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Index › Receivables and billing › Ecommerce fraud › Eftsure vs ClearSale
Ecommerce fraud prevention · October 2026 Edition

Eftsure vs ClearSale

Zero of fourteen models named Eftsure first on the direct prompt; one named ClearSale. Eftsure was named by eleven of the fourteen models and ClearSale by eight and both carry 16 labels, so the shares below are directly comparable.

Eftsure

accepted challenger

Named in three categories this edition.

ClearSale

accepted challenger

Named in two categories this edition.

First-choice share16%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#7A position in a field of 11; printed, not drawn.
Labels1616Equal, which is what makes the shares comparable.
The two percentage rows are drawn on one 0 to 100 track, Eftsure 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 Eftsure · SEON vs ClearSale · Eftsure vs Stripe Radar

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.
EftsureFirst choices, of fourteen modelsClearSale
Direct01
Paraphrase80
Comparative00
Budget-constrained00
Scale-constrained00
Negative002 against ClearSale
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.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Eftsure and ClearSale stood in it.
ModelDirectCLParaphraseCLComparativeCLBudget-constrainedCLScale-constrainedCLNegativeCL
Claude Haiku 4.5CL
GPT-5.4 mini
Gemini 3.5 FlashCLCL
Perplexity Sonar
Grok 4.1 FastCL
Mistral Small
DeepSeek V4 FlashCL
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2CL
GLM 4.7 FlashXCLCL
MiniMax M2.5CLCL
GPT-6 Luna
Muse Glimmer 30B
EftsureCL ClearSale first choice named as an alternative argued againstblank: not namedEach cell is one answer, Eftsure on the left and ClearSale on the right.

The direct prompt

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

ClearSale first, Eftsure not the choice

1 of 14 modelsEftsure was named in the answer but not as the choice, or not at all.
MiniMax M2.5ClearSale, SEON alternatives: Forter, Riskified

Neither was the first choice, one was named

3 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Kimi K2SEON alternatives: Eftsure, Kount, Trustmi
GLM 4.7 FlashXSignifyd alternatives: ClearSale, Eftsure, SEON, Sift
Muse Glimmer 30BSignifyd, Wyllo, formerly NoFraud alternatives: Eftsure, SEON

Neither was named

10 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5FraudNet, Trustmi alternatives: Kount, Sift, Signifyd
GPT-5.4 miniSift alternatives: Forter, Kount, Signifyd
Gemini 3.5 FlashSEON alternatives: Allianz Trade Pay, Sift, Signifyd, TreviPay
Perplexity SonarSEON alternatives: Kount, Sift, Signifyd
Grok 4.1 FastSift alternatives: Chargeflow, Fingerprint, SEON, Signifyd, Wyllo
Mistral SmallSignifyd alternatives: NoFraud, Sift
DeepSeek V4 FlashSEON alternatives: Sift, Signifyd, Stripe Radar
Llama 4 MaverickWyllo alternatives: NoFraud, SEON, Sift, Signifyd, cside
Qwen 3.7 FlashSignifyd alternatives: Fingerprint, Kount
GPT-6 LunaSEON alternatives: Kount

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
ClearSale leads by five points.
ClearSale5%#6 of 12
Eftsure0%#– of 12
The full small business standing →
Mid-marketThe figures above
The order flips: Eftsure leads at mid-market.
Eftsure16%#2 of 11
ClearSale2%#7 of 11
The full mid-market standing →
Enterprise
Eftsure leads by two points.
Eftsure2%#– of 9
ClearSale0%#9 of 9
The full enterprise standing →

What the models said about Eftsure

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

“Best for Preventing B2B Payment Fraud (Vendor/Invoice Fraud) ... Eftsure ... Designed specifically for mid-to-large enterprises managing complex vendor ecosystems.” Qwen 3.7 Flash · paraphrase prompt · first choice
“Eftsure is the most specialized and highly recommended due to its real-time vendor validation, B2B focus, and financial guarantee.” Mistral Small · paraphrase prompt · first choice
“I'd suggest starting with Eftsure or Trustmi since they're specifically built for B2B payment fraud use cases.” MiniMax M2.5 · paraphrase prompt · first choice

What the models said about ClearSale

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

“it can introduce a slight delay in order processing. Some merchants have also noted inconsistencies in support quality.” Claude Haiku 4.5 · negative prompt · soft negative
“I'd recommend starting with ClearSale or SEON as they specifically target mid-market businesses” MiniMax M2.5 · direct prompt · first choice
“Choose ClearSale if: You sell high-value luxury goods or ship to high-risk international markets” Gemini 3.5 Flash · comparative prompt · alternative
“Human-in-the-loop review for complex decisions, paired with automation for speed” DeepSeek V4 Flash · comparative prompt · alternative
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.