rich tax infrastructure can directly reduce the prevalence of excessive deposits and loans.