Application of Big Data Analytics in Internal Audit of Banks

Internal Auditing has a major role in corporate governance of banks. It examines governance systems, risk management and internal control processes. Data from various sources is critical evidence for audits. In the past, data validation, evaluation and analysis were from paper documents and records. Increase in number of customers and scale of operations today, generates "Big Data". Special platforms, software tools, and graph databases are now used for "Big Data Analytics (BDA)". BDA helps early identification of compliance challenges and risks, enabling timely correction. BDA with IOT based ‘continuous audit’ ensures real-time monitoring of financial and other operations. A data-driven audit strategy leads to early detection of latent frauds. This substantially reduces financial misstatements and fraud. The auditor can analyse vast datasets in real-time, making the audit process more efficient and effective for safeguarding financial integrity and compliance. This paper discusses the role of BDA in internal audit of banks, analyses challenges in incorporating BDA and suggests a conceptual framework for implementation.