E-Commerce Fraud Prevention: Everything You Need to Know to Protect Your Business

By 2040, estimates project that consumers will make 95% of their purchases online, but the convenience and accessibility online shopping offers is encouraging fraudsters like never before, leading to an increase in fraudulent activities.

When businesses don’t stop e-commerce fraud, they’re putting revenue on the line and potentially hurting their brand reputation. It’s crucial for online stores to use strong fraud prevention methods to protect both themselves and their customers. To stay ahead in a competitive market, top companies need to provide reliable, scalable, digital-first shopping experiences while keeping fraud at bay.

In this blog, we discuss the types of e-commerce (also known as digital commerce) fraud prevention businesses need to know about, red flags to watch out for, and tactics for preventing e-commerce fraud.

What is E-Commerce Fraud?

E-commerce fraud affects a wide range of businesses across various industries. Any company involved in online transactions is potentially at risk, but some sectors are more vulnerable than others. The types of businesses commonly affected include online retailers and commerce marketplaces.

Organizations must know the common signs of e-commerce fraud and put safeguards in place to protect their business, especially as both the e-commerce industry and e-commerce fraud continue to grow. Fraud in global e-commerce is expected to reach $343 billion between 2023 and 2027, and is already at around $48 billion annually. Account takeover (ATO) accounted for 29% of e-commerce fraud in 2023 while chargeback fraud amounted to 34%. Most telling of all, 90% of US companies have been the target of cyber crime.

What are the Types of E-Commerce Fraud?

E-commerce fraud can either be committed directly by a legitimate customer or by a third-party using stolen credit card information or account credentials. Here are some of the most common examples of e-commerce fraud.

• Card not present (CNP) fraud: This type of fraud occurs when a fraudster uses stolen credit card information to make purchases online, where the physical card is not present.
• Chargeback fraud: Chargebacks are when a customer disputes a fraudulent charge with their credit card company, leading to a chargeback for the merchant.
• First-party fraud: Also known as friendly fraud, this occurs when a legitimate customer disputes a legitimate transaction to get their money back.
• Return fraud: This involves customers returning products they have used or damaged, claiming they are defective or unwanted, in order to obtain refunds or replacements.
• Account takeover (ATO): In an ATO attack, fraudsters gain unauthorized access to a customer’s account and obtain other sensitive information about the customer or make fraudulent transactions using their saved payment information.
• Phishing and spoofing: Fraudsters send deceptive emails or create fake websites that mimic legitimate businesses to trick customers into providing their personal and financial information.
• Account creation fraud: Fraudsters create multiple fake accounts to exploit introductory offers, discounts, or referral programs, leading to financial losses for the merchant.
• Card testing: Fraudsters test cards by making small purchases with multiple stolen credit cards to test the validity of the cards.
• Card hopping: Fraudsters card hop by making larger purchases with stolen credit cards that have been validated through card testing.

How to Detect E-Commerce Fraud

The first step toward preventing e-commerce fraud is detecting unusual behavior. Here are some of the red flags and warning signs for e-commerce fraud:

• Higher order volumes: A sudden surge in order volumes, especially for high-value products, may be a sign of fraudulent activity.
• Low-value orders: Fraudsters may place multiple small orders to test stolen credit card information before making larger purchases.
• Different credit cards: If multiple orders are placed using different credit cards but under the same customer account, it could indicate fraudulent behavior.
• Repeated declined transactions: Frequent declined transactions from the same customer could suggest that stolen credit card details are being used to confirm user information.
• Unusual IP locations: Orders originating from IP addresses located in different countries or known high-risk regions may raise suspicions.
• Different billing and shipping addresses: Inconsistent billing and shipping addresses, particularly when combined with other red flags, may indicate fraudulent activity.
• PO box shipping addresses: Orders using PO box addresses as the shipping destination may be an attempt to avoid traceability and detection.

Strategies and Best Practices for E-Commerce Fraud Prevention

There are many strategies and tactics for preventing e-commerce fraud, including technical controls and best practices. Some of the most effective tactics for preventing e-commerce fraud include:

• Implementing machine learning tools to automate fraud detection: Machine learning algorithms can analyze patterns and detect anomalies in customer behavior to identify potential fraud.
• Linking fraud signals from a data network that’s larger than your own: Collaborate with fraud prevention networks or organizations that share information on fraudulent activities to leverage a broader range of data for fraud detection.
• Implementing risk-based or step-up authentication: Utilize adaptive authentication techniques that prompt additional verification measures, such as two-factor authentication, for higher-risk transactions.
• Implementing card security code requirements: Require customers to enter the CVV or CVC code on the back of their credit cards to verify their ownership during transactions.
• Investing in Address Verification Services (AVS): AVS compares the billing address provided by the customer with the address on file with the credit card issuer to identify potential discrepancies.
• Partnering with a reliable third-party payment processor: Choose a reputable payment processor that offers robust fraud prevention measures and has a proven track record in security.
• Following PCI standards: Ensure your business is compliant with Payment Card Industry Data Security Standard (PCI DSS) requirements to protect cardholder data and prevent security breaches.
• Training customer service representatives on fraud: Educate your customer service team on common fraud indicators and techniques to enhance their ability to identify and report suspicious activities.
• Keeping fraud prevention software updated: Regularly update your fraud prevention tools and software to stay ahead of evolving fraud tactics and leverage the latest security measures.
• Avoiding collecting too much sensitive customer data: Minimize the collection and storage of sensitive customer data, such as credit card information, to reduce the risk of data breaches.

E-commerce fraud prevention is a significant challenge for online businesses, but by implementing effective fraud prevention measures, you can protect your business and provide a secure shopping experience for your customers.

Be vigilant for red flags indicating fraudulent activities, leverage advanced technologies like machine learning for fraud detection, and follow best practices such as secure communication protocols and compliant data handling. By staying proactive and informed, you can minimize the risk of e-commerce fraud and safeguard your business’s success.

How Sift Helps E-Commerce Leaders Transform Trust into Revenue

Trust between an e-commerce business and its customers translates directly into revenue and growth. Sift’s AI-powered risk decisioning platform proactively blocks e-commerce fraud at every point in the user journey, building customer loyalty through deep, identity-level insights and better digital experiences.

With Sift, e-commerce companies can: 

• Create better consumer experiences: Give trusted customers an ideal experience every time they engage with dynamic friction solutions like one-click checkout and faster logins that bypass multi-factor authentication (MFA). Sift’s deep insights automatically deliver the right levels of friction at every point in the user journey, from account creation to checkout.
• Protect transactions: Sift’s Global Data Network of 1T annual events protects $325B annually across 700+ leading brands. Our AI-powered platform blocks emerging threats before they impact revenue, and builds trusted, seamless experiences for customers that improve loyalty and lifetime value.
• Adapt to changes: E-commerce providers grow when they’re able to scale their business while maintaining trust. Ensure your fraud team can confidently handle periods of high traffic with ease, accepting trusted users and adjusting to risk in real time.

Sift Fraud Prevention Case Studies

Here are some examples of how Sift has helped businesses proactively prevent fraud.

Harry’s decreased chargebacks by 85%

Harry’s is a care brand with operations in North America and the UK that wanted to find a scalable fraud prevention solution shortly after launching. They saw fraud in the form of promotion and payment abuse, account abuse, and friendly fraud, with resellers making fake accounts to purchase large quantities of Harry’s blade and resell them at a profit. Some customers would “game the system” by cancelling their subscription after receiving the product.

After some research, Harry’s decided to use Sift, and found that integration was quick and easy. They used Sift Console to pull metrics like Sift Scores, network visualizations, and social media data to identify suspicious users and determine who to block or review. In the first two months after integrating Sift, Harry’s saw an 85% reduction in chargebacks. The effectiveness is such that even as Harry’s has grown and expanded, their full-time fraud department is just one person.

Paula’s Choice increased ROI by 6x

Paula’s choice in many ways helped pioneer the cruelty-free skincare industry, offering safe and effective products for almost three decades. Operating internationally, they encountered e-commerce fraud as many online businesses do, mostly resulting in a large number of chargebacks and reselling issues. Initially, they tried their payment processor’s revenue protection program, but the limitations of the rules-based product proved limiting, and fraud once again grew. 

Switching to Sift and using their machine-learning models over their payment processors rules-based models proved effective for Paula’s Choice. The data and automation offered would have been hard to reproduce manually, and Sift Workflows was able to adapt to new fraud trends. The result was an immediate 0.2% decrease in chargeback rates, and a 1% decrease in block rates as Sift more accurately identified fraudulent orders. Three days after implementation, Paula’s Choice saw over $100,000 saved from fraudulent orders and in the long term a 6x increase in ROI.

Poshmark reduced spam and secured its online community

Poshmark hosts a vibrant online community of over 4 million fashion enthusiasts and gives them a place to discuss, sell, and buy clothing. Their expansive catalog features more 75 million items and 5,000 brands accessible to that community, and they realized that establishing trust was key to their success. They turned to Sift and have had massive success. 

Within a week of integration, Poshmark was able to train Sift’s learning algorithms on live data to stop fraudulent activity and adapt to new trends. Through these automated workflows, Poshmark has reduced between 60 and 70% of spam content on their platform, providing a safer, easier place for their community to interact.

Learn more about how e-commerce leaders grow fearlessly with Sift.

5 Future Trends in E-Commerce Fraud Prevention

It’s clear that e-commerce is not only here to stay, but will largely replace conventional shopping, as nearly 3 billion people shop online. Because of this trending change, e-commerce fraud will continue to evolve, so what are some of the e-commerce fraud prevention trends that we can look forward to?

• More AI-powered, real-time fraud detection: This trend is already emerging as AI and machine learning tools are getting better at detecting suspicious behaviors quickly and efficiently. The replacement of rules-based systems by AI-backed solutions will continue to learn and adapt as new fraud techniques become available. 
• Preferred payment methods: Merchants will continue to encourage their customers to use preferred payment methods through promotions and incentives. Minimizing both fraud risks and processing costs, preferred payment methods are already encouraged by 90% of merchants according to the 2025 Global eCommerce Payments and Fraud Report from the Merchant Risk Council (MRC). 
• Increasing reliance on Data and Tech: Merchants are screening fewer orders manually, instead relying on digital screening methods that put the overall declined transaction rate at around 20% according to the MRC. The same report shows that digital monitoring mostly occurs at the purchase stage and refund or dispute stage, with digital refund and dispute monitoring increasing by 12% from 2024. 
• First-Party Misuse Slows, Refund and Policy Abuse Rises: While more than half of merchants report increasing rates of first-party misuse (FPM), all saw significantly fewer major spikes. Refund and policy abuse—according to the MRC’s 2025 report—is on the rise, with one quarter of merchants surveyed saying they had seen an increase of 50% or more in the last year. The main driver is customers falsely claiming they never received goods or services. 
• Contextual and risk-based authentication: As machine learning improves, algorithms can start to recognize patterns based on a user’s behavior, device use, and relative risk level. Using this information, payment services and merchants can keep low-risk transactions speedy and efficient while applying extra scrutiny to high-risk ones.

Frequently Asked Questions