Software advice
Best AI Fraud Detection Software in 2026
AI fraud detection software scores payments, sign-ups, logins or transfers for risk using machine learning on device, behavior and transaction data, then approves, blocks or routes each event to a human reviewer. It serves merchants, marketplaces, banks and fintechs. It is not a chargeback insurance policy by default, a general identity checker, or a replacement for the analysts who set risk policy.
Quick answer
SEON ranks first for teams that want a published entry price. Ravelin suits high-volume online merchants, and Sardine fits fintechs that want fraud and AML in one platform. Stripe Radar is the cheapest published route for Stripe users.
Buying fraud software means deciding what kind of loss you are fighting. A webshop worries about stolen cards, refund abuse and chargebacks. A marketplace worries about fake sellers and account takeover. A bank or fintech worries about onboarding fraud, mule accounts and AML duties. Vendors in this space often hide prices behind a demo, so this ranking favors tools that publish what they charge and say plainly who they were built for. It judges detection quality, cost structure, data handling, how hard leaving is, and which team size each tool fits. Prices are as of October 2026, and a tool without a published price is marked as sold on request.
The 11 best AI fraud detection software in 2026, ranked
There is no score. Vendors can pay for more visibility on this website, for example a higher place in a ranking or more room on a page. Commercial relationships can also affect which products we feature and how prominently. How we rank.
| # | Tool | Best for | Free plan | Entry price |
|---|---|---|---|---|
| 1 | SEON | Fintech, payments and gaming teams that want a published entry price and device and digital-footprint signals | No | $699 per month (Starter) |
| 2 | Ravelin | High-volume online merchants in retail, travel, digital goods and marketplaces fighting payment fraud and refund abuse | No | Quoted |
| 3 | Sardine | Fintechs, banks and merchants that want device and behavior signals plus AML work in one platform | No | Quoted |
| 4 | Unit21 | Fintechs, crypto firms and sponsor banks that need fraud and AML cases handled in one place | No | Quoted |
| 5 | Stripe Radar | Businesses that already take payments through Stripe and want fraud screening with a clear tier ladder | Trial | From €10 per month (Radar Standard) |
| 6 | Signifyd | Ecommerce merchants that want the vendor to take on fraud chargeback liability for approved orders | No | Percentage of approved order value |
| 7 | Forter | Large retailers that want fraud decisions tied to a customer identity across checkout, login and returns | No | Quoted |
| 8 | Sift | Marketplaces, SaaS and gaming companies that need payment fraud, account takeover and fake-signup defense | No | Quoted |
| 9 | Feedzai | Banks and large payment firms that want fraud, identity and AML on one platform | No | Quoted |
| 10 | Alloy | Banks and fintechs that orchestrate identity checks from many data vendors during onboarding and monitoring | No | Quoted |
| 11 | DataVisor | Banks and fintechs that want fraud and AML decisions on one platform with unsupervised models. | No | Quoted |
- 1
SEON
SEON takes first place because it is one of few vendors here that prints a price. The Starter tier at $699 a month lets a small risk team start with 2,500 API calls, 50 custom rules and 10 users, and Premium removes those caps. The platform combines more than 1,100 first-party signals with AML screening, so the gap to enterprise suites is smaller than the price suggests.
Strong on
- A public Starter price with stated call, rule and user limits makes budgeting possible before any sales call
- Premium lists unlimited API calls, users and custom rules, with hands-on account management
- Fraud checks, identity verification and AML screening share one case management workflow
Weak on
- 2,500 API calls a month is small for a shop with steady checkout traffic
- Premium has no listed price, so growth past Starter returns to a sales conversation
Skip it if: Large banks that need a vendor with decades of in-house transaction-monitoring models and bespoke integration projects. Starter lists 2,500 API calls monthly, 50 custom rules and 10 users; Premium is custom-quoted.
- 2
Ravelin
Ravelin ranks second because its scope is narrower and clearer than most suites here. It targets high-volume online merchants and covers payment fraud, refund abuse, promo abuse, account takeover, partner fraud on marketplaces and 3D Secure optimization from one platform. The vendor also lists a support and investigations team. The cost is opacity: there is no public price, and every trial starts with a call.
Strong on
- Names refund abuse and promo abuse as products, not only card-not-present payment fraud
- Sector pages for retail, travel, digital goods and marketplaces show who the product was shaped for
- Public API and developer documentation are linked from the site
Weak on
- No published pricing or self-serve signup, so comparison with other vendors needs a sales conversation
- Aimed at merchants, so banks and lenders with AML duties need a different product
Skip it if: Banks and fintechs that need AML transaction monitoring or KYC onboarding in the same tool as merchant fraud rules. Pricing is not published; the site routes visitors to a booked call.
- 3
Sardine
Sardine sits third because it joins fraud prevention, AML compliance and transaction monitoring on one platform built around device and behavior signals. Its site lists device intelligence, behavior biometrics, location unmasking for people hiding their IP, and onboarding checks for consumers and businesses. That breadth suits a fintech with a small risk team. The tradeoff is that nothing about cost is public, and the pitch leans on agentic automation claims.
Strong on
- Device intelligence, behavior biometrics and onboarding verification are described as modular blocks that can be adopted separately
- Fraud and AML work share one vendor, which reduces handoffs for a small compliance team
- Location unmasking targets fraudsters who hide their real IP address
Weak on
- No public pricing or trial, so budgets depend on a demo and a quote
- Positioned for financial services, which makes it heavier than a webshop needs
Skip it if: Small online shops that want a plug-in with a fixed monthly fee and no onboarding project. No pricing is published; the site directs buyers to a demo request.
- 4
Unit21
Unit21 is fourth because it is built around analyst workload more than raw scoring. Fraud monitoring, device intelligence, a consortium and AML tooling such as sanctions screening and regulatory filings sit on one platform, and the vendor says configurable AI agents carry cases from alert to filing with a human in the loop. It fits compliance-heavy fintechs, and the claims about fewer false positives come from its own marketing.
Strong on
- Fraud and AML modules, including case management and regulatory filings, run on a single platform
- Verticals are named explicitly: fintech, crypto, sponsor banks and financial institutions
- AI agents are described as drafting investigation narratives with an audit trail and human review
Weak on
- Pricing is not public, so evaluation starts with a demo
- Built for regulated financial firms, which is more than an online retailer needs
Skip it if: Retailers whose main losses are chargebacks and promo abuse, not sanctions screening or regulatory reporting. No pricing is published; buyers request a demo.
- 5
Stripe Radar
Stripe Radar is fifth because it is the only entry here with three published tiers. Standard covers default rules, card-testing prevention and analytics from €10 a month. Plus adds custom rules, backtesting, manual review and 0 to 99 risk scores. Pro adds abuse signals for bots, multi-accounts and free-trial abuse. Radar is aimed at payment fraud, and the vendor says it works whether or not payments run on Stripe.
Strong on
- Three tiers with a public feature matrix make it easy to see what each step unlocks
- Plus adds custom rules with backtesting and manual reviews for teams that want control
- Pro covers abuse such as multi-accounting and free-trial misuse beyond card fraud
Weak on
- Risk scores and custom rules require Plus, so Standard offers little tuning
- Strongest where payments flow through Stripe, and has no AML module
Skip it if: Banks and lenders that need identity onboarding, AML monitoring or case workflows across several payment processors. Business prices start at €10 (Standard), €14 (Plus) and €19 (Pro) per month, or pay as you go.
- 6
Signifyd
Signifyd ranks sixth because it prices on outcomes. Its pricing page says it charges a percentage of the order total when an order is approved, nothing when it declines for fraud, and it offers a financial guarantee on approved orders. That shifts liability from merchant to vendor, which suits retailers who dislike managing rules. The cost is a revenue-linked fee set through assessment and a custom quote, and a merchant-only product scope.
Strong on
- A financial guarantee on approved orders moves chargeback liability to the vendor
- Related modules cover account protection, return abuse and PSD2 exemption management
- Fees apply only to approved orders, not to fraud declines
Weak on
- The fee scales with approved order value, so it rises as sales rise
- Exact pricing needs a custom quote after a review of your losses and declines
Skip it if: Businesses that want to own their rules and pay a flat fee regardless of order value. Priced as a share of each approved order; the rate depends on vertical, volume and ticket size.
- 7
Forter
Forter is seventh because the site pitches identity-based decisions across the whole shopper journey rather than a single score at checkout. Its list covers fraud management, payment optimization, dispute management, account protection and abuse prevention, plus a connector for payment service providers and an agentic commerce offer. That is a lot of surface for one vendor to cover. Detail on cost and contract terms is not public.
Strong on
- Five named product areas let a merchant start with fraud and add disputes or payments later
- A separate Element product is built for payment service providers to resell
- Agentic commerce features aim at purchases placed by AI agents
Weak on
- There is no price information, so a quote is required before any comparison
- Broad scope means smaller shops may pay for modules they do not use
Skip it if: Small merchants that want self-serve signup and a published monthly price. No pricing is published; the site directs visitors to a sales contact.
- 8
Sift
Sift is eighth because the product is mature but opaque on cost. It describes a machine-learning platform fed by more than a trillion annual events across 700 or more brands, aimed at payment fraud, account takeover and fake account creation. Industry pages cover SaaS, marketplaces, iGaming, food delivery and travel. A recent Attack Detection Agent alerts on spikes. The vendor publishes a Score API for developers, but no prices.
Strong on
- Use cases span payments, account takeover and fake accounts, with pages for marketplaces and SaaS
- A documented Score API gives developers a direct integration path
- An Attack Detection Agent flags velocity spikes such as sudden account creation surges
Weak on
- Its pricing page returns not found, so costs come only from sales
- Network claims are the vendor's own figures and cannot be checked
Skip it if: Teams that need a fixed list price they can approve without talking to sales. No pricing page is published; the site offers demos.
- 9
Feedzai
Feedzai places ninth because the platform is shaped for banks and payment institutions, not merchants. Its RiskOps platform covers transaction fraud, new account fraud, scam prevention, AML transaction monitoring and watchlist screening, and Farol is an AI agent for rules, alerts and suspicious activity reports. Offices are listed in New York, London, Atlanta and three Portuguese cities. Costs and deployment size are not published, which points to enterprise projects.
Strong on
- One platform spans fraud, identity verification and AML for banks
- Farol, an AI agent, helps analysts with rules, alerts and SARs
- Feedzai IQ adds network intelligence for acquirers and merchants
Weak on
- Enterprise positioning with no public pricing or trial
- A bank-scale rollout is likely to be too heavy for a small online shop
Skip it if: Small ecommerce teams that need a working setup within days and a fee below enterprise contract size. No pricing is published; the site offers a demo request.
- 10
Alloy
Alloy takes tenth place because it solves a different job than most tools above. It is an identity and fraud decisioning platform that sequences calls to a catalog of 300 or more data partners, then applies rules and a machine-learning Fraud Signal model across onboarding, transactions and ongoing KYC and KYB. The vendor reports more than 900 financial institutions as customers. A merchant fighting chargebacks will find it indirect.
Strong on
- An orchestration engine routes inputs and sequences vendor calls without custom code
- A catalog of 300 or more data partners keeps the setup vendor-neutral
- Onboarding, fraud and perpetual KYC and KYB checks sit in one decision flow
Weak on
- Built for financial services, with little coverage of chargebacks or promo abuse
- No published price, so each data partner adds its own cost on top of a quote
Skip it if: Online retailers whose main need is blocking stolen-card orders and chargebacks. No pricing is published; buyers schedule a demo.
- 11
DataVisor
DataVisor is a fraud and financial-crime platform made by DataVisor that combines a fraud product, an AML offering and a combined FRAML platform, with unsupervised and supervised models and an AI agent named Vera. It ranks eleventh because the buyer profile is narrow, mainly financial institutions, and the site publishes no price or trial, so a webshop or marketplace has less reason to start here.
Strong on
- Unsupervised and supervised machine learning sit in one product, aimed at fraud rings and new attack patterns.
- AI agents help with rule creation, investigations, alert summaries and suspicious activity report narratives.
Weak on
- No price or free trial is published, so cost is learned only through sales.
- The site gives latency figures of under 30 ms and under 100 ms in different places.
Skip it if: Small online shops that need a plug-in checkout tool with transparent per-transaction pricing. Pricing is not published; the site routes buyers to contact sales and a demo request.
How these AI fraud detection software were judged
How accurate is AI fraud detection software in practice?
Accuracy depends on your data, not on a vendor's headline figure. Network vendors such as Sift and Feedzai say pooled signals across customers help catch new attacks. Stripe Radar learns from payments across Stripe, and Signifyd backs its decisions with a financial guarantee, which is the clearest accuracy commitment on this list. Every approval-rate or loss-reduction number on vendor sites is self-reported. A fair test is a shadow run on three months of your own orders: compare what the tool would have blocked against real chargebacks, and count how many good customers it would have declined.
What does fraud detection software cost for a small business?
Published prices are rare. Stripe Radar lists business tiers from €10, €14 and €19 per month or pay as you go, and SEON lists Starter at $699 per month with 2,500 API calls. Signifyd takes a percentage of approved order value, so its cost rises with sales. Ravelin, Forter, Sift, Sardine, Unit21, Feedzai and Alloy sell through demos and quotes. Budget for the full cost: subscription, per-decision fees, data add-ons, and the analyst hours spent reviewing flagged orders, since manual review is usually the largest hidden line.
What happens to customer data when you use a fraud tool?
A fraud tool must receive names, emails, devices and payment details, so read the data terms before you integrate. Stripe's privacy policy states that it uses data to train AI models to protect against fraud, which matters if you want strict control. Vendors with network models usually pool signals across customers, so ask what is shared and for how long it is kept. Ravelin names a registered London office and SEON a Budapest seat in their notices. For the other vendors the policy was not checked in depth here, so request a data processing agreement and a retention schedule.
How hard is it to switch fraud detection vendors?
Switching is costly because the tool sits in the checkout and sign-up path and holds your tuned rules and history. Lock-in rises with network features and embedded workflows: Alloy orchestrates multiple data vendors, Unit21 and Feedzai hold case history for regulators, and Signifyd's guarantee only applies while its decision runs. API-first tools with exportable rules are easier to leave. Before signing, ask for a rules export, case data in a standard format, and a notice period, and plan a parallel run of at least a month before cutting over.
Which fraud detection tool fits a merchant, a marketplace or a bank?
Match the tool to the loss. A Stripe-based shop with modest volume can start with Radar tiers. A larger retailer fighting refund and promo abuse should evaluate Ravelin, Forter or Signifyd, and a marketplace should test Sift or Forter. Fintechs with AML duties belong in the Sardine, Unit21 or SEON group, and banks with large transaction volumes should look at Feedzai or Alloy. Team size matters too: a three-person risk team wants a product that explains decisions and offers managed support, while a large team can run its own rules.
How to choose an AI fraud detection tool in three steps
- Name the fraud type that costs you most. Pull twelve months of losses and split them into stolen-card chargebacks, refund and promo abuse, account takeover, fake sign-ups and onboarding fraud. A merchant dominated by chargebacks needs a payment fraud tool such as Ravelin, Signifyd or Radar. A fintech dominated by mule accounts needs identity and AML in the same platform, which is the Sardine, Unit21 and Alloy group. Writing this down first stops you from buying a broad suite for a narrow problem, and it gives every vendor the same brief during demos, so the answers can be compared line by line.
- Run a shadow test on your own data. Ask each shortlisted vendor to score three months of historical events without blocking anything. Compare their decisions with your confirmed chargebacks and with orders you manually approved. Count good customers they would have declined, because false declines cost sales that never show up in a fraud report. Vendors with public sandbox or developer documentation, like Sift and Ravelin, make this easier. If a vendor refuses a retrospective test, treat that as information about how it expects to be judged, and move to the next candidate on the list.
- Price the whole workflow before you sign. Add the subscription or per-decision fee, the integration work, and the analyst hours for manual review. Outcome-priced tools like Signifyd shift cost to a percentage of approved sales, while SEON and Stripe Radar bill against fixed tiers or volume. Ask what happens when traffic doubles in a campaign week. Then ask for the exit terms in writing: notice period, rules export and data deletion. The cheapest sticker price often loses once review hours and overage fees are counted, so compare totals, not tiers.
Frequently asked questions
What is the best AI fraud detection software in 2026?
SEON ranks first in this list because it publishes a Starter price of $699 per month and pairs device and digital-footprint signals with AML tooling. Ravelin ranks second for high-volume online merchants, and Sardine third for fintechs. The right choice depends on whether your losses are chargebacks, account takeover or onboarding fraud.
Which fraud detection tools publish their prices?
Stripe Radar lists tiers from €10, €14 and €19 per month for businesses, and SEON lists Starter at $699 per month. Signifyd explains that it charges a percentage of approved order value but quotes rates per merchant. Ravelin, Forter, Sift, Sardine, Unit21, Feedzai and Alloy did not show a price on their sites in October 2026.
Can small businesses use enterprise fraud platforms?
Technically yes, but most enterprise platforms here sell through demos and custom contracts, and several are built for banks. A small webshop is usually better served by Stripe Radar if it uses Stripe, or SEON Starter if it needs a rules engine and device signals. Feedzai and Alloy fit larger regulated firms.
Does a fraud tool take over chargeback liability?
Only some do. Signifyd states a financial guarantee on approved orders and charges a percentage of approved order value for it. Most other tools in this list score events and leave liability with the merchant. Read the contract wording on what is covered, such as fraud-only versus non-fraud chargebacks, before relying on a guarantee.
Do these tools also handle AML compliance?
Several do. SEON, Sardine, Unit21, Feedzai and Alloy list AML or KYC features such as customer screening, transaction monitoring or perpetual KYB. Stripe Radar, Sift, Signifyd, Forter and Ravelin focus on fraud and abuse for merchants and platforms. If you have regulatory AML duties, check the module list before you shortlist.
How long does it take to integrate fraud detection software?
It varies with the tool. SEON describes launching in days, and Stripe Radar is switched on inside an existing Stripe account. Bank-grade platforms such as Feedzai and Alloy involve data mapping and project work that vendors do not put a time on. Ask each vendor for a reference customer of your size and ask how long theirs took.
Is Stripe Radar enough without another tool?
For many Stripe-based shops, Radar covers card testing, default rules and analytics. Plus adds custom rules and backtesting, and Pro adds abuse signals. It does not cover AML, identity onboarding or case workflows, so marketplaces and fintechs usually add a second tool. Radar states it can work even if payments do not run on Stripe.
What should I ask a fraud vendor about data use?
Ask whether your data trains models shared with other customers, how long events are retained, where they are hosted, and whether you can request deletion. Stripe's privacy policy says data is used to train AI models for fraud protection, so policies differ. Get the answers inside a data processing agreement, not a sales call.