The pandemic unquestionably changed every aspect of the retail industry, and employee relations is no exception. Unfortunately, with retail employees leaving jobs more frequently and an increased reliance on seasonal workers, employee fraud is on the rise. In fact, according to the 2022 National Retail Security Survey conducted by NRF and the Loss Prevention Research Council in partnership with Appriss Retail, 58.6 percent of retailers reported an increase in employee theft since the start of the pandemic.
Luckily, there are strategies that loss prevention teams can rely on to reduce the risk of internal theft and build stronger workforces. But before these retail teams can prevent this unnecessary loss, they must first understand the full breadth of why employee fraud is on the rise and how this epidemic negatively impacts their business.
Why Employee Fraud Is on the Rise
Historically, economic and social uncertainty has led to increases in crime, fraud, and abuse. So, it’s no surprise that these issues are growing in today’s climate. Consumers are currently faced with a looming recession, the lingering impacts of the COVID-19 pandemic, and recent layoffs across many industries. All these components contribute to a difficult employment landscape for retailers and increase the potential for fraud.
Yet, despite these factors, retailers are still trying to hire new employees quickly to make up for the labor shortage. In fact, a new study from Forrester and Workjam explained that 63 percent of retailers were experiencing a deficit among their frontline team at the start of this year.
To offset this deficit, many retailers are forced to hire short-term or seasonal employees and bring them into the store with less training than in years past. With less training and less connection to the company long-term, employees are more prone to making costly errors or committing fraudulent acts while on the clock. At the same time, these employees are also feeling the effects of a national rise in inflation, providing yet another incentive for theft or fraud.
The Different Forms of Employee Fraud
Employee fraud can occur in a variety of ways. For example, unintentional employee fraud can occur via cashier mistakes. Another common type of employee fraud is “sweethearting.” This occurs when an employee gives discounts or free items to friends or family.
Other examples of employee fraud include:
- Curbside delivery fraud
- Loyalty points fraud
- Price match and markdown fraud
- Employee-assisted refund fraud
- Cash theft
- Merchandise theft
- Delivery personnel theft
- Inventory manipulation
- Colluding with conspirators inside or outside of the company
Regardless of the type of fraud committed or the intention, these acts erode profitability and can lead to a domino effect among other employees if their peers are successful in their attempts. To combat this, it’s critical that loss prevention teams invest in strategies to mitigate fraud and improve employee relationships.
How Retailers Can Stop Employee Fraud
So how can retailers best stop fraud in its tracks? In the case of unintentional fraud, the solution may be more training and regular re-training based on performance metrics.
For the more advanced forms of employee fraud, however, retailers can rely on AI that detects unusual behavior and recommend a course of action. Exception-based reporting (EBR) uses advanced data analytics to review a large volume of transactions to pick up on irregularities. This triggers a warning for a first-time issue or a departure for an employee with recurring issues.
When paired with AI/ML models, EBR systems can detect anomalies in cashier behavior and store performance to identify even more types of fraud, shrink, and margin issues. As time progresses, the recommendations will be more accurate and more efficient for loss prevention teams. AI can also automatically perform next-step analysis which provides consistency in the investigation and resolution process.
The impacts of AI-driven EBR are powerful. By taking a data-driven approach, retailers will be alerted to more instances of fraud and the case investigation time will decrease—shortening the window of time for when a bad actor can impact the bottom line. In the future, emerging applications for AI, like generative AI, will help build case narratives and video analytics that can be used as additional data points to enhance the value of an EBR solution.
The Importance of Protecting Your Business
When it comes to fraud, no stone should be left unturned. Retailers must protect their business from the inside out by using data and analytics to catch every instance of fraud. In doing so, retailers will enjoy greater employee trust and relationships, stronger profitability, and better long-term success.
Dr. Vishal Patel is the chief technology officer for Appriss Retail. In this role he is responsible for all engineering functions, building and supporting the product suite, and helping bring new products to market that better serve Appriss Retail’s customers. He has more than a decade of software and programming experience working with a variety of different technology stacks, database solutions, and cloud providers. Previously, as the director of data science R&D for Appriss, he was responsible for building and deploying data application and machine learning models for retail customers as well as customers of Appriss Health and Appriss Insights.
