Loss prevention in retail

Inventory discrepancies, organized retail theft, return fraud: losses in retail have been rising for years. At the same time, AI, RFID, and connected security systems are changing how retailers identify and manage risks. As a result, loss prevention is increasingly evolving into a data-driven business strategy.

It often begins with small discrepancies. A product is missing from the shelf. Inventory counts do not match stock records. An item is scanned incorrectly at the self-checkout. Individually, incidents like these may seem insignificant. Taken together, however, they cause billions in losses for retailers worldwide. So what measures can help reduce these losses?

In the industry, this is referred to as “loss prevention.” In retail, the term describes all processes, technologies, and security measures designed to reduce or prevent financial losses – from shoplifting and inventory discrepancies to fraud, process errors, or losses throughout the supply chain. Today, it is no longer just about traditional theft prevention. Modern loss prevention increasingly combines security strategies with data analysis, process control, and intelligent technologies to identify risks at an early stage.

In the international retail context, there are several nuances in the terminology surrounding loss prevention.

The term “theft” refers to actual stealing – for example, shoplifting, organized retail crime groups, or internal fraud committed by employees.

“Shrink” or “shrinkage,” by contrast, describes the discrepancy between the inventory that should theoretically be available and the inventory that is actually present. The causes can vary widely:

The scale of the financial impact is illustrated by the EHI Retail Institute’s study Inventory Discrepancies in German Retail 2025.

The figures paint a clear picture: in 2024 alone, losses in German retail caused by theft from customers, employees, and service personnel amounted to roughly €4.2 billion. In 2023, that figure was still €4.1 billion.

According to the study, average inventory discrepancies amounted to 0.64 percent of net sales in German retail, based on total retail revenue of approximately €495 billion.

What stands out in particular is the pace of this development. Even though many retailers are investing heavily in security and prevention technologies, losses continue to rise. In this context, the study also points to broader economic factors: high inflation, rising living costs, and declining purchasing power may be contributing to increased theft.

Loss prevention is therefore becoming not only a technological and organizational challenge, but increasingly a reflection of wider social developments.

For a long time, retailers relied primarily on visible security measures such as cameras, anti-theft devices, security personnel, and alarm systems. These systems still play an important role. At the same time, however, they are increasingly reaching their limits.

Modern retail structures have become far more complex. Omnichannel models, self-checkout systems, e-commerce, and digital supply chains create new vulnerabilities. At the same time, organized retail theft has become more professionalized and increasingly exploits technological and operational gaps.

As a result, loss prevention is shifting from a reactive security function toward a data-based management system.

Technological development in retail today follows one central principle: achieving the greatest possible transparency regarding product movement, inventory levels, and potential risks.

To accomplish this, a wide variety of systems are connected:

One of the most important technologies in modern retail is RFID (“Radio Frequency Identification”). Products are equipped with small radio-frequency chips that can be automatically detected and tracked – without manual scanning, as required with traditional barcodes.

Surveillance systems are also undergoing fundamental change. Traditional CCTV cameras primarily recorded incidents. Modern systems powered by artificial intelligence, by contrast, analyze behavior in real time.

Retailers are also increasingly implementing intelligent shelving systems. So-called smart shelves can detect how many items are removed and whether unusual removal patterns occur.

These systems often work with RFID or weight sensors and are part of broader Internet of Things (IoT) infrastructures.

This can create several advantages at once:

• faster shelf restocking
• improved product availability
• earlier detection of potential theft
• fewer blind spots on the sales floor

Particularly for high-value products, smart shelves can provide additional security without visibly disrupting the shopping experience.

Some retailers are now testing intelligent shopping carts. These systems automatically recognize:

• which products are inside the cart
• whether items were correctly recorded
• whether merchandise is leaving the store unpaid

In some cases, shopping carts can even lock automatically if unpaid products are about to leave the store. These technologies are primarily intended to reduce so-called “push-out thefts” – incidents in which fully loaded shopping carts are pushed out of the store without payment.

Ultimately, the evolution of modern loss prevention reflects a broader transformation within retail. Security, logistics, data analytics, and customer experience are increasingly converging. Products, sales floors, supply chains, and digital processes are all becoming part of a connected system designed to identify risks as precisely as possible.

Retailers are attempting to make uncertainty technologically manageable. Whether through RFID, AI-powered cameras, smart shelves, or cloud platforms, these technologies ultimately pursue the same objective: greater transparency regarding products, processes, and movement within an increasingly complex retail ecosystem.

The real challenge in the years ahead may not be technological alone, but societal. The more intelligent security systems become, the more pressing the question becomes: how much analysis, data collection, and surveillance will customers ultimately accept in everyday life?