Internal Audit Hyperautomation Blueprint Series: Revenue and Receivables | AuditBoard

Internal Audit Hyperautomation Blueprint Series: Revenue and Receivables

Internal Audit Hyperautomation Blueprint Series: Revenue and Receivables
  • Impactful automation opportunities in quote-to-cash

  • RPA, advanced analytics, data visualization, and API/iPaaS

  • Fraud detection and internal control automated analysis

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Complete the form to download Internal Audit Hyperautomation Blueprint Series: Revenue and Receivables.

Get your free copy of AuditBoard’s guide to hyperautomation for practical tips for successfully implementing hyperautomation in your revenue and receivables processes. 

In a time where “default is digital” has become the normal operating standard, it may come as no surprise that hyperautomation leads as one of the top technology trends. The rapid rise of hyperautomation in the last several years indicates a shift from basic, task-centric automation — enabled by stand-alone, non-integrated solutions like RPA, process mining, and machine learning (ML) — toward process-level automation and process orchestrations.

The trend toward hyperautomation may seem daunting for audit teams who have only recently implemented automation technologies like RPA and audit analytics solutions — but implementing hyperautomation in your audit processes need not be overwhelming. 

The second installment of AuditBoard’s Internal Audit Hyperautomation Blueprint Series provides an introduction to hyperautomation and guidance for how to implement it in revenue and receivables, a frequently audited business process containing many opportunities for hyperautomation. 

Download the first installment focused on Purchasing and Payables here.

Get your copy of the full guide for concrete guidance on implementing hyperautomation in the revenue and receivables lifecycle, including:

  • The most impactful automation opportunities in quote-to-cash, including an overview of commonly used systems and data files. 
  • Value-add focused procedures for incorporating RPA, advanced analytics, data visualization, and API/iPaaS into discovery analytics/data profiling. 
  • Fraud detection and internal control automated analysis and testing techniques.

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