Over the past 20 years, data analysis has become an essential part of the audit process for the vast majority of audit organisations. Using data analysis in audit (generally referred to as “audit analytics”) has already provided significant benefits for audit organisations of all sizes across a broad range of industries, but there is still much progress that can be made by optimising the audit analytics process.
Audit analytics include a wide range of types of application, varying by sise and sophistication of the audit organisation, as well as by industry. Applications range from ad hoc analysis to support a given audit objective, through to repeatable automated procedures and on to continuous auditing and monitoring. There are common best practices that apply no matter where an organisation operates on the continuum of audit analytics, nor how far they have progressed from a traditional cyclical approach to a continuous and risk-based model.
