SAS no. 99 states that you “should ordinarily” presume there is risk of material misstatement due to fraud relating to revenue recognition. If you do not identify improper revenue recognition as a risk of material misstatement due to fraud, you should document the reasons supporting this conclusion. The assumption in this chapter is that you are searching for material misstatement of revenue in the source journal. I should clarify that the phrase sale of goods will be used throughout the chapter to indicate revenue earned from the sale of tangible goods, services, or rental income.

Chapter 13 described the methodology for building a fraud data analytics plan for financial accounts. Using the plan, this chapter will focus on the fraud data analytics search routines for fraud scenarios in the source journal.

Revenue is the candy jar of choice used by management to misstate the financial statements. The candy jar has many different types of candy to cause revenue to be over‐ or understated. Fraudulent revenue may be recorded through a source journal or through a journal entry. Management may decide to misapply GAAP, thereby causing the recorded transaction to misstate the financial statements.

For the auditor, revenue recognition requires an understanding of the industry and the organization. The auditor needs to have the ability to apply and interpret the principles of revenue recognition to the audit program. It sounds simple; however, there are many widely accepted revenue recognition procedures and many situation‐specific ways to interpret and apply each of these procedures. Just as organizations are different, the kinds of revenues they generate are different. Consequently, these different types of revenues need different recognition and different reporting methods. Therefore, each revenue system also needs an audit program tailored to its uniqueness.

What Is Revenue Recognition Fraud?

The fundamental revenue recognition concept is that revenues should not be recognized by a company until the revenue is earned and realized or realizable. Revenue is earned if your company has fulfilled its obligations under the revenue contract. Revenue is realized when there is a real expectation that the customer will pay for the goods or services provided by your company.

Therefore, revenue recognition fraud occurs when revenue is recognized on the financial statements and the revenue is not earned or there is no expectation that the customer will fulfill its obligation to pay for the services. The second aspect is that management has concealed the fact that the revenue is not earned or the receivable is not realizable.

Inherent Fraud Risk Schemes in Revenue Recognition

It is generally recognized that misstating revenue is the most common fraud technique used by management to misstate the financial statements. The auditing standards created the phrase that improper revenue recognition is a presumed fraud risk. Therefore, it is critical that fraud auditors understand the fraud scenarios used by management to create fraudulent revenue:

1. False revenue and false customer scheme is the process of creating a false customer and recording through the source journal a false revenue transaction for the false customer.
2. False revenue and real customer scheme is the process of recording through the source journal a false revenue transaction that a real customer did not order. In this scheme, the real customer may retain the goods or may return the goods.
3. Real customer and improper recognition of revenue schemes through historical schemes:
   1. Holding the books is simple; the revenue is shipped in the subsequent period but recorded in the current period.
   2. Channel stuffing is more abstract than holding the books open. In channel stuffing, the customer is real, the goods have been delivered, and the terms of sale are achieved. Channel stuffing is referred to as accelerating sales by causing a real customer to order more goods than a customer would normally purchase through the offering of inducements that are intended to shift revenue versus a normal marketing technique. The traditional inducements are deep discounts, rebates, and extended payment terms.
   3. Sham sales transactions occur with the recording of a revenue transaction with a real customer; however, there is no economic benefit for either party. Typically, tendencies in sham transactions are that there are no cash transfers between the two parties; the two parties have a relationship; and both parties tend to be in the same industry. The sole purpose of sham transactions is to increase revenue versus create an economic benefit.
   4. Soft sale is recording a revenue transaction through the source journal before a fully executed contract exists between the two parties.
   5. Undisclosed return policy scheme is recording a revenue transaction through the source journal when the customer has a right to return the product.
   6. Incomplete terms schemes is recording a revenue transaction through the source journal before all terms and conditions of the sales contract are fulfilled.
   7. Upfront fees are for services provided over a period of time. The fraud scheme is recognizing the upfront fee as current revenue versus amortizing the revenue over the life of the contract.
   8. Non‐operating revenue recognized as operating revenue occurs when a cash receipt from a non‐operating revenue source is recorded as operating revenue.
4. Revenue is misstated because of the misapplication of GAAP in relation to the customer contract. These schemes need to be identified as part of the brainstorming based on how your company achieves the five criteria of revenue recognition.
5. Revenue created through changing GAAP without disclosure.
6. Revenue recognized through improper application of GAAP related to specific accounting statements:
   1. Percentage of completion schemes
   2. Bill‐and‐hold schemes
   3. Income recognized on consignment sales
7. Falsifying accounts receivable aging or the failure to write off uncollectable receivables.
8. Revenue created through accrued revenue: journal entries schemes.

All of these schemes have been committed by management in some company. The study of prior schemes by the fraud auditor will enhance their practical application of the suggested fraud data analytics routines.

Inherent Fraud Schemes and Creating the Revenue Fraud Scenarios

For ease of reading, the following will repeat the guidance in earlier chapters.

1. Person committing: The starting point is to understand how revenue is reported and how internal persons are held accountable for meeting sales numbers in the company. The person committing would start with financial management. In a regional sales environment, the misstatement may occur through one division or one sales region.
2. Direction of misstatement: Most reported fraud schemes result in the overstatement of revenue. Therefore, overstatement is the most predictable direction of misstatement. However, GAAS fraud risk factors need to be considered in determining the direction of misstatement. If the fraud auditor is focusing on a specific region versus the company as a whole, then the direction of testing is dependent on the historical success of the region. A highly successful region is more likely to understate revenue as a form of cookie jar, whereas a region having difficulty in meeting internal goals is more likely to overstate its revenue.
3. General ledger account: What is critical about revenue recognition is which accounts are used for the sales journal and which accounts are used for revenue accrual journal entries.
4. Type of entity: The same structure identified in the shell company chapter is relevant for financial reporting.
5. Fraud action statement: Describes how the fraud scenario occurs in the financial account. The fraud action statement describes whether the transaction is false or real, whether the entity is false or real, and whether the transaction is recorded through a source journal or journal entry.
6. A GAAP implication focuses on either whether the recorded revenue transaction achieved the five criteria of revenue recognition or how management concealed the failure to achieve the five criteria.
7. Impact statement for revenue recognition should provide specifics to the impact on the financial statements.

Identifying Key Data on Key Documents

The revenue system has more diversity than any other core business system. The industry will impact the documents that will comprise the system. Think about the difference between retail, health care, telecommunications, wholesale, and construction. Within each industry and within each company the revenue system is more unique than payroll, which is somewhat standardized throughout all industries. In this chapter, we will present the methodology for detecting revenue fraud in the financial accounts.

The revenue cycle comprises sales order, which is a customer purchase order or internal sales order; shipping records; internal sales invoice; customer payment; and customer return or customer sales adjustment. The understanding of the information on these documents becomes the basis of the fraud data analytics plan. Consistent with Chapter 3 the documents all have a control number, control date, sales invoice amount, and a description of what was ordered that is posted to a general ledger account. Furthermore, in the revenue cycle, in contrast to the expenditure cycle, the documents may originate from an internal source or an external source.

Sales order is the document that starts the sales process. The sales order may originate from an internal salesperson or from a customer's purchase order system. If the document originates from the customer's purchase order system, then the consistency of information is by customer versus internal systems. This will impact the usability question in the planning phase.

Shipping process occurs through an internal fleet of trucks or through an external fleet of vehicles. If the shipping occurs through an external source, the critical issue is how to match the internal records to the external shipping records. If the shipping records are internal, then fraud data analytics for improper recognition is possible.

Internal sales invoices are created either through one centralized billing system or through billing systems that are decentralized by location. The sales invoice becomes the central point of the fraud data analytics.

Customer payments depending on the industry may originate from currency, credit card, paper check, electronic transfer, or via a loan transaction. Is the payment applied to a specific invoice or to an account balance?

Customer return or sales adjustment is the contra entry to a customer payment transaction. These transactions are associated with reversing false transactions.

Now that the fraud auditor understands the documents that comprise the system and the information on the documents, the fraud auditor can start the process of building the fraud data profile.

Fraud Brainstorming for Revenue

The proper recognition of revenue is defined in IFRS 15, Revenue from Contracts with Customers. As a disclaimer, the intent of this section of the chapter is not to be an authoritative discussion of the new accounting standard, but rather, the importance of understanding how to use the standard in the search for a fraud scenario or the associated concealment strategy. Fraud data analytics brainstorming starts with understanding the basic framework for proper revenue recognition:

1. Persuasive evidence of an arrangement exists—this is intended to ensure that an understanding exists between the two parties and that a final understanding of the terms and conditions is achieved.
2. Delivery has occurred or services have been rendered—this assumes that the customer takes title and assumes the benefits and risks of ownership.
3. The seller's price to the buyer is fixed or determinable as to payment terms, right of return, discounts, and rebates.
4. Collectability is reasonably assured because all the terms and conditions are achieved and the customer has the ability to fulfill its obligations.

To illustrate the concept of fraud brainstorming for fraud data analytics, let's focus on the collectability concept. So, how could management conceal the collectability concept or how can we find data that indicate the collectability concept was falsified? From a data perspective we will focus on the concept of the probability of whether the customer will pay for a recorded revenue transaction at the recorded amount.

For discussion purposes, we will focus on three different situations. There are two types of revenue transaction from the collectability perspective: false revenue or real revenue.

• False revenue to a false customer. Clearly your company will not collect from a fictitious customer. However, there are cases that management has used their personal funds to create the illusion of collection. Among management's fraud strategies:
  • Record the revenue at year‐end so the false revenue does not appear on the aging report.
  • Reverse the revenue transaction after opinion date.
  • Clear the false revenue transaction with a sales adjustment or return transaction.
  • Use a rebilling scheme to create a current date on the false revenue.
  • Use a variation of a lapping scheme to cause the aging report at year‐end to reflect the balance as paid.
  • Apply a dormant credit to the false revenue transaction.
• False revenue to a real customer. The assumption is that the customer did not order the item and the customer will not accept the item:
  • Since the transaction is a false revenue transaction, the previous concepts apply.
  • Conceal the return of the item from the customer that indicates the return is posted to the customer account after the opinion date. In one publically traded company, management concealed the returns by making false statements to the customer regarding the shipment. Then management had the items returned to a secret warehouse to conceal the return from the auditors.
  • Crediting the customer account with a false sales adjustment versus a sales return transaction.
• Real revenue to a real customer. The assumption is that the contract is valid and the sales transaction is complete. The focus is on the probability the customer will remit the required funds under the terms of the contract. In one sense all customers are the same; however, from a collectability perspective customers are very different.
  • New customers with credit limits that exceed normal credit limits for new customers.
  • Existing customers:
    • Active customers with no history of delinquent payments should be excluded from this analysis; the exception is for channel stuffing.
    • Nonactive customers with a history of delinquent payments and a change to credit amount or creditworthiness should be the focus of the analysis.
  • Improper application of GAAP.

From a GAAP perspective, let's use price concessions on tangible goods to brainstorm how revenue can be overstated and concealed from the auditors. For purposes of discussion, price concessions are: rebate, allowance or a price reduction, or other terms of agreement. Since our discussion is on revenue our discussions will not focus on other accounts such as a potential liability. The price concession discussion assumes collectability; the question focuses on the total amount of consideration to be received and the proper reporting of the event.

The starting point is to understand how the transaction should be recorded from a GAAP perspective. The second aspect is a review of standard customer contracts to ensure the contract is consistent with GAAP. Assuming management's accounting policies are GAAP compliant, now the fraud auditor can start building the fraud data analytics plan.

The next important step is to discuss how management could conceal the over‐ or understatement of revenue. Using the rebate concept, the rebate could be recorded as a marketing expense versus a contra revenue account. Management could hire a marketing company to pay the rebates and record the disbursement as a marketing expense.

Remember, the purpose of the brainstorming session is to assist the auditor in developing the fraud action statement. Consistent with Chapter 13, the following fraud action statements are the generic list, which needs to be converted for the GAAP implications of the revenue transaction.

The primary techniques used to overstate revenue are:

1. Record false revenue through either a false customer or a real customer.
2. Record real revenue in the wrong period or account.
3. Record accrued revenue that is false or improper recognition of revenue through a journal entry.
4. Record contra revenue as an operating expense.
5. Record non‐operating revenue in operating revenue.
6. Consideration should also be for uncollectable revenue hidden in the accounts receivable.

The primary techniques to understate revenue:

1. Record real revenue in the wrong period.
2. Record through a journal entry improper recognition of revenue.

FDA for False Revenue Scenarios

False revenue schemes either occur through a false customer or through a real customer. In false customer schemes, the search starts with fraud data analysis for shell customers and then proceeds to the transactional analysis. In real customer schemes, the fraud data analytics searches for clues in the sales journal or returns and adjustments in the subsequent period.

False Revenue for False Customers through Accounts Receivable Analysis

Since false customers seldom pay for false revenue transactions, the fraud data analytics should search for customers with material sales and no posting from cash receipts. The design of the report would in essence recreate the accounts receivable account. The report would have eight columns of data providing both dollar amount and frequency of postings:

• All debits originating from a sales journal
• All other debits
• All credits originating from a cash receipts journal
• All other credits

While the analysis will detect the false revenue, the issue becomes the timing of the procedure. If the opinion date is after the first quarter of the next year, perform the procedure at year‐end, otherwise the procedure must be performed midyear. In the midyear approach, the search for the false revenue scenario should be performed on final quarter sales.

The report will have a few phases before the report reveals the false revenue. Start with summarizing the data as recommended. Exclude those customers with no sales or minimal sales. Then exclude those customers reflecting a significant amount of postings from the cash receipts journal. The first search is for customers that have no cash receipts posting and recorded sales. If the false sales were recorded through the year, then the report will reflect significant other credits. If the false sales are recorded at the end of the year, then the account will only reflect sales journal postings.

Remember, one of the concealment strategies is a form of lapping. If the lapping scheme is being used, then the customer will have cash receipts posting. However, since the posting must be transferred to the true customer, the customer account should also have a material amount in the other debits and credits column.

Fraud Concealment Strategies for False Revenue Fraud Scenarios

The second approach to search for a fraud scenario is through the concealment strategy used by management. The following concealment strategies all can be found through the study of historical fraud stories:

• The weakness in the false revenue schemes is the realization principle. False customers typically do not pay for goods and services. There are published cases where financial management used personal funds to create the illusion of customer payment. In some way and at some time, the false receivable will need to be cleared.
• Lapping is typically associated with an asset misappropriation scheme. However, the technique can be used to hide the false revenue from the aging schedules. The concept is simple: Apply a real customer's payment to a false customer's account payment at the end of the year. After the aging report is created, the customer payment is transferred back to the real customer. The fraud data analytics should search for transfer of customer payments between customer accounts after the creation of the aging schedule.
• The astute auditor should see how the concealment techniques can be used in different industries. In the banking industry, management or a loan officer might be trying to hide an uncollectable loan. The lapping technique would conceal the bad loan from the delinquency report. Similar but different, the delinquent loan could be concealed by rolling over the loan using internal bank funds. Also, see the discussion on rebilling in what follows.
• In accounts receivable, there are dormant credits associated with both dormant customers and active customers. The dormant credit is transferred to clear the false revenue. The fraud data analytics searches for the transfer of an aged credit to a customer's account.
• Rebilling is a technique to hide a delinquent invoice from the aging report. The concealment technique is concealing a true delinquency for a real customer with real revenue. The financial management is trying to hide the bad‐debt expense. The technique is also used to hide false revenue.
• In the rebilling scheme the delinquent invoice is credited with an adjustment or return, thereby removing the customer invoice from the aging report. A second invoice is created for the same customer with a current date. The adjustment or sales return is recorded through a source journal and is posted to the correct general ledger account. The fraud data analytics is first matching sales adjustments to aged sales invoices. The second step is to search for a current duplicate invoice for aged invoice. The use of a customer order number or line item descriptions on the invoice is a useful technique for the matching.
• A more sophisticated approach to hide the sales adjustment is to post the sales adjustment as a contra transaction in the sales journal, thereby concealing the adjustment in the sales journal. The search for a contra entry in the sales journal is an easy technique using the number anomaly strategy.
• Returns and adjustments is the most common technique to clear false revenue. The return or adjustment is typically posted after the opinion date. There are many variations of the returns and adjustments scheme. Instead of clearing the false revenue with the sales return, which the auditor is looking for, the false revenue is cleared with a sales adjustment transaction and the inventory is added back as an inventory adjustment. The fraud auditor needs to understand the different systems or transactions that exist in the revenue system to clear a customer invoice.
• Shipping concealment strategies vary by the organizational structure of the company. The first step is to ship the inventory somewhere. The shipment location for the false revenue schemes maybe another company warehouse, public warehouse, freight forwarder location, etc. The fraud data analytics should summarize sales by customer by shipping address, providing aggregate dollar value and the frequency of the invoice. Depending on the number of customers, the fraud auditor will need to determine how to shrink the report.
• There are many other concealment strategies associated with fraudulent revenue schemes. However, not all schemes are useful in fraud data analytics. The undisclosed terms and conditions scheme is often associated with fraudulent revenue; however, the concept does not lend itself to fraud data analytics. As a reminder, it is important to understand what you can find and what you cannot find with fraud data analytics.

Fraud Data Analytics for Percentage of Completion Revenue Recognition

In revenue recognition, there are specific accounting pronouncements for specific revenue transactions. It would be impossible for this book to describe the fraud data analytics for all the statements. Therefore, to illustrate the use of the methodologies, we have selected percentage of completion.

While there are different variables that are considered in percentage of completion revenue recognition, this discussion will focus on the incurred cost account. The account is typically composed of a subledger of projects, and the expenditures are posted from either a source journal or a journal entry. The first report is a summary of the subledger by total expenditures. The sole purpose is to identify the material account balances or changes in material balances. The report can be enhanced by creating a comparison report (i.e., total expenditures at third quarter by account to fourth quarter by account) and calculating a dollar change and percentage change.

The use of disaggregated analysis would summarize which journals created the account balance for all accounts in the subledger: accounts payable, payroll, other, and general journal entry. The purpose of the report is to identify which journal created the account balance. The first sample selection is based on accounts that have a material general journal entry posting. The journal entry should be selected and summarized by account posting. The second analysis is material postings from the accounts payable journal. Summarize the accounts payable by vendor, providing aggregate dollar value, aggregate frequency, maximum invoice, minimum invoice, and average invoice for the final month (or final quarter) of the report period. The sample selection starts with a fraud data profile of a false vendor invoice.

Summary

The purpose of this chapter was to describe a methodology for searching for fraud scenarios in the sales journal. Consistent with Chapter 13, the fraud auditor will need to adapt the methodology to their industry and company. A second aspect is the unique issues associated with fraud in GAAP interpretation. The fraud data analytics plan will need to be further adapted to search for fraud in GAAP.

As a reminder, the fraud audit procedure must be linked to the fraud scenario and the fraud data analytics.