Automated System for Improving Audit Data Processing Through DAMA-DMBOK Best Practices and Low-Code

Abstract

In the context of financial auditing, the efficient retrieval of accurate data, minimization of reprocessing efforts, mitigation of inherent risks in data processing, and improvement of information quality represent crucial objectives. In this regard, we present an automated system designed to optimize data processing in auditing. This system provides an automated assessment of the six data quality dimensions according to the DAMA model: completeness, reasonability, accuracy, uniqueness, validity, and consistency. This process is essential to determine whether data sources meet the necessary standards for use in various analytical processes. The tool was validated in the Wholesale Banking Management of Banco de Crédito del Perú, where it successfully analyzed 100% of data sources in the commercial credit audit, reducing the processing time of each source by 10 times. These results confirm that our software significantly contributes to improving data processing in the field of financial auditing. This system has proven to be effective and reliable in enhancing the overall efficiency and accuracy of financial audits.