Shoplifting in Retail: How AI Can Help Prevent Shop Theft

Did you ever see someone steal goods and hide them in their bags or change the price tags on commodities to get a lower price? Shoplifting is exactly what this sounds like.

What is Shoplifting?

Shoplifting is a type of retail theft that involves stealing goods without paying or attempting to underpay. The most commonly stolen items include clothing, electronics, jewelry, and groceries.

It is a big problem in the retail industry as traditional methods of surveillance aren’t so effective. So, shoplifting impacts the sales of the retailer and amounts to heavy financial losses.

Although it is a criminal offense, the number of cases related to shoplifting is significant. So, a solution, which is more robust, reliable, and efficient, is required in the first place.

This is where AI for retail steps into the picture. We will discuss the role of AI in preventing shoplifting later in this blog. First, let us understand how shoplifting occurs.

How Shoplifting Takes Place?

Shoplifting in retail can occur in a variety of ways. Some common methods that shoplifters use to steal merchandise from retail stores are:

1. Concealment

Shoplifters usually hide stolen items in clothing, purses, or bags. To achieve it, they tend to wear loose clothing to make it easier to hide items. This way of shoplifting is concealment.

2. Price Tag Change

Shoplifters often exchange expensive price tags for cheaper ones to buy expensive things at a lower price. Although it’s highly unethical and risky, people do it.

3. Grab and Run

Shoplifters grab the goods and run out of the store as quickly as possible. This highlights the shoplifter but retailers can’t do much. It is very common and most thieves escape being caught.

4. Distraction

Shoplifters can be a gang too. So, one of them distracts a store employee by asking for help while another person steals items from the store. By this, the actual thief is saved from being noticed.

Why does Shoplifting Take Place?

Ever thought about shoplifters? Whether they steal out of habit or for their luxurious craving? Is it their desperate behavior, or an undiagnosed mental illness? There is no one specific reason why shoplifting occurs. Yet, there may be some reasons.

The personal desires for items one can’t afford can motivate people to steal or shoplift. They can hide it or grab and run, whatever suits them.

Another reason could be to make money by selling the stolen item in black. Someone who doesn’t has any funds left can indulge in shoplifting easily.

But, not all theft is voluntary. Sometimes a person can suffer from psychological problems such as anxiety, obsessions, and compulsions. These disorders can cause a person to have maladaptive behavior such as stealing.

Whatever the reason, retailers across the globe are facing the shoplifting crisis. They are experiencing a spike in merchandise losses, known as shrink.

While shrink includes a variety of factors including external theft, employee theft, vendor fraud, and mislabeled items, about 37% of retailers’ shrink is due to external theft.

How to Mitigate Shoplifting Risks?

Retailers are implementing many strategies to prevent loss and mitigate risks. These include hiring security staff, installing security cameras, requiring manager approvals for any discounts, and investing in radio-frequency identification (RFID) systems.

However, shoplifting prevention systems powered by artificial intelligence are more efficient. In combination with existing approaches, they can considerably reduce the retailer shrink due to external theft.

How AI Prevents Shop Theft?

Artificial Intelligence is an emerging technology being used across industries to solve problems. The retail industry is no different.

AI in retail is helping retailers prevent shoplifting, identify counterfeiting, offer smart shopping experiences, manage inventory, and do even more.

Here are some ways in which AI can help in shoplifting prevention.

Smart Surveillance Systems

Retailers can install video surveillance cameras that monitor the store in real-time. The video footage is analyzed by machine learning models in real-time. The models try to interpret the body language and behavioral patterns of the people in the store. They also identify the people using facial recognition technology and items being robbed using RFIDs.

If the system finds any suspicious activity taking place within the store, it can alert the store manager or staff immediately. So, quick action can be taken against the person and prevent shoplifting.

Inventory Monitoring

Retailers can use machine learning algorithms to analyze sales data, compare it with inventory data, and identify if any products are stolen. The retailer can then take steps to better secure those products, such as by placing them in a locked display case or by increasing surveillance in that area of the store.

Predictive Analytics

Retail AI systems can analyze point-of-sale (POS) data to detect patterns in behavior that might indicate theft. For example, if a particular item is frequently sold without being scanned or if there are unusually high levels of returns or voided transactions, this could be a sign of shoplifting.

Wrapping Up

AI-powered video surveillance, sales analysis, and inventory management systems are helping retailers protect stores and reduce losses. However, it is important to ensure that these Retail AI systems do not violate customers’ privacy rights and are used ethically and responsibly.

Anubrain specializes in developing custom AI solutions that meet the unique needs of our customers. Contact us to know more.