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Founded Year



Series E | Alive

Total Raised




Last Raised

$205M | 2 yrs ago



About Signifyd

Signifyd operates as an online commerce protection platform. It combines machine learning with human work to eliminate online payment fraud for e-commerce companies. The company leverages big data, machine learning, and domain expertise to provide a financial guarantee against fraud on approved orders. The company was founded in 2011 and is based in San Jose, California.

Headquarters Location

99 Almaden Boulevard 4th floor

San Jose, California, 95113,

United States


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Signifyd's Product Videos

ESPs containing Signifyd

The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.

Enterprise Tech / Information Security

The fraud detection & prevention market offers a range of technology solutions to help businesses combat fraudulent activity across digital and physical channels. These solutions provide real-time analysis of potential customer interactions, identity verification, and authentication, as well as comprehensive fraud detection and prevention capabilities. The market is driven by the growth of e-comme…

Signifyd named as Leader among 15 other companies, including Featurespace, Alloy, and Mimiro.

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Research containing Signifyd

Get data-driven expert analysis from the CB Insights Intelligence Unit.

CB Insights Intelligence Analysts have mentioned Signifyd in 6 CB Insights research briefs, most recently on Feb 27, 2023.

Expert Collections containing Signifyd

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

Signifyd is included in 12 Expert Collections, including E-Commerce.



10,643 items

Companies that sell goods online (B2C), or enable the selling of goods online via tech solutions (B2B).


Unicorns- Billion Dollar Startups

1,221 items



1,563 items

Technology that addresses regulatory challenges and facilitates the delivery of compliance requirements. Regulatory technology helps companies and regulators address challenges ranging from compliance (e.g. AML/KYC) automation and improved risk management.


Fintech 250

997 items

250 of the most promising private companies applying a mix of software and technology to transform the financial services industry.



2,779 items

Companies in this collection provide technology that enables consumers and businesses to pay, collect, automate, and settle transfers of currency, both online and at the physical point-of-sale.


Tech IPO Pipeline

568 items

Latest Signifyd News

The Impact of AI-Based Applications on E-Commerce

Sep 14, 2023

AI is becoming an integral part of our lives, and we are using its advantages in all areas, including trade. Let’s look at how AI-powered applications are impacting the development of e-commerce. Under the influence of today’s digital world, the rapidly evolving realm of e-commerce has undergone a major facelift. The recent rise of AI has impacted not only people but businesses as well. Thanks to the latest AI-driven functionalities and products in e-commerce, you’ll surely have noticed how your favorite website has changed for the better. Chatbots, arguably the most annoying part of any e-commerce site, have gone from giving out unhelpful and scripted responses to real-time, informative, and dynamic ones. The search function across various websites has improved, almost as if it has finally understood what you mean when you write a query, not just what you type. The advancement of AI doesn’t just bring improved UX to the table, it has the potential to change the industry as a whole. Plenty of companies, Gearheart in particular, are already at the forefront of harnessing AI’s power to reshape the e-commerce experience. Let’s discuss the impact of AI on e-commerce, and how businesses use it to create apps that revamp the various aspects of e-commerce. Image by Philip Oroni, Unsplash (@philipsfuture) Apps for Personalization and Recommendations AI-driven apps in e-commerce have a variety of uses – one of them is creating custom product recommendations tailored for each user. These have become incredibly popular over the past few years, with companies like YouTube, Instagram, and Facebook using them in their content delivery systems (Instagram Reels, Meta videos, and so on) to keep users on their feeds as long as possible. These algorithms account for every factor that comes into play when a user opens the app. Even things that’ll seem trivial at first, such as when you hover too long over a product, or skip past a video ad after watching it for a while, get noted. It continually studies you and your preferences and assumes your intent on each action you perform. By this constant analysis, algorithms can gain an accurate understanding of what a person likes and, subsequently, recommend it to them. You’ll surely have noticed how the tailored content is in the typical “Recommended for you” and “Users also bought” sections on various websites. Customers don’t want their time to be wasted with frivolous and unhelpful recommendations. If they feel that their preferences are understood and that their time is valued, they’re more inclined to come back to an app. Any business that claims to care for its customers and their time will have a better chance to succeed in the market. Common Ways to Use Let’s dive further into how AI-driven apps in e-commerce work. Spotify and YouTube, for example, utilize AI algorithms to analyze the user’s search history and their preferences for the content they view, such as likes, dislikes, comments, saves, shares, and so on. All these interactions can tell you what a user feels about a particular type of content, which can help the AI decide whether to drive them away from that genre or toward it. In the case of Netflix, they’ve used collaborative filtering, in which they group like-minded viewers in one category and suggest similar content to all of them together. Spotify, on the other hand, has multiple models that can process audio features, user playlists, and listening habits to create and suggest music based on the user’s current mood and favorite genre. Meanwhile, YouTube uses a simpler recommendation system that takes the user’s history and contextual data and matches it with the user’s preferences and current interests. The ability to learn repeatedly from the user is what makes these models, and in turn these apps, a success. Zalando’s Size Advisor was created to target a specific problem everyone faces online: the size issue. Whether or not an article of clothing will fit is the biggest problem anyone faces when they visit any e-commerce website. Luckily, Zalando’s virtual fitting room utilizes the best AI algorithms that provide accurate size recommendations to customers. Once they’ve filled out their height and weight, the system analyzes data from similar builds and suggests the best clothing items for them. The system also learns based on user reviews, therefore minimizing the need for returns or exchanges. Apps for Chatbots and Customer Support AI-powered chatbots have ushered in a new age of customer support, being capable of providing 24/7 support and tailored solutions to frustrated customers who need help with their problems. One of their greatest benefits is that there is no downtime between responses and no timezone issue. As long as the bot is being hosted on a server, it’ll always stay active and work as it’s programmed to. It allows businesses to offer round-the-clock support to all of their customers with accuracy and efficiency. Chatbots can respond instantly and retrieve product-based information the customer asks for, greatly improving the user experience. These bots can also be used to transition into actual human support for complex issues, but they can often resolve most problems immediately, saving a lot of time for both employees and customers. Apps for Everyday Use There are some noteworthy applications for this specific purpose if you’re considering a chatbot-based support system for your app. For example, Zendesk Chat uses AI to facilitate real-time interactions between both customers and businesses. The platform acts as an information-gathering intermediary and the models themselves learn from interactions made by both customers and companies. Tidio’s AI-powered chatbot delivers near-instant responses and gathers user data to provide a personalized experience. It starts with predefined responses but slowly learns to become more accurate with its answers and can eventually grow to predict user intent and offer specific assistance for each user. Apps for Fraud Detection and Security AI’s also seen innovation in the field of cybersecurity. The algorithms used today are incredibly thorough and accurate, able to immediately detect unusual patterns and behavior indicating fraud. Even if you’re not aware of the dangers in the digital world, you can make use of AI-driven security for your own benefit. It’s become easier than ever to implement safe protocols and build an app that can safeguard customers against malicious users and their activity. Most Popular Examples One of the most popular examples of AI-driven fraud detection you’ll hear about is Forter. The tech Forter has in place allows them to be able to tell merchants about the risk of each transaction made on their platform. Forter utilizes behavioral data analysis, where it analyzes users in real time to judge a customer’s trustworthiness without having to block a sale. Signifyd is another notable example of a great fraud detection tool. What makes it so popular is its ease of use with pre-existing e-commerce plugins, such as Shopify. On a more related note, it uses historical user data to contextualize orders on your platform. What that means is that Signifyd is able to discern and, in a sense, understand the intent behind each transaction. With this extensive information, Signifyd is capable of accurately accepting or rejecting decisions in real time. Future Outlook To conclude, the future of online businesses lies in the hands of AI-driven apps in e-commerce. Many more innovations are yet to become the norm: features like automated customer service that offers seamless real-time assistance, voice commerce that transforms customer interaction, and even supply chain optimization aren’t widely implemented yet. As algorithms continue to advance, businesses are forced to keep up. Those who embrace these trends are not only setting themselves up for long-term success but shaping the future of e-commerce as we know it.

Signifyd Frequently Asked Questions (FAQ)

  • When was Signifyd founded?

    Signifyd was founded in 2011.

  • Where is Signifyd's headquarters?

    Signifyd's headquarters is located at 99 Almaden Boulevard, San Jose.

  • What is Signifyd's latest funding round?

    Signifyd's latest funding round is Series E.

  • How much did Signifyd raise?

    Signifyd raised a total of $411.2M.

  • Who are the investors of Signifyd?

    Investors of Signifyd include FIS, Neuberger Berman, CPP Investments, Owl Rock Capital Partners, IA Ventures and 16 more.

  • Who are Signifyd's competitors?

    Competitors of Signifyd include BioCatch,,, Bolt, ClearSale, Riskified, Forter, Sift, FUGU, Kount and 13 more.

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CB Insights puts confidence and clarity into your most strategic decisions.
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  • Predict emerging trends
  • See competitors' playbooks
  • Stalk the smart money
  • Identify tomorrow's challengers
  • Spot growing industries
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Compare Signifyd to Competitors

Sift Logo

Sift provides real-time machine learning fraud prevention solutions for online businesses across the globe. Its machine-learning software automatically learns and detects fraudulent behavioral patterns and alerts businesses before they or their customers are defrauded. It provides its services in a wide range of industries such as financial technology, retail, payment service providers, and more. It was formerly known as Sift Science. The company was founded in 2011 and is based in San Francisco, California.

Forter Logo

Forter provides fraud prevention and protection solutions for e-commerce companies. It offers solutions such as fraud management, abuse prevention, identity protection, payment optimization, chargeback recovery, and more. It was founded in 2013 and is based in New York, New York.


NS8 is an eCommerce company that provides abuse, fraud, and user experience protection tools. The company uses behavioral analytics, real-time user scoring, and global monitoring to optimize and protect against threats, which give eCommerce merchants insight into their real customers.

Shield Logo

Shield is a software-as-a-service (SaaS)-based self-learning fraud prevention solution for e-commerce. It combines latest fraud detection technology with machine learning, predictive analytics, and big data that runs on an optimized risk algorithm to compute the decision for accepting or rejecting each transaction. It was formerly known as CashShield. It was founded in 2008 and is based in Singapore, Singapore.

SEON Technologies

SEON Technologies offers end-to-end fraud prevention and detection tools for businesses. Its artificial intelligence (AI)-powered system uses data enrichment and machine learning to reduce revenue loss and manual review time. The company was founded in 2017 and is based in London, United Kingdom.

Vesta Logo

Vesta offers a transaction guarantee platform for online purchases and electronic payment solutions. It is engaged in fraud protection and e-commerce payment solutions that assist online merchants, telcos, payment processors and acquirers optimize revenue by helping eliminate the fear of fraud through a variety of channels, including the internet, mobile phones, retail point of sale, and mobile commerce applications. Vesta was formerly known as Carrier Services. The company was founded in 1995 and is based in Lake Oswego, Oregon.

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