Navee Blog | AI and machine learning in counterfeit detection: revolutionizing brand protection

In today’s rapidly evolving global market, counterfeiting has emerged as a significant threat, impacting brands, deceiving consumers, and fueling organized criminal activities. Despite these, counterfeit products continue to plague the market, making its way from stands in busy touristy streets to even legitimate marketplaces.

Counterfeiting is not as harmless as it seems and counterfeiters are becoming more creative with each passing day, often accompanied with their own complex supply chains. It is this complexity that requires new ways to tackle this hydra-like multi-headed monster.

Today, with innovations in artificial intelligence (AI) and machine learning, brand protection has taken a leap forward. For one, counterfeit detection is not only faster but also has become more accurate and scalable thanks to such technologies. This blog dives deep into the world of counterfeiting and we’ll see just how crucial these new technologies are playing an increasingly vital role in protecting brand integrity and ensuring consumer trust.

The rabbit hole of counterfeits: who is affected?

Counterfeiting runs deep and it is most certainly not a victimless crime; it affects brands, consumers, governments, and entire industries. Globally, the counterfeit industry is a multi-billion-dollar operation, spanning across a vast array of sectors including fashion, pharmaceuticals, consumer electronics, and even food products. It’s safe to say that where there is money, there’s bound to be counterfeits.

According to a jointly published 2019 report entitled “Illicit trade: trends in trade in counterfeit and pirated goods” by the Organisation for Economic Cooperation and Development (OECD) and the EUIPO, the international trade in counterfeit and pirated products could have amounted to as much as $509 billion in 2016, estimated to be 3.3% of world trade – up from $461 billion in 2013, representing 2.5% of world trade. What drives the point further is mentioned that the numbers are based only on global customs seizures and do not even include counterfeit goods that were not seized. In addition, these amounts do not include domestically produced and consumed counterfeit goods, or pirated digital products distributed online.

Evidently, it’s the consumers that fall prey to this and are often deceived into buying counterfeit goods, risking not only their hard-earned money but frighteningly also their health and safety in some cases. Counterfeit pharmaceuticals, for example, are a leading cause of preventable death, especially in developing nations where regulations might be less stringent.

Brands not only suffer substantial financial losses but what every company fears and can be a nightmare to patch up — their damaged reputation and a complete loss of consumer trust. Add to that already startling list are legal complications that arise with it.

Governments also find themselves on the losing end due to decreased tax revenues and increased law enforcement costs.

The domino effect of counterfeit goods touches nearly every facet of global trade.

Enter e-commerce and why brand protection matters more than ever

Counterfeiters have evolved with the rise of e-commerce, capitalizing on the convenience these platforms offer consumers. For brands, this has become a double-edged sword: while online marketplaces provide access to a global audience, they also serve as fertile ground for counterfeit goods to thrive.

According to a study “Misuse of E-commerce for Trade in Counterfeits” by the EUIPO and OECD in 2021, to give you an idea, footwear (34%), clothing (17%), perfumes and cosmetics (10%), and leather articles (9%) were among the most commonly detained counterfeit products linked to e-commerce. The analysis also solidifies the claim that for criminals, e-commerce provides an increasingly attractive means to facilitate the trade in counterfeit goods for a large range of product categories.

This creates a vicious cycle for brands: not only do they lose direct revenue to counterfeiters, but they also risk permanent damage to the trust they’ve worked hard to build over years, or even decades. For luxury and highly regulated industries, the stakes are even higher. Counterfeit luxury items don’t just eat into profits but can cause permanent damage to a brand’s exclusivity and allure, while fake pharmaceuticals pose serious health risks that can lead to lawsuits and long-term reputational harm.

In a marketplace dominated by digital transactions and global reach, brand protection is more critical than ever. Without it, brands face not just short-term losses but potentially irreversible damage to their reputation and market position.

Traditional counterfeit detection methods: offline and online approaches

But most certainly brands must have already been aware of this. For some, they already have various systems and strategies in place, either through their own internal team or outsourced solutions.

Before AI became widely adopted, counterfeit detection methods both online and offline were much more manual and resource-intensive. These traditional systems, though effective to some extent, struggled to keep up with the rapid rise of counterfeiting, especially as e-commerce expanded globally.

Offline counterfeit detection systems

Offline counterfeit detection has long relied on physical inspection techniques and the use of security features on products. These methods included holograms, watermarks, serial numbers, barcodes, and RFID tags. These security features were integrated into the products or packaging, allowing inspectors to identify counterfeit products through direct observation.

physical inspection & security markers: Inspectors, whether in-store or during customs checks, would manually examine products for discrepancies in labels, serial numbers, or watermarks. These methods worked well for small batches, but with growing counterfeit operations, they quickly became labor-intensive and unsustainable. Furthermore, counterfeiters increasingly replicated even these security features, making it difficult to distinguish fakes from genuine goods without sophisticated tools.
human error in detection: Physical inspection techniques were vulnerable to human error. Whether it was a missed serial number mismatch or a barcode oversight, the risk of inconsistencies grew with the volume of items being checked. Manual methods also lacked the ability to scale effectively, especially as counterfeiters began operating on a much larger scale. This was especially problematic for industries like pharmaceuticals and luxury goods, where the stakes were particularly high.
time-consuming processes: These manual inspections often took too long to be effective on a large scale, especially at customs checkpoints or large distribution centers. By the time fakes were detected, they had often already made their way into the market, causing damage to brand reputation and consumer trust. Furthermore, counterfeiters evolved to create near-identical replicas of products, reducing the effectiveness of visual inspections.

Take for example this case in July 2024 in Hong Kong. The authorities arrested counterfeiters who sold fake tickets to a sold out Sammi Cheng concert — succesfully replicating these tickets with highly convincing security features such as QR codes and hologram stickers.

Online counterfeit detection strategies

As the internet and online marketplaces exploded in popularity, counterfeiters quickly shifted their operations to the digital realm. For brand protection teams, this created a new challenge: detecting and removing counterfeit goods from countless online platforms. Before the introduction of AI, online detection relied heavily on manual keyword searches, digital monitoring, and takedown requests.

Keyword-based searches: Teams manually searched for counterfeit products online using keywords related to the brand or product name. While this method was useful initially, counterfeiters quickly adapted by making subtle changes to product names or descriptions. For example, a counterfeit product might use a misspelled brand name (like “Adibas” instead of “Adidas”) or include vague descriptors like “luxury shoe” instead of the actual brand name. These changes allowed fakes to slip through undetected by traditional keyword searches.
Human-led market monitoring: Teams spent hours combing through online marketplaces, social media platforms, and independent websites to identify infringing listings. This process was highly labor-intensive and often ineffective in covering the vast number of online sales channels where counterfeit goods were sold. As a result, many fakes went unnoticed, while legitimate listings were sometimes mistakenly flagged, causing frustration for brands and sellers alike.
Manual takedown requests: Once counterfeit listings were identified, the process of removing them was also time-consuming. Teams had to manually submit takedown requests to each platform, often waiting days or even weeks for a response. In many cases, counterfeit listings would reappear shortly after removal, creating an endless cycle of identification and takedown with no real long-term solution in sight.
Limitations in scalability: The sheer volume of online marketplaces, social media platforms, and independent websites made it nearly impossible to monitor all counterfeit activity. With counterfeiters operating across global platforms, brand protection teams struggled to scale their efforts effectively, leaving significant gaps in coverage.
Inconsistent enforcement: Even when fakes were identified, enforcement varied significantly from platform to platform. Some websites were quick to respond to takedown requests, while others were slow or reluctant to act. This inconsistency left brands vulnerable to counterfeiters who knew which platforms were less vigilant.

“It’s a game of Whack-a-Mole, and it’s a constant every day.”

Words from an executive when asked about counterfeiting and specifically the issue of takedowns in the industry of merchandising in the music industry. Capitalizing on the immense popularity of superstars in music, counterfeiters feed off the hype and remain persistent in online marketplaces.

It gets overwhelming, exhausting, and this is where AI solutions come in and offer a helping hand.

AI-Powered counterfeit detection: a game changer for brand protection

As counterfeit detection methods struggled to keep up with the rise of online marketplaces and complex supply chains, the introduction of AI-powered solutions has revolutionized how brands protect themselves. Both offline and online counterfeit detection processes have become faster, more scalable, and far more accurate.

Offline AI developments in counterfeit detection

1. AI-enhanced product authentication

In the past, product authentication depended largely on physical inspection by trained professionals. However, AI has now taken over this task, employing machine learning algorithms to analyze product features in real-time. For example, AI can scan subtle details like texture, stitching patterns, or even the molecular composition of a product to verify its authenticity. This technology eliminates the margin of human error and can process vast quantities of products quickly, which is invaluable for industries like pharmaceuticals or luxury goods.

2. Smart devices for on-the-go validation

Devices such as AI-driven scanners and mobile apps now enable field inspectors, customs officers, and retailers to authenticate products directly through their smartphones. This real-time detection ensures that counterfeits are intercepted before they reach consumers, bolstering brand protection. For instance, handheld scanners powered by AI can instantly verify whether a pharmaceutical product is authentic, by comparing its chemical composition to a known database.

3. Reducing time and resource strain

AI has reduced the time-consuming nature of manual inspections. For industries that previously relied on human labor to examine products, AI-powered systems are now capable of automatically scanning and identifying irregularities on a production line, dramatically speeding up the inspection process. This streamlining means that brands can focus more on maintaining product quality while leaving much of the grunt work to the technology.

Online AI developments in counterfeit detection

1. Advanced image recognition

AI has completely transformed how counterfeit products are detected online. Advanced image recognition technologies enable AI systems to scan vast amounts of product images, analyzing details that are invisible to the human eye. For instance, an AI model trained to recognize a particular luxury watch can analyze thousands of listings on e-commerce sites and flag any product that deviates even slightly from the original—whether in color, texture, or dimensions. This process is vital for companies like Navee, whose image-based technology plays a key role in scouring the web for counterfeit goods.

2. Automation of takedown requests

The time-consuming process of manually filing takedown requests is a thing of the past. AI not only detects counterfeit listings but also automates the removal process by sending real-time alerts and takedown notices to online platforms. This automation ensures that infringing content is quickly addressed and removed, greatly reducing the time counterfeit goods spend in circulation. Companies like Miraculous Corp benefit significantly from this technology, as AI can efficiently detect and eliminate fake product listings across multiple platforms, safeguarding their brand image.

3. Scaling monitoring capabilities

AI has enabled brands to scale their monitoring efforts beyond human capabilities. Instead of focusing on one or two platforms, AI systems can monitor thousands of online marketplaces, social media platforms, and independent websites simultaneously. The technology is especially effective in identifying fake listings that cleverly bypass traditional keyword-based searches by using subtle misspellings or alternative descriptors. This capability is a major breakthrough for companies operating in global markets, where counterfeiting is rampant across numerous regions and platforms.

4. Real-time data analysis for smarter counterfeit detection

Perhaps the greatest benefit of AI in counterfeit detection is its ability to analyze data in real-time. AI systems can process vast amounts of data, track trends, and quickly adapt to new tactics employed by counterfeiters. This real-time monitoring and response capability helps brands stay ahead of counterfeiters, adapting their strategies as the counterfeit market evolves. It also allows for the identification of suspicious patterns in online behavior, flagging new counterfeit trends before they become widespread issues.

Why choose Navee for online counterfeit detection?

At Navee, we offer state-of-the-art AI technology designed to help brands protect themselves from the growing threat of counterfeiting especially in the new age of eCommerce. Our advanced image-recognition tools and AI algorithms provide unparalleled accuracy, ensuring that your brand stays protected.

Navee’s versatility and scalability

Technology: We harness a semi-exact image search technology that can sift through diverse photo alterations and bypass new strategies of counterfeiters. Our machine learning algorithms continuously evolve, learning from every counterfeit detection to improve accuracy.
Cross-industry applications: Our technology is adaptable across various industries, from fashion to entertainment.
Large-scale detection: Navee’s AI can scan millions of listings across multiple online platforms, reinforcing takedowns of counterfeit products at a scale impossible for manual methods.
Client success focus: Despite being AI and tech-driven, Navee’s priority is people. We ensure client success through strong relationships, offering personalized support and solutions to meet brands’ unique needs.

Watch our robust technology in action with our client, Miraculous Corp.

Protect your brand with AI-powered solutions

With Navee, our focus is to shift the approach towards counterfeits from reactive to proactive. By combining cutting-edge technology with industry-specific expertise, Navee provides a powerful tool to protect your products, your brand, and your customers from the dangers of counterfeiting — all this, one image at a time.

Talk to one of the experts now in our team and see the tailored solutions that could work best for your brand.

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