The Scenario – Revenue Discrepancies Uncovered During Initial Analysis
An accounting firm is conducting a year-end financial audit on a midsized commercial landscaping company.
The company uses contractors to provide various landscaping services to customers. Services can depend on the time of year, location and size of the property, and customer needs. Contracts are typically signed on an annual basis and must be renewed each year. Customers are invoiced monthly for services performed during the previous period, but the landscaping company projects the annual revenue from each customer in their financial system.
An initial analysis using standard financial procedures identifies significant anomalies in the revenue recorded for two customers. In the first case, a year-over-year comparison shows a significant increase in recorded revenue. In the other, a large spike in revenue is recorded toward the end of the accounting period that is not consistent with any of the customer’s previous invoices. Intelligent data management is needed.
To ensure the accuracy and legitimacy of the financial statements, the financial auditor requests that the client provide all business process documentation associated with the areas of risk selected for revenue testing.
The Challenge – Complex and Recurring Revenue From Numerous Clients
To maintain independence and ensure the completeness of the audit process, the auditor requests business process documentation for all customers for that year. These can include service orders, work orders, customer invoices, sales contracts and supplier service agreements, evidence of service completion, and other legal and governance documents.
The volume of documents associated with each customer adds to the complexity of the audit. Using traditional, manual approaches, the auditor would need to manually collect, open, read, review, and categorize each document before linking them with the associated financial transactions.
Further, the varying nature of the services offered each month makes it difficult for the client to project future revenues, while a limited contract management and reporting system creates significant opportunities for mistakes or omissions that can adversely impact the recording of revenue.
The Challenges – Intelligent Data Management is Needed
- Complex revenue recognition criteria from recurring contracts
- Significant variations in monthly revenue depending on delivered services
- Numerous business process documents associated with each customer
- Potential for customer churn or termination of agreements
- Revenue forecasting is dependent on estimates and historical trends
- Limited contract management system and financial controls
The Solution – Intelligent Data Management Vizschön™ Platform for Revenue Testing
The Vizschön™ Platform by Vigilant AI significantly reduces the time and resources required to conduct revenue testing.
The intelligent data management platform simplifies data capture from multiple sources and pinpoints discrepancies or areas of risk for further testing.
Financial auditors can then conduct a Test of Details, Test of Controls, and Cutoff Testing to verify the completeness, accuracy and occurrence of recorded revenue.
Advanced artificial intelligence and machine learning (AI/ML) links all available data to every accounting entry in a fully contextualized data lake. Auditors can more rapidly verify transactions and identify all critical documents associated with any financial transaction.
Key Platform Features
- Automated scanning and tagging of source business process documents
- Rapid cross-correlation of business process documents to accounting entries
- Ability to search terms in multiple languages
- Secure data architecture
The Results – A Faster and More Complete Test of Revenue
By leveraging the Vizschön™ Platform by Vigilant AI, financial auditors can conduct a more complete and independent test of revenue, ensuring that stakeholders can rely on the information provided in financial statements.
In this example, the platform enables the auditor to conduct a more in-depth analysis of the identified areas of risk. The Test of Details allows an auditor to understand if a large increase in year-over-year revenue is expected by examining all service orders against invoices to detect if the services provided have been potentially misstated. A further test of controls can then determine if there is a failure of financial controls, such as reviewing credit terms, contractual rates, and service provider reconciliations, leading to potential errors.
In addition, the test of Details can verify that the spike in revenue is legitimate. For example, the business process documentation could show that a customer engaged the landscaping company for additional design and construction work on a major renovation of their property.
Finally, Cutoff Testing would determine if services were delivered on a timely basis in the correct period or if the customer’s total revenue was simply carried forward into the next year, even though the renovation project is not recurring work, resulting an overestimate in projected revenue.
With Vizschön™ by Vigilant AI, financial auditors can spend less time collecting, linking and reviewing business process documentation and more time testing revenue against areas of risk such as the examples above.
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