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Ecommerce fraud prevention · November 2026 Edition

Signifyd vs Sift

Five of fourteen models named Signifyd first on the direct prompt; four named Sift. Both were named by all fourteen models and Signifyd carries 57 labels and Sift 50, so the shares are not directly comparable.

Signifyd

accepted challenger

Named in two categories this edition.

Sift

accepted challenger

Named in two categories this edition.

First-choice share13%9%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate23%16%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#4A position in a field of 11; printed, not drawn.
Labels5750A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Signifyd reading right to left. Rank and label count are printed, not drawn.SEON was named alongside these two in nine of the fourteen direct answers. Stripe Radar vs Signifyd · Stripe Radar vs Sift · Signifyd vs SEON

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.
SignifydFirst choices, of fourteen modelsSift
Direct541 against Signifyd
Paraphrase111 against Signifyd
Comparative50
Budget-constrained004 against Signifyd · 2 against Sift
Scale-constrained10
Negative007 against Signifyd · 6 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 November 2026 Edition, Signifyd and Sift were named in the same answer 133 times, of the 216 answers naming Signifyd and the 180 naming Sift. In those answers Sift took the first choice twelve times and Signifyd twenty-four.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Signifyd and Sift stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
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
Signifyd Sift first choice named as an alternative argued againstblank: not namedEach cell is one answer, Signifyd on the left and Sift on the right.

The direct prompt

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

Signifyd first, Sift an alternative

5 of 14 modelsSift was named in the answer but not as the choice, or not at all.
Perplexity SonarSignifyd alternatives: ClearSale, SEON, Sift
Mistral SmallClearSale, Signifyd alternatives: Stripe Radar, Sumsub
Llama 4 MaverickSignifyd
Kimi K2Signifyd alternatives: SEON, Sift, Wyllo
GPT-6 LunaSignifyd alternatives: Kount, Sift, Trustmi

Sift first, Signifyd an alternative

4 of 14 modelsSignifyd was named in the answer but not as the choice, or not at all.
GPT-5.4 miniSift alternatives: Forter, Riskified, Signifyd
Gemini 3.5 FlashSift alternatives: Kount, SEON, Trustmi AI
Qwen 3.7 FlashSift alternatives: LexisNexis Intelligent Investigator, Ping Identity, Signifyd, Wyllo
MiniMax M2.5ClearSale, SEON, Sift alternatives: Kount

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Trustpair alternatives: Riskified, SEON, Signifyd
Grok 4.20SEON alternatives: ClearSale, Sift, Signifyd, Stripe Radar
DeepSeek V4 FlashSEON alternatives: Sift, Signifyd
GLM 4.7 FlashXStripe Radar alternatives: SEON, Signifyd
Muse Glimmer 30BClearSale alternatives: SEON, Sift, Signifyd, Trustpair

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
Signifyd leads by twelve points.
Signifyd12%#3 of 14
Sift0%#12 of 14
The full small business standing →
Mid-marketThe figures above
Signifyd leads by four points.
Signifyd13%#2 of 11
Sift9%#4 of 11
The full mid-market standing →
Enterprise
The order flips: Sift leads at enterprise.
Sift13%#2 of 15
Signifyd12%#3 of 15
The full enterprise standing →

What the models said about Signifyd

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

“reviews highlight issues with accuracy and billing” GLM 4.7 FlashX · negative prompt · hard negative
“far more accessible than enterprise-focused tools like Signifyd, Riskified, or Sift, which often target mid-market+ businesses and can cost thousands per month” Grok 4.20 · budget prompt · soft negative
“Guaranteed protection, zero liability for approved orders. | Higher fees per order; potential increase in false decline rates on borderline orders.” Gemini 3.5 Flash · negative prompt · soft negative
“One of the most widely adopted platforms, especially for mid-to-large merchants on Shopify, Magento, and BigCommerce.” Grok 4.20 · comparative prompt · first choice
“Compare Signifyd or Riskified if your priority is covered chargeback exposure and automated order decisions.” GPT-6 Luna · comparative prompt · first choice
“The best ecommerce fraud prevention platform for a mid-market B2B company is Signifyd.” Llama 4 Maverick · direct 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 seven in this category shown.

“Sift – if you don't have a dedicated risk team, due to complexity and false positives.” DeepSeek V4 Flash · negative prompt · hard negative
“specific complaints focus on the user experience and rule creation” GLM 4.7 FlashX · negative prompt · hard negative
“enterprise-focused tools like Signifyd, Riskified, or Sift, which often target mid-market+ businesses and can cost thousands per month” Grok 4.20 · budget prompt · soft negative
“Sift — *Best Overall for Digital B2B Storefronts & ATO Protection*” Gemini 3.5 Flash · direct prompt · first choice
“I'd recommend requesting demos from ClearSale, Sift, and SEON” MiniMax M2.5 · direct prompt · first choice
“A mid-market friendly, deployment-light option is Sift.” Muse Glimmer 30B · paraphrase 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.