Audit of Application and Database Controls
Description
In modern financial environments, errors and fraud can originate not only from external attackers but also from weaknesses in internal processes. Therefore, organizations must rely on strong automated controls to guarantee that every transaction is validated, reconciled, securely stored, and auditable. Students are expected to explore the importance of input validation, ensuring that incorrect or malicious data (such as negative amounts, excessively large fields, or special characters) is rejected before entering the system. They will also evaluate reconciliation processes, which are fundamental in finance because input records must always match output totals in reports, statements, or summaries. Any discrepancies could indicate data integrity failures or fraudulent activity. Additionally, the lab requires testing of referential integrity at the database level, where relationships between tables (e.g., customers, accounts, transactions, invoices) must be preserved by primary and foreign key constraints. This prevents orphan records and ensures consistent financial information. Finally, students will analyze audit trails and system logs, which record user activity, timestamps, and system actions. These mechanisms are vital for accountability, compliance with regulations, and forensic investigations in case of disputes. The expected outcome is for students not only to execute the tests but also to critically assess the system’s strengths and deficiencies, and then recommend improvements to FinGroup’s financial control framework.
Files
Steps to reproduce
# Audit of Application and Database Controls – Dataset This dataset contains anonymized data, SQL scripts, Python validation code, and reconciliation outputs to replicate the laboratory exercise described in *Audit of Application and Database Controls*. ## Contents - `data/`: Sample transactional data, reports, and audit logs. - `scripts/`: SQL and Python scripts to perform validation, reconciliation, and referential integrity checks. - `results/`: Example reconciliation summaries and findings. - `docs/`: Laboratory guide (PDF) describing the problem, requirements, and guiding questions. ## Citation If you use this dataset, please cite: > Nestor Alzate Mejia, Cano Beltrán, Jhon Haide (2025). *Audit of Application and Database Controls – Dataset.* Universidad Cooperativa de Colombia. ## License Creative Commons Attribution 4.0 International (CC BY 4.0).
Institutions
- Universidad Cooperativa de Colombia