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Ecommerce fraud prevention · October 2026 Edition

NoFraud vs Sift

Zero of fourteen models named NoFraud first on the direct prompt; two named Sift. NoFraud was named by twelve of the fourteen models and Sift by fourteen and NoFraud carries 23 labels and Sift 44, so the shares are not directly comparable.

NoFraud

accepted challenger

Named in one category this edition.

Sift

accepted challenger

Named in three categories this edition.

First-choice share8%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate13%16%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#6A position in a field of 11; printed, not drawn.
Labels2344A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, NoFraud reading right to left. Rank and label count are printed, not drawn.Signifyd was named alongside these two in eleven of the fourteen direct answers. SEON vs NoFraud · SEON vs Sift · Eftsure vs NoFraud

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the ecommerce fraud prevention page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
NoFraudFirst choices, of fourteen modelsSift
Direct02
Paraphrase002 against Sift
Comparative02
Budget-constrained401 against NoFraud
Scale-constrained00
Negative002 against NoFraud · 5 against Sift
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, NoFraud and Sift were named in the same answer forty-five times, of the 79 answers naming NoFraud and the 161 naming Sift. In those answers Sift took the first choice four times and NoFraud twenty.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where NoFraud and Sift stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
NoFraud Sift first choice named as an alternative argued againstblank: not namedEach cell is one answer, NoFraud on the left and Sift on the right.

The direct prompt

The plain question, one answer per model, grouped by where NoFraud and Sift stood in it.

Sift first, NoFraud not the choice

2 of 14 modelsNoFraud was named in the answer but not as the choice, or not at all.
GPT-5.4 miniSift alternatives: Forter, Kount, Signifyd
Grok 4.1 FastSift alternatives: Chargeflow, Fingerprint, SEON, Signifyd, Wyllo

Neither was the first choice, one was named

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5FraudNet, Trustmi alternatives: Kount, Sift, Signifyd
Gemini 3.5 FlashSEON alternatives: Allianz Trade Pay, Sift, Signifyd, TreviPay
Perplexity SonarSEON alternatives: Kount, Sift, Signifyd
Mistral SmallSignifyd alternatives: NoFraud, Sift
DeepSeek V4 FlashSEON alternatives: Sift, Signifyd, Stripe Radar
Llama 4 MaverickWyllo alternatives: NoFraud, SEON, Sift, Signifyd, cside
GLM 4.7 FlashXSignifyd alternatives: ClearSale, Eftsure, SEON, Sift

Neither was named

5 of 14 modelsThe answer made no first choice from these two in this category.
Qwen 3.7 FlashSignifyd alternatives: Fingerprint, Kount
Kimi K2SEON alternatives: Eftsure, Kount, Trustmi
MiniMax M2.5ClearSale, SEON alternatives: Forter, Riskified
GPT-6 LunaSEON alternatives: Kount
Muse Glimmer 30BSignifyd, Wyllo, formerly NoFraud alternatives: Eftsure, SEON

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
NoFraud leads by thirty-two points.
NoFraud34%#1 of 12
Sift2%#7 of 12
The full small business standing →
Mid-marketThe figures above
NoFraud leads by four points.
NoFraud8%#5 of 11
Sift4%#6 of 11
The full mid-market standing →
Enterprise
The order flips: Sift leads at enterprise.
Sift11%#3 of 9
NoFraud0%#– of 9
The full enterprise standing →

What the models said about NoFraud

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“NoFraud is the one I'd most strongly caution against for smaller merchants, based on the 1.8/5 Trustpilot score” DeepSeek V4 Flash · negative prompt · hard negative
“Its paid starter plans begin at $250/month, so they may not suit a very limited budget.” GPT-6 Luna · budget prompt · soft negative
“Examples of platforms using this model: Riskified, Signifyd, ClearSale, NoFraud” Gemini 3.5 Flash · negative prompt · soft negative
“The best ecommerce fraud prevention platform for a company with a limited budget is NoFraud for Shopify merchants” Llama 4 Maverick · budget prompt · first choice
“For the most budget-friendly options, start with NoFraud (free Lite tier, $250/month)” Mistral Small · budget prompt · first choice
“NoFraud is widely considered the best value platform for growth-stage businesses.” Qwen 3.7 Flash · budget prompt · first choice

What the models said about Sift

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“Can be complex to configure; occasional false positives requiring manual review. Not ideal for very small teams due to setup overhead.” Grok 4.1 Fast · negative prompt · soft negative
“Unlike consumer-focused tools (like Sift or Stripe Radar), these are specifically designed for B2B payment workflows” Kimi K2 · paraphrase prompt · soft negative
“Some users note that the system can occasionally generate false positives, which may require additional review time.” Claude Haiku 4.5 · negative prompt · soft negative
“Start with Sift for most mid-market B2B ecommerce—it's consistently #1 in G2 rankings for balanced performance without overkill.” Grok 4.1 Fast · direct prompt · first choice
“Sift maintains #1 position across all fraud prevention categories in G2's Fall 2025 Reports” Muse Glimmer 30B · comparative prompt · first choice
“Sift - Top-rated on G2 for real-time detection.” Grok 4.1 Fast · comparative prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.