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How to Utilize AI to Combat Counterfeiting


How to Utilize AI to Combat Counterfeiting

Counterfeiting is a serious problem that affects many industries, particularly those that rely heavily on supply chain management. In the manufacturing industry, counterfeiting involves the production and distribution of fake products that are intended to imitate legitimate goods. One of the biggest challenges with counterfeiting is that it can be difficult to detect. Often, counterfeit products will look and feel like the real thing and may only be discovered once they have been sold and used by consumers. This not only exposes consumers to potential harm, but it can also damage the reputation of legitimate companies and manufacturers.

There are many ways in which counterfeiting can occur within the supply chain. One common method is through the use of fraudulent identification, which allows counterfeiters to obtain unauthorized access to supply chain networks. Once inside the network, they can introduce counterfeit goods into the system, often under the guise of legitimate products. Another way that counterfeiting can occur is through the manipulation of existing products. This can involve the alteration of labels, packaging, or even the product itself in order to make it appear as though it is genuine. In some cases, counterfeiters may even go so far as to replicate entire products using inferior materials or components.

In order to effectively combat counterfeiting in the supply chain and manufacturing industry, it is important to take a proactive and comprehensive approach. This might involve implementing new technologies and processes, as well as building strong relationships with key stakeholders. By doing so, manufacturers can help to protect their customers, their reputation, and their bottom line. Advancements in technology have provided another strong element in the fight against counterfeiting. There are a variety of ways that technology can be used to allow both manufacturers and consumers ensure they are buying and selling authentic products. 

One strategy that manufacturers and supply chain managers can employ, to combat counterfeiting, is to invest in robust authentication and verification technologies that can help to detect counterfeit products. This might include using unique identifiers, such as serial numbers or barcodes, that can be tracked and verified throughout the supply chain. Another important strategy is to establish strong relationships with suppliers and other partners within the supply chain. By working closely with these stakeholders, manufacturers can gain greater visibility into their operations, and can more effectively identify and address potential risks related to counterfeiting. A third approach to combating counterfeiting is to educate consumers on how to identify and avoid counterfeit products. This can be done through various channels, such as product packaging, social media campaigns, and informational websites. Finally, manufacturers can work with law enforcement agencies to investigate and prosecute those involved in the production and distribution of counterfeit products. By taking legal action against counterfeiters, manufacturers can send a clear message that counterfeiting will not be tolerated.

One key aspect of combatting counterfeiting is by utilizing technology. Many companies have been  implementing a robust tracking and tracing system in the supply chain, which can help to identify the source of counterfeit products and prevent them from entering the market. This can involve using serialization, unique identifiers, and other advanced technologies to track products from the point of origin to the end consumer. By implementing a comprehensive tracking system, manufacturers can quickly identify and isolate any counterfeit products that are detected in the supply chain, minimizing the potential impact on consumers and the company’s reputation.

Advancements in technology have also greatly impacted the ways that consumers themselves are able to authenticate products. For example, some brands now use blockchain technology to track the entire supply chain of their products, from raw materials to finished goods. This provides a secure and transparent way for consumers to verify the authenticity of their purchases. Additionally, some companies have developed smartphone apps that allow consumers to scan product codes or labels to instantly verify their authenticity. These tools make it easier than ever for consumers to make informed purchasing decisions and avoid counterfeit products. Another way that technology has impacted authentication is through the use of advanced security features, such as holograms, RFID tags, and smart labels. These features can be embedded within products or packaging to provide unique identifiers that are difficult for counterfeiters to replicate. Finally, some companies are exploring the use of digital fingerprints and other biometric data to further enhance product authentication. As technology continues to evolve, we can expect to see even more innovative solutions for authenticating products and protecting consumers from counterfeit goods.

Another important way that technology has impacted authentication is through the use of artificial intelligence and machine learning. There are several ways that AI can help consumers identify counterfeit goods. AI can help consumers identify counterfeit products by analyzing various data points and patterns to quickly and accurately distinguish authentic products from counterfeit ones. AI algorithms can also compare product codes or labels to instantly verify their authenticity. This can help brands and retailers to proactively detect and prevent the distribution of counterfeit goods. This also makes it easier for consumers to make informed purchasing decisions and avoid fake products that might be harmful or of inferior quality. 

Another method is to use machine learning algorithms to analyze product data and detect patterns that indicate counterfeit activity. This can involve analyzing product images, descriptions, and other data to identify anomalies that suggest a product is not genuine. 

Additionally, AI-powered chatbots can assist consumers in real-time by providing them with information about a product’s history, authenticity, and other key factors. AI-powered chatbots can use natural language processing (NLP) to understand and respond to consumer inquiries about a product’s authenticity. These chatbots can access a variety of data sources, including blockchain records, to provide consumers with real-time information about a product’s origin, production history, and other key details. By using AI-powered chatbots, consumers can quickly and easily get the information they need to make informed purchasing decisions, reducing their risk of buying counterfeit goods. Additionally, chatbots can provide personalized recommendations and deals based on a user’s shopping habits, further enhancing the shopping experience. By leveraging the power of AI, consumers can become more informed about the products they are buying, reducing their risk of falling victim to counterfeiters.

Overall, preventing and detecting counterfeiting requires a multifaceted approach that involves the use of technology, strong relationships with suppliers and partners, education for consumers, and collaboration with law enforcement agencies. With these strategies in place, manufacturers and supply chain managers can better safeguard their products and reputation from the negative effects of counterfeiting. Technology, specifically advancements in AI technology, has made it easier for consumers to verify the authenticity of products and has helped to protect both individuals and businesses from the harmful effects of counterfeiting. Utilizing all these resources and with increased help and sophistication of AI methods, manufacturers and consumers can be confident that they are buying genuine products and are protected from the risks associated with counterfeiting.

Bernard Klein is the president of Almont Group Inc. A dedicated father of three, he finds time to run and box while running a successful company that helps clients’ source goods overseas.


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TradeSun and Coriolis Technologies Partner for ESG Scoring of Trade Transactions

TradeSun, a technology company leveraging artificial intelligence for trade compliance and automation, and Coriolis Technologies, a leading trade data and analytics provider, have partnered to launch an integrated solution for banks to measure and verify environmental, social and governance (ESG) performance across trade transactions.

With regulators applying pressure on companies to disclose more detail on ESG performance, quantitative ways of analyzing the impact of trade finance activities are vital in achieving regional and international sustainability targets.

The combined solution enables TradeSun customers to leverage Coriolis’ ESG Tracker, an independent ratings-based platform developed with more than 50 financial institutions, to score, monitor, and verify their trade finance transactions and activities against the 17 Sustainable Development Goals (SDGs), as defined by the United Nations.

Banks can also view ratings against domestic and international regulatory frameworks such as EU Taxonomy, Sustainable Finance Disclosures Regulation, and US Sustainability Accounting Standards Board Regulations. Additionally, financial institutions can search and
explore company ratings for governance purposes, including completing a personnel check.

Customers of TradeSun will be able to use Coriolis’ ESG Tracker in tandem with other integrated data partners, enabling further insights, flexibility, and aiding financial institutions in offering financial incentives to their clients upon meeting specific ESG criteria.

About TradeSun

TradeSun is an innovator and leader in trade digitalization. Our award-winning AI-powered platform for trade finance processing and compliance empowers customers to reduce risk, costs, and fuel growth by leveraging state-of-the-art technologies. The TradeSun Platform is a one-stop solution that automates document review,
significantly reducing processing times. It offers real-time compliance, covering trade-based money laundering, dual use goods, fair price, vessel tracking and sanctions.

About Coriolis Technologies

Coriolis Technologies is a leading trade data and analytics provider, offering real-time insight into global environmental, social and governance efforts. Coriolis Technologies aggregates global trade data from unique and secure sources. Proprietary technology analyzes the data, producing vital intelligence for banks and
businesses, scoring company activity against essential industry requirements, including Sustainable Development Goals and ESG regulation.

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North America Artificial Intelligence (AI) in Retail Market Size to Surpass US $10 Billion By 2027

According to a recent study from market research firm Graphical Research, the North America Artificial Intelligence in retail market is set to grow from its current market value of more than $1 billion to over $10 billion by 2027.

North America AI in retail industry trends is anchored by a digital revolution that has taken over the retail market with a boom. It has boosted speed, efficiency, and accuracy across all branches of retail, owing in great part to advanced data and predictive analytics technologies that assist organizations in making data-driven business choices.

AI in retail has provided businesses with access to high-level data and information, which can be used to enhance retail operations and create new business prospects. In fact, it is projected that North America AI in retail market size will be $10 billion by 2027.

Amazon Web Services, Inc, BloomReach Inc., IBM Corporation, Google LLC, Intel Corporation, Microsoft Corporation, Lexalytics Inc., Nvidia Corporation, RetailNext Inc., Oracle Corporation,, Inc. and SAP SE. are among the leading companies using AI in retail supply chain across North America.

Advanced AI technologies are enabling businesses to aggregate and evaluate individual consumer data in order to conduct tailored promotions. This is why retail businesses in the region are modernizing their e-commerce systems with cutting-edge technology. Below mentioned are the recent examples of companies who have embraced AI into their retail business:

  •  J.C. Penney used AI to overhaul its e-commerce platform in September 2021. The firm is utilizing artificial intelligence (AI) technologies to change its e-commerce platform and improve the online customer experience.
  • Jesta I.S. Inc. extended its cutting-edge vision AI-based CRM platform, which provides omnichannel merchants with deep visual insight into consumer engagement, in June 2020. The visual analytics system delivers agile and actionable customer insights across all channels.
  • NielsenIQ announced a new agreement with Loop Insights Inc. in April 2021 to change the retail sector of North America through automated marketing and increased consumer interaction using real-time business analytics.

Machine learning technology assists businesses in improving the consumer experience and optimizing their supply chain strategy. By using ML’s predictive analytics approach, the retailer is provided with insights to define which marketing campaigns and social media channels are effective in relation to the company's products and services.

In order to unveil a greater ability in captivating new customers, as well as retaining them, retailers are creating a mix of machine learning with marketing efforts. It is expected that North America AI industry share from machine learning technology will grow with a 40% CAGR through 2027.

Considering the ease of shopping and hassle-free operation, e-commerce platforms have taken the centerstage during COVID-19 social distancing times. Because of this increased customer traffic on e-commerce shopping platforms, the automated merchandising application accounted for 30% of the regional market share in 2020.

Online merchants typically utilize automated merchandising software to forecast consumer’s purchase behaviors and provide them with additional shopping options. Through repeated encounters, advanced CRM and marketing systems learn a consumer’s habits and preferences to create a thorough shopper profile, which is then used to send proactive and targeted outbound marketing – tailored suggestions, rewards, or content.

Canada AI in retail industry size will account for more than $2 billion in revenue by 2027. The country’s top retail businesses are heavily concentrating on the adoption of AI and ML-based technologies and approaches that provide a smooth and integrated consumer experience. For example, Walmart Canada will invest USD 3.5 billion in digital transformation over the next five years in July 2020. The funds will be used to purchase IoT sensors, AI software, and blockchain- based transportation payments.

Author Bio

Priyanka Ravi Nair is an MBA (Finance) graduate from Pune, India. She started her journey in content writing more than 2 years ago and there has been no looking back ever since. She aims to explore several aspects in the field of content writing and is currently learning the ropes on writing articles pertaining to market research, business trends, and core industry developments.


Understanding The Opportunities for AI-Cameras and LiDAR for Smart Road Infrastructure

As the Consumer Electronics Show (CES) in January sparked a new wave of autonomous vehicles (AVs) coming to the automotive market in the next few years, much focus as of late has been on the technology of these vehicles themselves. However, the technology embedded in road infrastructure is also beginning to see more conversation between service providers and municipalities.

With advancements in artificial intelligence (AI) and 5G network connectivity, smart-road infrastructure technology offers the promise of being added to many different roads, bridges, and other transit systems across the U.S. in hopes of improving real-time traffic analytics and tackling the most challenging road safety and traffic management problems. One technology at the center of this discussion is on the present-day use of AI-enhanced cameras and tomorrow’s promise of LiDAR technology.

Artificial Intelligence Will Enhance Camera Sensing Performance

Today there are hundreds of thousands of traffic cameras deployed in the U.S. alone, and even millions more when CCTV cameras are considered. They are mainly used for road monitoring and basic traffic management applications (e.g., loop emulation). However, bringing the latest advancements of AI to these assets can immediately improve basic application performance and unlock more advanced software applications and use-cases.

AI and Machine Learning deliver superior sensing performance over traditional computer vision techniques found in legacy cameras. They enable more robust, flexible, and accurate detection, tracking and classification of all road users with algorithms that can automatically adapt to various lighting and weather conditions. In addition, they allow for predictive capabilities to better model road user movements and behaviors, and improve road safety. Agencies can immediately benefit from AI- enhanced cameras with applications such as road conflict detection and analysis, pedestrian crossing prediction and infrastructure sensing for AV deployments.

LiDAR Technology Cannot Fully Replace Cameras

LiDAR can provide complementary and sometimes overlapping value with cameras, however there are still several safety critical edge cases where LiDAR’s technology does not perform well (e.g., heavy rain and snow, granular classification), and where cameras have been proven to handle better. Moreover, today’s LiDAR technology remains expensive to deploy at scale due to its high unit price and limited field of view. As an example, it would take multiple LiDARs at a hefty investment to be deployed in a single intersection, where just one 360-degree AI-camera can be a more cost-effective solution.
For many budget-focused communities, AI-cameras remain the proven technology of choice today. Over time, as the cost of LiDAR technology moderates, communities should evaluate augmenting their infrastructure with such sensors.

Eventually, Sensor Fusion Will Drive Strong Results

When the cost of LiDAR technology eventually sees an anticipated reduction, it will be viewed as a strong and viable addition to the AI-enhanced cameras that are being installed today. Similar to autonomous vehicles, sensor fusion would be the go-to approach for smart infrastructure solutions and would allow to maximize the benefits of both technologies. See table below.

Relative Performance Comparison of Camera vs. Lidar Today

1. Assumes presence of with IR or good low-light sensor
2. Expected to improve with time

The use of a cost-effective and performing AI-powered camera today, combined with the great potential of LiDAR in the coming years could help communities and municipalities achieve a win-win scenario today and tomorrow.
At the end of the day, the goal is clear in improving overall traffic flow and diminishing vehicle crashes and fatalities, but the technology and implementation strategy has to be right in doing so. The technology monitoring our roads needs to change too, thus calling for the consideration of AI-powered cameras today with the promise of LiDAR tomorrow.

About the Author:

Dr. Georges Aoude is the co-founder of Derq, an MIT spinoff powering the future of connected and autonomous roads, making cities smarter and safer for all road users, and enabling the deployment of autonomous vehicles at scale. Derq provides cities and fleets with an award-winning and patented smart infrastructure Platform powered by AI that helps them tackle the most challenging road safety and traffic management problems.

enterprise workflow solutions including enterprise legal management and contract lifecycle management, announced today that its InvoiceAI has

Onit’s InvoiceAI Wins the Business Intelligence Group’s Award for Innovative Technology Products

Industry Acknowledgement Spotlights the Product’s Use of AI to Review Historical and Real-Time Legal Invoices and Find Savings beyond Billing Rules

Onit, Inc., a leading provider of enterprise workflow solutions including enterprise legal management and contract lifecycle management, announced today that its InvoiceAI has won a 2022 BIG Innovation Award. The annual business awards program acknowledges organizations, products and people worldwide that bring new ideas to life in innovative ways.

InvoiceAI uses artificial intelligence to help increase savings and reduce the time corporate legal departments spend on invoice review. Manual invoice review is time-intensive and often ineffective, especially for large Fortune 500 legal departments that receive a high volume of bills from outside counsel and vendors. Enterprise legal management eases this burden by applying billing rules to enforce outside counsel guidelines. Traditional billing rules without AI rely on words and context provided by in-house teams and an invoice that uses different descriptions or wording can evade them. InvoiceAI fills that gap.

InvoiceAI looks between the billing rules to identify potentially noncompliant charges. It can automatically adjust invoices to comply with guidelines or bring the discrepancy to the attention of reviewers. Because it is AI-based, it is always learning, improving and working tirelessly to reduce the volume of invoices needed for review and identify unnecessary expenses.

The BIG Innovation Award for InvoiceAI further validates the positive impact of AI for legal operations teams in large enterprises. Their AI for invoice review transforms highly repetitive and manual tasks into automated processes that optimize both legal spend and efficiency. In fact, some customers have found up to 20% in savings when using Onit’s enterprise legal management solution and InvoiceAI.

Innovation is driving the global economy across virtually all industries. Maria Jimenez, chief nominations officer of the Business Intelligence Group said they are honored to award these executives, companies and products the BIG Innovation award this year. Each has made tremendous strides at improving the lives of their community.

Learn more about InvoiceAI here or by watching this video. You can also schedule a demonstration or reach out to for more information.