E-commerce fraud, encompassing illicit activities that exploit online retail systems, poses a growing threat to businesses and consumers in 2025. As e-commerce continues to dominate global retail, driven by seamless digital platforms and innovative payment solutions, fraudsters have adapted, employing advanced technologies to perpetrate scams. Addressing this issue is critical to preserving consumer trust, protecting financial stability, and ensuring compliance with evolving regulations. In 2025, the e-commerce ecosystem thrives on AI-driven personalization, global supply chains, and emerging payment methods, but these advancements also create new vulnerabilities for fraud.

The State of E-commerce Fraud in 2025

Market Context

With consumers embracing omnichannel shopping and digital wallets becoming mainstream, the digital attack surface has expanded. Every touchpoint—login, checkout, loyalty programs, and even customer service is now a potential vector for fraud.

Additionally, the return of Trump-era tariffs in 2025 has introduced new volatility into global supply chains. Increased import duties on consumer electronics, fashion, and other high-demand goods have led to price surges. Fraudsters exploit this economic tension by targeting marketplaces with counterfeit goods, fake promotions, and phishing scams promising tariff-free deals.

Fraud Statistics and Trends

According to recent forecasts, global e-commerce fraud losses are expected to exceed $80 billion in 2025. This marks a sharp increase from previous years, with industries like fashion, electronics, and digital goods being prime targets. Fraudsters are not only attacking more frequently but are also refining their methods using automation and artificial intelligence.

Common Types of E-commerce Fraud in 2025

Account Takeover (ATO)

Account takeover attacks have surged, increasing by 131% in recent years. Attackers use stolen credentials to access customer accounts, often through brute-force attacks, credential stuffing, or phishing. Once inside, they change personal information, reset passwords, and make unauthorized purchases. Attackers mimic legitimate user behavior, making detection difficult. Businesses face loss of customer trust and brand reputation damage. Attackers may also use compromised accounts for internal phishing or to impersonate employees, leading to further financial and operational harm.

Synthetic Identity

Synthetic identity fraud involves criminals combining real and fake information to create new identities. These identities open accounts, build credit, and make fraudulent purchases. This type of fraud often goes undetected for months, causing significant financial losses. E-commerce businesses struggle to identify synthetic identities because they appear legitimate in many systems. The impact includes increased chargebacks, regulatory scrutiny, and higher costs for e-commerce fraud prevention.

Payment & Chargebacks

Payment fraud and chargebacks directly affect the financial health of e-commerce businesses. Fraudsters use stolen payment information to make unauthorized purchases, resulting in chargebacks when customers dispute the transactions. LexisNexis' True Cost of Fraud study shows that for every dollar lost to fraud, businesses may incur up to $4.41 in total costs, including fees and labor. High chargeback ratios can lead to higher processing fees or even loss of payment processing capabilities. These issues also damage customer retention and reputation, forcing businesses to invest more in fraud prevention technologies.

Friendly Fraud

Friendly fraud occurs when customers dispute legitimate purchases, claiming they never received the product or did not authorize the transaction. This type of fraud accounts for 30% of purchase transaction fraud. Clothing, subscription goods, and electronics are the most disputed categories.

Automated Attacks

Automated attacks target e-commerce platforms using bots and scripts. The most common forms include unauthorized access sales (46.82%), data-related content leaks (41.22%), and website attacks (10.53%). Attackers use credential stuffing, phishing kits, payment skimming, and ransomware to exploit vulnerabilities. These attacks scale quickly due to dark web marketplaces trading stolen credentials and attack tools. Real-world incidents, such as breaches at major online retailers, highlight the growing threat. Automated attacks disrupt operations, compromise customer data, and increase the need for advanced e-commerce fraud prevention.

The Expanding Threat Landscape of E-commerce Fraud in 2025

E-commerce fraud continues to evolve rapidly in 2025, driven by advanced technologies and shifting market dynamics. To fully grasp this expanding threat, it’s essential to understand the tools fraudsters use, the challenges businesses face, and which sectors are most at risk.

Key Fraud Tactics and Tools in Use

Fraudsters in 2025 are leveraging advanced tools to outpace traditional detection systems.

• Sophisticated Tools Used by Fraudsters: AI and machine learning enable fraudsters to craft realistic synthetic identities and automate attacks. Bots are increasingly used for scalping, inventory hoarding, and credential stuffing, overwhelming e-commerce systems. These tools allow fraudsters to operate at scale, targeting multiple platforms simultaneously with minimal effort.
• Dark Web Marketplaces: The dark web remains a hub for fraud, with marketplaces selling stolen data, counterfeit goods, and fraud tools. In 2025, these platforms have become more accessible, offering fraudsters everything from hacked account credentials to AI-generated phishing kits, amplifying the scale and sophistication of attacks.
• Exploitation of New Payment Methods: Emerging payment methods, such as Buy Now, Pay Later (BNPL) systems, have introduced new vulnerabilities. Fraudsters exploit gaps in BNPL verification processes to make purchases they never intend to pay for. Similarly, cryptocurrency transactions, while secure in theory, are exploited due to their irreversibility, making it difficult for merchants to recover funds from fraudulent purchases.

Challenges for Businesses in 2025

Businesses face multiple challenges in mitigating fraud:

• Detection Complexity: Modern attacks are multi-vector and low-and-slow, making them difficult to detect in real time.
• User Experience Trade-offs: Stricter verification measures can harm conversion rates if not implemented thoughtfully.
• Regulatory Burdens: Companies must comply with varying regional regulations like GDPR, CCPA, and newer AI-specific laws.
• Economic Disruptions: The reintroduction of Trump tariffs has caused shifts in product pricing, sourcing, and consumer behavior. As companies seek new suppliers or markets to reduce costs, fraudsters exploit transitional vulnerabilities—such as unknown vendors, weak inventory validation, or fake customs declarations.
• Data Fragmentation: Data spread across platforms, partners, and channels hinders cohesive fraud detection strategies.

Businesses Most Vulnerable to E-commerce Fraud

While any business with an online presence can fall victim to e-commerce fraud, certain sectors face heightened risks due to their operational models, customer interactions, or transaction volumes.

• High-Value Goods Retail: Businesses selling luxury items, electronics, or collectibles are prime targets due to the high resale value of their products. Fraudsters often use stolen payment details or fake identities to purchase these goods, reselling them for profit on secondary markets or the dark web.
• Cross-Border E-commerce Platforms: Companies operating internationally face unique challenges, as fraudsters exploit inconsistencies in payment verification across jurisdictions. The complexity of cross-border transactions, coupled with varying regulatory standards, makes these platforms vulnerable to fraudulent chargebacks and identity theft.
• Digital Marketplace Aggregators: Platforms that connect third-party sellers with buyers, such as those hosting artisanal goods or freelance services, are susceptible to fraud involving fake seller accounts, counterfeit products, or manipulated reviews. These marketplaces must monitor both buyers and sellers to prevent scams.
• Crowdfunding and Pre-Order Platforms: Businesses that collect funds for products or services before delivery, such as crowdfunding sites or pre-order-based retailers, are at risk of fraudulent contributions or fake campaigns. Fraudsters may create sham projects to siphon funds or use stolen credentials to back projects without intent to pay.
• On-Demand Service Providers: Businesses offering instant services, such as food delivery, ride-sharing, or gig economy platforms, face risks from fraudulent accounts created to exploit promotional offers or discounts. These platforms often process high volumes of low-value transactions, making it harder to detect fraud in real time.
• Virtual Event and Ticketing Platforms: Online platforms selling tickets for virtual events, webinars, or live streams are vulnerable to fraudsters using stolen payment methods or creating fake accounts to resell access codes. The time-sensitive nature of these transactions complicates fraud detection efforts.

This list is not exhaustive, as the expansion of digital commerce into new industries continues to broaden the scope of potential fraud targets.

E-commerce Fraud Protection Strategies in 2025

Effectively combating e-commerce fraud demands a comprehensive strategy that safeguards business assets while preserving a smooth customer journey. The following core approaches are essential for building strong defenses against evolving fraud threats:

Strengthen Identity Verification Protocols

To prevent unauthorized account access and fraudulent transactions, implement multiple layers of identity checks tailored to transaction risk levels:

• Enhanced Authentication Methods: Utilize layered verification techniques beyond simple passwords, such as hardware tokens or biometric scans, especially for sensitive actions like account modifications or high-value purchases.
• Contextual Risk Assessment: Dynamically adjust authentication demands based on transaction context, device reputation, and user behavior, ensuring minimal friction for trusted customers while flagging suspicious activity.

Deploy Intelligent Fraud Detection Systems

Adopt sophisticated technology solutions capable of continuous learning and adaptive threat detection:

• AI-Powered Analytics: Leverage machine learning models that evolve with emerging fraud trends, enabling early detection and reducing incorrect flags that can harm user experience.
• Behavioral Monitoring: Track anomalies in user interactions such as unusual browsing paths, session durations, or rapid input sequences to identify potentially fraudulent behavior.
• Device and Network Fingerprinting: Build comprehensive profiles of devices and network environments used in transactions, aiding in recognizing repeated suspicious patterns across different accounts.

Mitigate Automated and Bot-Driven Threats

Bots pose a substantial risk by mimicking legitimate traffic and executing high-volume fraudulent actions:

• Comprehensive Bot Defense: Integrate solutions that distinguish human users from automated scripts through behavior analysis, challenge-response tests, and fingerprinting techniques.
• Secure All Access Points: Extend protection beyond front-end websites to APIs and mobile applications, closing common loopholes fraudsters exploit.
• Continuous Traffic Analysis: Maintain baseline metrics of typical traffic flows and set automated alerts to detect sudden surges or unusual patterns indicative of bot attacks.

Enhance Payment Security Infrastructure

Securing payment channels reduces exposure to fraudulent charges and financial losses:

• Address and Card Verification: Confirm billing information accuracy through AVS and require card security codes to verify physical possession.
• Next-Generation Payment Authentication: Adopt standards like 3D Secure 2.0 that enhance security without compromising checkout speed or user convenience.
• Data Tokenization: Replace sensitive payment credentials with tokens during transaction processing to minimize risk if data interception occurs.

Establish Robust Fraud Response Frameworks

Beyond technology, clear operational policies and trained personnel are vital:

• Risk-Based Order Review: Define and automate criteria for flagging orders for manual inspection, focusing on factors such as new customer profiles, mismatched addresses, or atypical purchase sizes.
• Efficient Dispute Handling: Implement structured workflows to manage chargebacks and disputes, gathering necessary evidence promptly to contest fraudulent claims effectively.
• Ongoing Staff Education: Regularly train customer service and fraud prevention teams on the latest fraud methodologies and internal protocols to ensure rapid and accurate response.

Real-World Case: CAPTCHA Bypass Leads to Payment System Attack in eCommerce

In 2024, a Magento 2 platform operator shared on Reddit their experience of a severe fraud attack that occurred shortly after integrating Braintree credit card payments. Within just a single day, over 118,000 fake transaction attempts were automatically submitted, putting the merchant’s payment system and business reputation at serious risk.

Despite having deployed a traditional CAPTCHA solution, attackers easily bypassed it using automated scripts. The CAPTCHA failed to block the flood of fraudulent activity. Ultimately, the merchant had to temporarily shut down their payment gateway to avoid further financial losses and potential service outages.

GeeTest’s Protective Advantage in Similar Scenarios

GeeTest CAPTCHA offers a more resilient and intelligent alternative to traditional CAPTCHA systems, especially in high-risk use cases such as credit card testing, fake order attacks, and API abuse.

1. Behavior-Based Verification

GeeTest uses behavioral analysis to examine subtle user actions such as mouse movement patterns, click strength, and slide speed. This makes it difficult for automation tools and bots to simulate human interactions accurately.

2. Adaptive Risk-Based Challenges

The system continuously assesses user risk in real time. Higher-risk behaviors result in stricter verification, while low-risk users can complete actions with minimal friction, maintaining a balance between security and usability.

3. Strong Resistance to Attack Tools

GeeTest effectively counters OCR, automated solvers, and click farms through dynamic obfuscation, behavioral analysis, and adaptive challenges. By randomizing visual elements, validating human-like interactions, and escalating checks for suspicious traffic, it increases attack complexity and cost, making large-scale bypasses impractical.

4. Full Coverage Across Critical Business Touchpoints

GeeTest can be integrated at all key stages where fraud commonly occurs. These include login, account registration, checkout, address updates, and coupon redemption. This comprehensive deployment helps block fraudulent behavior across the entire user flow.

Conclusion

As e-commerce accelerates into 2025, so too does the sophistication and scale of fraud. From AI-generated synthetic identities to automated bot attacks exploiting emerging payment methods, the threat landscape has grown more complex and costly. Businesses must recognize that no single solution can fully shield them—true protection demands a layered, adaptive defense strategy that spans identity verification, payment security, bot mitigation, and real-time fraud intelligence.

E-commerce businesses that prioritize proactive fraud prevention, not reactive damage control, will be best positioned to protect their customers, preserve trust, and maintain long-term growth in the face of rising cyber threats.