“How Technology is Helping Businesses Across India in Fighting Counterfeit”

“How Technology is Helping Businesses Across India in Fighting Counterfeit”

-Authored by Mr. Nitin Gupta- Co-founder, CEO & CTO, NeuroTags

The counterfeit market in India has reached about Rs 40,000 crore and is expected to grow more. If we talk about the world market, then the numbers reach up to $1.6 trillion and are expected to go up to $4.2 Trillion by 2022. Companies are investing billions every year in fighting counterfeit, but the results are not as expected.

Honestly speaking, the brands at the moment are not well equipped with the effective Anti-Counterfeit measures.  Brands in India will have to adopt new technology to prevent the counterfeits. Fortunately, there are new technologies like NeuroTags which are specifically focused on solving the counterfeit problem with the help of smart algorithms and AI.

Let's have a look at the current systems deployed by the Brands in the current market and their drawbacks and what kind of technology actually solves the counterfeit problem effectively.

Holograms Tags/Labels/Stickers

Holograms have been the oldest method to prove the authenticity of a product. Various companies use their trademark or some unique design on the hologram stickers. These stickers are supposed to be present the authentic products only. The companies also keep changing the hologram design to beat the counterfeiters. But copying the holograms has become very easy these days. Also, the holograms are simple stickers, so the product buyers have no way to check the genuineness of the product other than trusting the hologram. This method is ineffective to prevent the counterfeits.

RFID Tags/Labels

This is a comparatively expensive solution than the others. 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.

Authentication via QR code labels

Many solution providers offer QR code labels/stickers. These tags can be scanned using any smartphone making it easier for the end users to check the authenticity of the product. Scanning of these tags usually redirects users to an API or the product website.

The problem with these 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 scratchable 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.

Blockchain Based Technology

The blockchain is a good concept, but a public blockchain without proof-of-work is a very weak system, and the cost of maintenance of blockchain makes it economically un-viable to be deployed for any practical use case unless the ticket size of the product is very large ($10K or more). 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 verification codes.

AI backed Smart Technology

NeuroTags provides a foolproof and economical 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 genuineness with a certain probability. They can open the scratchable part after purchasing the product and scan it to be sure of the product authenticity. On the backend, the patent-pending technology and AI-based anomaly detection system keeps monitoring the scan activities of the closed tags and the open tags. The system immediately raises the RED flags for any abnormal or anomalous scan pattern.

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