Benford's law is a statistical technique that analyzes the frequency distribution of leading digits in numerical data sets. It is commonly used to detect anomalies or irregularities in financial transactions that could indicate fraud. Fraudulent transactions often deviate from the expected distribution predicted by Benford's law, making it a quick and effective way to flag suspicious activity for further investigation.
While regression analysis, control self-assessments (CSAs), and interviews with control owners may also provide insights, they are not as directly suited for quickly identifying fraudulent patterns in large sets of transaction data as Benford's law analysis.

When no documented security procedures exist, the IS auditor's next step is to identify and assess the security practices currently in place. This allows the auditor to determine whether effective controls are operating, even if undocumented, and to evaluate the associated risks before recommending formal documentation.

The most important aspect to review during the planning sessions for a post-implementation review is the business use cases. These use cases outline the specific business requirements and objectives the application was meant to address. Reviewing them ensures that the system's functionality aligns with the original business needs, helping to determine whether the system delivers the expected value and meets stakeholders' expectations.