5 Ways Manufacturers Can Leverage Technology to Curb Counterfeiting If you are a manufacturer you don't want someone to copy your product so we bring to you the best tactics to fight forgery

By Nitin Gupta

Opinions expressed by BIZ Experiences contributors are their own.

You're reading BIZ Experiences India, an international franchise of BIZ Experiences Media.

Shutterstock

The constant rise in the counterfeit products has created a negative impact on the world market. As far as India is concerned, apart from having tremendous business potential, it stands as a significant market for counterfeit products. Counterfeiting is spread across all the sectors/industries like pharma, retail, FMCG, etc. From toothpaste to aspirin and to high-end handbags, the counterfeit is everywhere. The problem arises when the companies fail to track down this market and collect their end consumer data, and they are unable to keep an eye on the distribution network. The counterfeit market in India has reached up to Rs 40,000 crore in the organized sector. The market for fakes in the world is close to 1.6 trillion dollars, and manufacturers are spending close to 204 billion dollars annually to fight this problem.

Here are five ways, manufacturers can leverage technology to curb the counterfeiting.

Blockchain Based Technology

Blockchain has generated a lot of curiosity and expectations among the people. It is a great concept and solves the purpose of maintaining the transactions details and contracts among the participating parties. But to preserve the immutability or transactions it needs to be backed by proof of work. A public blockchain without proof-of-work is a fragile system, so the cost of maintaining the blockchain makes it economically non-viable to be deployed for any practical use-case unless the ticket size of the product is significant ($10K or more) and all participating parties are ready to bear the technological overhead. Also, blockchain technology alone cannot solve the problem of copying the code for verification. It needs to work together with technologies such as AI, and other smarter way to detect duplication of the verification codes. There are private blockchain which can overcome the proof of work with some consenting algorithms, but it would be overkill and unnecessary technological overhead to use a blockchain for product validation purpose in most of the cases. Then again the problem of copying the validation code by counterfeiters needs to be addressed in addition to blockchain technology.

RFID Tags/Labels

RFIDs are a comparatively expensive solution. RFID reader is needed to read the code embedded in the RFID chip, but anyone with a reader can read and clone the code. These tags can be read using RFID reader only, so it is difficult for the buyers to check the authenticity of the products. However there are some NFC tags which can be read by many of the smartphones, but again they face the problem of being copied by counterfeiters.

Micro Tags

Micro tags are mainly used in Pharmaceuticals. These tags are very small, edible and can be put directly on the pills. Few solution providers offer scan-able micro tags, but a special scanning device is required to scan the pills so end users are generally unable to scan it.

QR code Authentication using smartphones

This solution is very popular. Many solution providers offer QR code based labels/stickers. These tags can be scanned using any smartphone making it easier for the end users to check the genuineness of the product. Users are generally directed to an API or the product website on the scan of these tags. The drawback of QR codes is, anyone can copy and put them on counterfeited products, and counterfeited products will pass the validation, no matter whether you print them using 1024 DPI or different level of printing methods or special paper. It's just the QR code which gets converted to the alphanumeric code which is then used by the backend to validate. So, the QR codes used in existing track and trace system, do not effectively catch counterfeits unless they are backed by some monitoring system or AI to check the Anomaly and other characteristics. Some solution providers give scratch-able QR codes that can be scanned after purchasing the tag. So the buyer has no way to check the product authenticity before making the purchase.

AI backed Smart Technology

AI backed tags provide a foolproof and cost-effective solution. The solution is to apply algorithmically coupled, AI-backed semi-open codes. The buyers can scan the open part of the tag to check the product authenticity with a certain probability. Once they purchase the product, they can open the scratch-able part and scan it to be sure of the product authenticity. On the backend, the patent-pending technology and AI-based anomaly detection system keeps watching the scan activities of the protected tags and the open tags. Once the protected tag is scanned all the corresponding open tags gets invalidated. The system also raises the RED flags for any abnormal or anomalous scan pattern.

Nitin Gupta

Co-founder, CEO and CTO at NeuroTags

Business Ideas

70 Small Business Ideas to Start in 2025

We put together a list of the best, most profitable small business ideas for BIZ Experiencess to pursue in 2025.

Starting a Business

How to Develop the Mindset for a Billion-Dollar Success, According to Raising Cane's Founder

Todd Graves was turned down by every bank in town when he started. Here, he sits down to share his mentality on success, leadership and building a billion-dollar brand.

News and Trends

Reliance Retail Launches FMCG Brand 'Independence' In Gujarat

Independence includes diverse categories such as staples, processed foods, beverages, among other daily essentials

Starting a Business

These Brothers Started a Business to Improve an Everyday Task. They Made Their First Products in the Garage — Now They've Raised Over $100 Million.

Coulter and Trent Lewis had an early research breakthrough that helped them solve for the right problem.

Business News

Here Are the 10 Jobs AI Is Most Likely to Automate, According to a Microsoft Study

These careers are most likely to be affected by generative AI, based on data from 200,000 conversations with Microsoft's Copilot chatbot.