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No retailer wants to think that their employees are stealing from them. Unfortunately, dishonest behavior from employees is one of the largest segments of retail loss:
- The average loss per dishonest employee at a store is over $1,200.
- 75% of employees admit to stealing from their employer at least once.
- 5% of an organization’s revenue is lost to employee theft, which amounts to $87,500 for c-stores every year
That’s a loss of over $7,000 a month. The most likely time for an employee to steal from a retailer is during a risk event.
What is a risk event?
Risk events are times when the cash drawer is open, but no sale is made. Examples include returns, cancels, and price adjustments. These events give opportunities for different kinds of employee theft.
The simplest example of employee theft at the point-of-sale terminal is called skimming. Skimming occurs when an employee removes some cash from the drawer and keeps it for themselves. Though these shortages are often caught when balancing the cash register at the end of a shift, experienced ‘skimmers’ can be more difficult to catch.
For example, an employee may be ringing up more returns than are needed by customers and taking the money for themselves. Employees engaging in this behavior may process more returns during their shift than is standard for the business. Because genuine returns result in cash being removed from the drawer, it becomes more difficult to spot when returns are falsified.
How do I identify risk events and stop theft?
To identify and stop risk events, retailers can utilize AI-driven loss prevention software. Loss Prevention Analytics creates a log of risk events and pairs them with video footage from that transaction. So, if an employee is skimming cash from the register by faking returns, the system will flag each return, because it is a risk event. By having this data, retailers can notice if a particular employee has a higher number of returns during their shifts. They then can use the video log to check the footage of the register from those risk events and note if the returns are legitimate, or if an employee is stealing.
Utilizing a data-driven loss prevention solution to spot theft also applies to other risk events, such as cancels and price adjustments. Using the right loss prevention technology is key for retailers who want to take advantage of their data and spot theft.
