Synergy Between Internal Control, Forensic Accounting, And Artificial Intelligence In The Financial System. Optimal Model For Fraud Detection And Financial Information Transparency In The Digital Age

Abstract

The paradigm of internal control and forensic accounting in private financial institutions, mainly banks and savings and credit cooperatives, which have traditionally carried out their processes manually and on a sample basis, must take on new transformational challenges by incorporating artificial intelligence tools to provide a holistic predictive and reactive system that guarantees the traceability of information and mitigates accounting data bias. This study focuses its efforts on proposing an optimal model of synergy between internal control, forensic accounting, and artificial intelligence to predict and address potential financial fraud. The findings were the result of applying a quantitative methodology with a pragmatic approach, using inferential statistical techniques and instruments under an analytical and descriptive method with the contribution of Chi-Square and Correlation of variables in the SPSS system for hypothesis validation. The study population focused on 422 entities in the Ecuadorian financial system, concluding that financial system organizations must incorporate artificial intelligence into internal control and accounting processes to achieve effectiveness in financial information transparency and have predictive models that guarantee data reliability. The optimal model suggested and recommended by the study is MinimaxET (error minimization and information transparency maximization model).