Option C because data analytics techniques are especially effective at detecting unusual transaction behaviour such as duplicate payments, out-of-hours activity, abnormal amounts, or missing approval steps. This type of risk is well-suited to structured data analysis, making it the most detectable using standard audit analytics techniques.
Data analytics can be effective in detecting patterns indicative of fraudulent activities, such as unusual payment patterns, duplicate invoices, or other anomalies within accounts payable data. Analyzing large sets of data can help auditors identify irregularities that may be indicative of fraud in the invoicing and payment process.
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