# Signifyd vs NoFraud: which do AI models recommend for ecommerce fraud, October 2026

Finance AI Recommendation Index, October 2026 Edition, Ecommerce fraud prevention. Four of fourteen models named Signifyd first on the direct prompt; zero named NoFraud. Page: https://finance-ai-index.com/receivables/ecommerce-fraud-prevention/signifyd-vs-nofraud/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Signifyd | 8% | #4 of 11 | 19% | 43 | 14 of 14 |
| NoFraud | 8% | #5 of 11 | 13% | 23 | 12 of 14 |

## The direct prompt, model by model

- Mistral Small: signifyd first (first choices: Signifyd) (alternatives: NoFraud, Sift)
- Qwen 3.7 Flash: signifyd first (first choices: Signifyd) (alternatives: Fingerprint, Kount)
- GLM 4.7 FlashX: signifyd first (first choices: Signifyd) (alternatives: ClearSale, Eftsure, SEON, Sift)
- Muse Glimmer 30B: signifyd first (first choices: Signifyd, Wyllo, formerly NoFraud) (alternatives: Eftsure, SEON)
- Claude Haiku 4.5: neither first, one named (first choices: FraudNet, Trustmi) (alternatives: Kount, Sift, Signifyd)
- GPT-5.4 mini: neither first, one named (first choices: Sift) (alternatives: Forter, Kount, Signifyd)
- Gemini 3.5 Flash: neither first, one named (first choices: SEON) (alternatives: Allianz Trade Pay, Sift, Signifyd, TreviPay)
- Perplexity Sonar: neither first, one named (first choices: SEON) (alternatives: Kount, Sift, Signifyd)
- Grok 4.1 Fast: neither first, one named (first choices: Sift) (alternatives: Chargeflow, Fingerprint, SEON, Signifyd, Wyllo)
- DeepSeek V4 Flash: neither first, one named (first choices: SEON) (alternatives: Sift, Signifyd, Stripe Radar)
- Llama 4 Maverick: neither first, one named (first choices: Wyllo) (alternatives: NoFraud, SEON, Sift, Signifyd, cside)
- Kimi K2: neither named (first choices: SEON) (alternatives: Eftsure, Kount, Trustmi)
- MiniMax M2.5: neither named (first choices: ClearSale, SEON) (alternatives: Forter, Riskified)
- GPT-6 Luna: neither named (first choices: SEON) (alternatives: Kount)

## What the models said about Signifyd

- "Signifyd's public terms define eligible chargebacks narrowly... That's a reason to get the exact coverage schedule and exclusions in the signed agreement—not, by itself, a reason to avoid Signifyd." (GPT-6 Luna, negative prompt, soft negative)
- "Choose Signifyd or Riskified if: You want to outsource fraud completely... Go with Signifyd if you are mid-market and want seamless e-commerce platform plug-ins." (Gemini 3.5 Flash, comparative prompt, first choice)
- "The original "chargeback guarantee" pioneer ... Best fit: High-volume merchants ($10M+ GMV) who want fraud completely off their plate." (Kimi K2, comparative prompt, first choice)
- "The Best Overall (Especially for Open Credit): Signifyd ... widely considered the gold standard for B2B commerce" (Qwen 3.7 Flash, direct prompt, first choice)

## What the models said about NoFraud

- "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)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.