Edition 88
How SQRL Codes Help with Fraud Detection
by By RLA Standards Committee Reverse Logistics Association

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Fraud costs everyone since the losses are ultimately absorbed by the consumer. Counterfeit fraud is the most insidious because it is often difficult to detect. In 2015 the average shrink rate was 1.38%, costing the overall U.S. retail economy $45.2 billion.1 Shoplifting with returns for cash is most onerous. Organized Retail Crime (ORC) has perfected sophisticated schemes that defy the inspections of beleaguered customer service personnel. Retailers estimated that holiday return Fraud cost $2.2 Billion alone in 2015, Retailers surveyed estimate that total annual returns will reach $260.5 billion, or 8 percent of total retail sales, with $9.1 billion of retailers’ annual returns expected to be fraudulent, or 3.5 percent of the industry’s total returns. While it costs retailers 1 to 3% of their revenue, it costs manufacturers easily twice that much.2

While loss prevention personnel address these issues to some extent, the sophisticated thief circumvents too many human based monitoring procedures. Thus the fraud detection and prevention soluitions (FDP) market is expected to grow from $16.62 Billion in 2017 to $41.59 Billion by 2022.3 Authentication solutions are expected to have the largest market share and dominate the FDP market from 2017 to 2022. Transaction authentication continues to become more sophisticated. Incomm’s POS data mining continues to penetrate addition market segments with their transactional Rosetta Stone.

Single-Factor Authentication (SFA) such as transaction validation provides a significant barrier to the casual shoplifter. However sophisticated (and often organized, professional) thieves will often replace legitimate purchases with counterfeit or fake products. These schemes are often sufficiently sophisticated as to pass a visual inspection: Computer components are switched out and replaced with junk, for example.



How do you prevent this? Recently, Amazon announced a new counterfeit detection program called “Transparency.” Manufacturers can purchase a special label from Amazon that will allow consumers to determine whether a given product is genuine. Using a 2D matrix code and a special Amazon smart phone application, consumers can scan the label to access more information about a product and verify its origin. This is designed to provide an additional authentication process to curtail the sales of counterfeit and knock-off products such as designer handbags or electronic devices. It is a proprietary solution designed to help consumers make informed decisions.

The Reverse Logistics Association Standards Committee has developed an alternative solution—also aimed at consumers (as well as professionals). The RLA solution is also primarily4 based on the 2D matrix codes, though we recommend QR codes which are based on an Open Standard invented by Denso-Wave in 1994. Called Standardized QR Labels (SQRL Codes) this ANSI standard approach is a data dictionary of tags that can be combined to allow the optimum amount of data with multiple fields in limited label space. Current technology allows up to 4,000 characters of data to be encoded on a single label with multiple URL’s or fields. SQRL codes can also be read without Internet access.

Many of the fields pertain to information that would help consumers and retail service desks determine that a product is genuine. For example, one of the recommended fields is U14B which is titled Counterfeit Detection. In it, manufacturers can include a description of design elements that would distinguish a legitimate product from a knock-off or counterfeit. The manufacturer can also include another field, M049, which lists components that must be returned such as cords or CD ROMS. Another field that is available, M048, lists items in the manufacturers Top Assembly Form: are all of the parts there? Or F06, Ingredients: Does this product contain anything to which I am allergic?

To thwart the more sophisticated professions, SQRL codes also support encrypted codes. Returned products can be scanned by professional readers to synchronize serial numbers. Denso Wave has developed special systems that allow for encrypted fields to be invisible: they cannot be replicated.



SQRL codes are an open standard (ANSI MH10.8.2.12N) Currently over 200 field tag names have been defined. More are added as they are proposed to the committee. Manufacturers select which fields they desire and compose the labels which in the SQRL schema are placed on collateral materials, shipping containers, product packaging and directly on products. Each label contains relevant information to various aspects of the product life cycle. Although the labels require readers that will properly format the label contents, they will evolve as SQRL codes catch on. One of the companies on our committee is working on such a product now. There will be others.

SQRL codes are ISO 15434 complaint. They can be read by most smart phones as well as most industrial scanners. Fraud detection is important, however, there are many additional applications. One label does it all since there is plenty of space to include numerous fields on a single QR code symbol. Other uses include: single scan swiping and automated product registration. Automated warranty management, pre and post-sales support applications are designed to improve the customer experience. Information about recycling and product recalls will also help improve consumer promotional scores.

Our Standards Committee is soliciting pilot projects. If your company would like to pioneer in this exciting new labeling standard, please contact us. Please join our monthly committee meeting the second Friday of each month at 11:00 a.m. Pacific Coast time, or contact us at sqrl@rla.org. For more information go to www.rla.org/sqrl

references
1 The 2016 National Retail Security Survey , National Retail Federation
2 The Recon Group, 2013
3 Published by MarketsandMarkets™, Nov 2017
4 SQRL code protocols can also be ported to RFID, Barcodes or other symbologies.
RLM

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