1. Refund and Policy Abuse Has Become the Top Threat

For the first time, refund and policy abuse has overtaken payment fraud as the leading concern named by merchants in the MRC’s 2026 survey. This includes practices like wardrobing, where a customer purchases an item, uses it, and returns it as if new; claiming an item never arrived when it did; and requesting refunds while keeping the merchandise.

This shift reflects two things happening at once. First, payment-side fraud detection has genuinely improved, closing off some of the easier avenues criminals used to rely on. Second, refund and return policies at many merchants have become more generous over the past several years, in part to compete on customer experience, which has created more surface area for abuse. The response is not to make policies harshly restrictive again, since that risks alienating the large majority of customers who use returns honestly. Instead, it means building the same kind of pattern-based tracking used for payment fraud, applied to return behavior: flagging accounts with unusually high return rates, wardrobing patterns, or repeated “item not received” claims for closer review, without slowing down the return process for everyone else.

2. First-Party Fraud Continues Its Sharp Rise

First-party fraud, where the actual accountholder disputes a legitimate charge, jumped from 15 percent of reported fraud in 2023 to 36 percent in 2024, and the trend has continued into 2026. This lines up closely with the growth in friendly fraud disputes covered elsewhere on this site, but it is worth flagging here as part of the broader pattern: an increasing share of ecommerce loss is coming from the merchant’s own customer base rather than from external criminal actors. Fraud strategies built entirely around detecting outside attackers will increasingly miss where the loss is actually concentrated.

3. Generative AI Is Lowering the Barrier to Entry for Fraud

Generative AI tools have made it dramatically easier for fraud rings to operate at scale and with more convincing cover. Criminals can now spin up an entire fake storefront, complete with a polished brand identity, product photography, and marketing copy, in a matter of hours, collect payment from unsuspecting shoppers, and disappear before any meaningful complaint volume builds. This is a different threat than transaction-level card fraud; it targets consumer trust in the broader ecommerce ecosystem, which indirectly affects legitimate merchants who now compete against a marketplace where fake storefronts are more common and more convincing than in years past.

Synthetic identity fraud, where AI is used to blend real and fabricated personal data into a plausible but fictitious identity, now accounts for roughly 11 percent of all fraud cases. These synthetic identities are built specifically to pass basic verification checks, making them harder to catch with traditional identity verification alone.

4. Agentic Traffic Is a Genuinely New Category of Risk

Perhaps the most novel trend for 2026 is the rise of agentic AI traffic, automated systems capable of independently executing tasks like logging into accounts, filling out checkout forms, and completing payments. This kind of traffic surged 450 percent in 2025, and it creates an unusual challenge: distinguishing between a legitimate AI shopping assistant acting on behalf of a real customer and an automated fraud tool probing for vulnerabilities.

Traditional bot detection was built to catch obviously non-human behavior, like implausibly fast form completion or repetitive scripted patterns. Agentic AI tools can behave in ways that look far more human, since they are often built on top of genuine browsing and interaction models. Merchants will need to move beyond simple “is this a bot” detection toward more nuanced intent and pattern analysis that can distinguish helpful automation from harmful automation, a distinction that did not need to exist just a few years ago.

5. AI Is Also Making Fraud Prevention Meaningfully Better

It is not all bad news. The same AI advances fueling new fraud tactics are also driving real gains in detection accuracy. Modern AI-based fraud detection systems now operate at 90 to 97 percent accuracy, compared to 60 to 75 percent for legacy rule-based systems, while false-positive rates have dropped from the 10 to 20 percent range down to under 2 percent in leading implementations. In one notable example, Mastercard’s generative AI work on compromised card detection doubled detection rates while cutting false declines by up to 200 percent.

This matters directly for the false decline problem discussed elsewhere on this site. Better AI-driven detection does not just catch more fraud; it also reduces the collateral damage of blocking legitimate customers, addressing both sides of the fraud prevention equation at once rather than trading one for the other.

6. Behavioral Biometrics Are Becoming Mainstream

As account takeover and bot traffic both grow more sophisticated, more merchants are turning to behavioral signals that are difficult to fake: keystroke dynamics, touch pressure on mobile devices, scroll velocity, and mouse movement patterns. These signals help distinguish a genuine human shopper from an automated script or a fraudster using stolen credentials, even when surface-level details like the device or IP address look unremarkable. Expect these behavioral layers to become a standard component of fraud stacks rather than a specialized add-on over the course of 2026.

7. Layered, Multi-Signal Defense Is Replacing Single-Point Rules

Across every trend above, one theme repeats: no single signal or rule is sufficient anymore. AVS checks alone miss account takeover. Bot detection alone misses agentic traffic built on legitimate browsing patterns. Payment fraud rules alone miss the growing wave of refund and policy abuse. The merchants managing risk well in 2026 are the ones building layered systems that combine authentication, behavioral analytics, transaction monitoring, and return pattern tracking into a single coordinated view of risk, rather than maintaining a patchwork of disconnected point solutions added reactively over time.

What This Means for Ecommerce Merchants in 2026

None of these trends call for panic or a wholesale rebuild of existing fraud systems overnight. They call for a deliberate, prioritized update to where fraud prevention attention is directed. For most merchants, that means:

• Extending fraud monitoring beyond payments and into the returns and refunds process, where the MRC now identifies the greatest concentration of risk
• Building or acquiring detection capable of distinguishing helpful AI-driven shopping traffic from harmful automated fraud attempts
• Evaluating whether current fraud tools rely on modern AI-driven scoring or legacy binary rules, given the meaningful accuracy gap between the two
• Continuing to invest in account-level protections against takeover, since first-party and account-based fraud are both growing faster than traditional card-present fraud
• Reviewing decline data regularly to ensure any new detection layer added for one of these emerging threats does not introduce new false declines elsewhere

A Note on Cross-Border and Marketplace Exposure

Merchants selling across multiple countries or through third-party marketplaces face an added layer of complexity in 2026, since refund abuse, synthetic identity fraud, and agentic traffic patterns often vary significantly by region and platform. A rule set tuned for a merchant’s primary domestic market may perform very differently against international order volume, where local payment methods, shipping norms, and dispute processes differ. Merchants expanding internationally this year should budget time to validate that existing fraud thresholds still hold up in each new market, rather than assuming a single global rule set will perform consistently everywhere.

Looking Ahead: Building a 2026-Ready Fraud Stack

Merchants planning their fraud budget and roadmap for the rest of 2026 should treat this year as a genuine inflection point rather than an incremental continuation of prior years. The combination of refund abuse overtaking payment fraud, first-party fraud nearly doubling its share of losses in two years, and the emergence of agentic AI traffic means that a fraud stack built even two years ago is very likely misaligned with where risk actually sits today. A practical audit starts by mapping current tools against each of the seven trends above and identifying which ones have no real coverage at all, since those gaps, not the areas already well defended, are where losses are most likely to grow over the remainder of the year.

FAQ: Ecommerce Fraud Trends in 2026

Q: Is payment fraud no longer a major concern for ecommerce merchants?

A: Payment fraud remains a significant concern, but it has been overtaken by refund and policy abuse as the top-named threat in the MRC’s 2026 report. This reflects a shift in where fraud losses are concentrated, not a disappearance of payment-related risk.

Q: What is agentic traffic and why does it matter for fraud prevention?

A: Agentic traffic refers to automated AI systems capable of independently completing tasks like logins and payments, distinct from simple scripted bots. It matters because it surged 450 percent in 2025 and requires more nuanced detection than traditional bot-blocking rules, since it can closely resemble legitimate human browsing behavior.

Q: How is generative AI being used by fraudsters?

A: Generative AI is being used to create convincing fake storefronts quickly, generate synthetic identities that blend real and fabricated data, and produce more persuasive phishing content aimed at harvesting login credentials for account takeover attacks.

Q: Does better AI-driven fraud detection mean higher false decline rates?

A: The opposite tends to be true. Leading AI-based fraud detection systems have driven false-positive rates down significantly compared to legacy rule-based systems, improving both fraud catch rates and the customer experience for legitimate shoppers.

Q: How should a merchant prioritize these trends with limited resources?

A: Start by reviewing where losses are actually concentrated using your own data, since the industry-wide shift toward refund abuse and first-party fraud will not affect every merchant equally. From there, prioritize the layer of defense with the clearest gap, whether that is account protection, return abuse tracking, or upgrading from legacy rule-based detection.