Best Fraud Detection Software (2026): Top 10 Compared

Stripe Radar is the fraud detection product built into Stripe's payments platform. Stripe's documentation explains that Radar evaluates transactions in real time and that every Radar pricing tier charges a fee for each transaction it evaluates, including recurring payments. Stripe Billing users are the exception and are billed only for the first transaction in a subscription. The pricing page also states that Radar's AI works across a business whether or not Stripe processes its payments, although protection for payments outside Stripe is listed under the enterprise option.

The tier structure is published. Radar Lite covers AI-based fraud prevention for card payments, card testing prevention and fraud alerts, and is included at no additional charge for businesses on standard Stripe payments pricing. For individual businesses, Radar Standard starts at $10 a month, Radar Plus at $14 a month and Radar Pro at $20 a month, each with a pay-as-you-go alternative. Platforms and marketplaces have their own tiers starting at $20, $44 and $70 a month. Enterprise buyers can request tailored recommendations, custom pricing and access to Radar's risk signals. The pay-as-you-go per-transaction rates sit behind an expandable panel on the pricing page and were not recorded for this comparison.

The comparison table on the pricing page shows what each tier adds. Standard covers fraud prevention across all payment methods, default rules, allowlists and blocklists, early fraud warning signals and a three-level risk rating. Plus adds numeric risk scores, custom rules with backtesting, manual reviews, risk preferences, Adaptive 3D Secure, Smart Refunds and Radar Assistant. Pro adds dynamic risk thresholds and abuse signals for free trial abuse, bots, multi-account behaviour and account sharing.

The clearest fit is a merchant or platform already processing cards on Stripe. Banks monitoring account-to-account transfers are outside the product's stated focus.

SEON is a fraud prevention platform that has extended into AML compliance, and it also appears on the StatWharf AML software page for that reason. On this page the focus is the fraud line. The pricing page describes an API-first approach intended to be connected quickly, and says the platform draws on more than 1,000 online and device signals to identify risky users and transactions. SEON's own case study quotes on that page cite uses such as payment fraud reduction, bonus abuse prevention and multi-accounting detection at registration. Those figures are vendor-reported.

Pricing is unusually transparent for the category. The Starter plan costs $699 a month and includes SEON platform and API access, 2,500 fraud checks a month, 10 users and 50 custom rules. Implementation help on Starter comes through support tickets and email, with basic monitoring and standard reporting. The Premium plan is priced on request. It adds case management and AML compliance, unlimited API calls, unlimited users and unlimited custom rules, a dedicated implementation team, round-the-clock support with hands-on account management, and Managed Risk Services, which the vendor describes as consultative support with tailored strategies.

The two-tier structure suggests a practical path for smaller online businesses. A merchant, marketplace or gaming operator can begin on Starter with a defined monthly budget and a fixed check allowance, then move to Premium once volumes grow or once compliance obligations require case management. Buyers should ask what happens when checks exceed the Starter allowance, because the pricing page does not state an overage rate.

Banks with large transaction monitoring estates are not the audience the pricing page describes. SEON positions Starter at small and medium-sized businesses and Premium at organisations that want protection across the whole customer journey. Buyers comparing it with guarantee-based vendors should note that SEON sells detection and tooling, not chargeback liability cover.

Sift describes itself as a fraud prevention platform for digital businesses, combining AI and machine learning models, configurable workflows, identity-centric global data and expert analysts. Its homepage cites a global data network of more than 1 trillion annual events and names Hertz, Yelp and Poshmark among its customers. The platform covers payment fraud, account takeover and account abuse across the account, transaction and post-transaction stages.

The Payment Protection product is the part most relevant to transaction fraud. Sift states that every transaction is scored in under 150 milliseconds using device, behaviour, network and identity signals, with more than 16,000 risk signals behind each score. The vendor describes a patented ensemble of models that retrains continuously as fraud patterns shift, plus global, cohort and custom models. Fraud types listed include stolen card fraud, card testing, buy-online-pick-up-in-store abuse, alternative payment method fraud and fraudulent currency movement.

Control is the main theme. Sift contrasts its approach with black-box scores and points to Score Explainability, network visualisation and transaction activity views, so analysts can see why a decision was made. Teams can test policies and thresholds against historical traffic before they go live, build workflows in a no-code decision engine, and decide in bulk from the console. The vendor also lists dispute data ingestion, historical chargeback import, pre-built workflow templates, PSD2 compatibility and turnkey integrations with identity verification, 3D Secure, KYC and AML providers.

Sift does not publish prices. Its pricing paths return no page, and buyers are directed to sales for a quote. The product suits organisations with a fraud or trust and safety team that wants to tune decisions itself. Merchants that would rather hand over fraud losses to a vendor may prefer the guarantee-based providers on this page.

Signifyd sells fraud protection to ecommerce merchants built around a financial guarantee. Its Guaranteed Fraud Protection product uses AI-driven decisioning at checkout to approve or decline each order, and approved orders are backed by a guarantee against fraud chargebacks. Signifyd says merchants are reimbursed for chargebacks on approved orders, which moves fraud loss from the merchant's books to the vendor's.

The detection layer draws on what Signifyd calls its commerce network. The product page cites more than 25,000 data features and describes custom, chained models trained for different ecommerce verticals. The pricing page adds that Signifyd collects session data such as IP address, behaviour and transaction data, and correlates it with forensic data and more than 150 out-of-band identity sources. Merchants can tune the risk threshold against target chargeback and approval rates, and the models learn from merchant feedback such as chargebacks and bank authorisation outcomes.

The pricing model is stated even though the rate is not. Signifyd charges a percentage of the order total when an order is approved, with no charge when an order is declined for fraud. The percentage depends on the products sold, the merchant's vertical, order volume and average ticket price. Exact pricing follows an assessment of current fraud operations, chargeback losses and order declines. The guarantee itself is configurable, ranging from fraud-only protection to a total chargeback liability shift.

Integration options are broad. Signifyd lists pre-built order integrations with Miva, BigCommerce, Adobe, Salesforce Commerce Cloud, Shopify, NetSuite, Accertify and VTEX, payment integrations with Adyen, Stripe, PayPal, Square and Worldpay, and REST APIs, webhooks, JavaScript tags and mobile SDKs for custom builds. The fit is an online retailer that wants predictable fraud cost per approved order rather than an in-house tuning operation.

Riskified is an ecommerce fraud prevention company that describes protecting the shopping journey from login to checkout to refund claims and returns. Its homepage lists digital goods, retail, luxury fashion, travel and athletic and outdoor brands among the segments it serves, and includes customer testimonials from companies such as Lorna Jane, Rue Gilt Groupe, Gametime, Booking.com and Finish Line. The outcome figures in those testimonials are customer-reported.

The core product is Chargeback Guarantee. Riskified states that it guarantees approval rates and covers chargebacks on approved orders, and that merchants pay only for approved orders that generate revenue. Its machine learning models analyse hundreds of features per transaction and return approve or decline decisions in under a second. The vendor says each decision draws on more than a billion prior transactions from nearly a decade of guarantee decisions. Recover, included with Chargeback Guarantee, runs customer verification flows for borderline orders to reduce false declines, and a Control Center lets fraud teams track performance and analyse trends.

The rest of the suite extends past the checkout decision. Adaptive Checkout adjusts the shopping flow for each customer's risk profile. Policy Protect targets refund, promotion and reseller abuse. Dispute Resolve collects evidence and manages chargeback disputes. Account Secure addresses account takeover. Riskified states support for payment methods from ACH and open invoices to digital wallets, and integrations through its API, Magento, Stripe and Shopify.

No prices are published. The pricing link leads to a contact form, so buyers should expect a quote based on order volume and risk profile. The fit is a larger online merchant that wants the vendor to carry chargeback risk on approved orders and also has abuse problems beyond payment fraud. Banks and payment processors monitoring account transfers sit outside the product's stated scope.

Forter positions itself as a decision platform for commerce, covering fraud management, payment optimisation and what it calls agentic orchestration. Its homepage describes a single decision layer across pre-purchase, checkout, account activity and post-purchase flows, and stresses that the product is payment and processor agnostic, so merchants are not tied to one acquirer or gateway.

The fraud management product rests on the Forter Network, which the vendor sizes at more than 2 billion identities across more than 250,000 storefronts. Forter says its AI analyses identity, behavioural, device and payment signals in real time to recognise returning legitimate customers and stop chargebacks before they occur. The same decisions apply across cards, wallets, buy now pay later, ACH, gift cards and alternative payment methods, which reduces the need for separate tools per payment type. For investigations, an Analytics Agent assembles transaction context and surfaces the signals that matter, and Forter Prism provides intelligence inside the merchant portal.

Two areas extend beyond classic fraud detection. Payment Optimization is presented as a way to raise authorisation rates and reduce costs by orchestrating payment flows. Agentic Orchestration addresses AI shopping agents: the vendor says it helps brands accept legitimate AI shoppers while blocking automated attacks across new commerce protocols. Buyers preparing for agent-initiated purchases may find this relevant; others can treat it as optional scope.

The homepage reports averages for chargeback reduction and false decline reduction, and customer quotes about higher approval rates. These are vendor-reported figures. Forter publishes no prices, and its pricing page is a contact-sales form. The fit is a large online merchant, marketplace or travel business with multiple payment providers and enough order volume to justify an enterprise decisioning contract. Banks screening account-to-account payments are not the audience described.

Sardine describes itself as an agentic risk platform that unifies fraud prevention, AML compliance and real-time transaction monitoring for banks, merchants and fintechs. It is one of the few vendors on this page whose published material addresses both buyer groups directly, with separate product pages for merchant payment fraud and bank payment fraud.

For merchants, the payment fraud page describes pre-authorisation risk scores built from checkout behaviour, device risk, shipping address signals and cardholder verification. Rules can be created, modified and backtested in a no-code editor, and workflows can approve, step up, decline or route orders to a chargeback guarantee provider. An AI agent collects dispute evidence and submits it to the acquirer. Coverage extends to marketplace payments, gift cards and digital goods, and deposit and cashout risk in digital wallets and iGaming.

For banks and fintechs, the bank payment fraud page lists ACH, wires, SEPA, RTP, FedNow, Zelle and checks. Sardine says it evaluates transactions before funds move, can hold instant payments for review, and predicts ACH returns for unauthorised debits and insufficient funds by return code. It also covers altered or duplicate check deposits and fraudulent payouts or payroll disbursements.

The modelling layer is open. Sardine offers consortium-trained models, a feature store the vendor sizes at more than 12,000 risk features, and a Model Garden where teams can host their own models next to Sardine's. The wider platform adds KYC, KYB, document verification, sanctions screening and customer risk rating. No prices are published, so buyers should ask how cost scales when fraud, AML and identity products are combined. The fit is a fintech, sponsor bank or payments company that moves money across several rails and wants fraud and compliance teams working in one system.

Feedzai is an AI-native fraud and financial crime prevention platform that serves customers from global banks to emerging fintechs. Its homepage states that it secures around $9 trillion in payments each year and reports results from a tier 1 bank against that bank's previous solution, including more fraud detected and fewer false positives. These are vendor-reported figures. The site also cites analyst recognition, including a fraud prevention leader placement in the Chartis 2026 RiskTech Quadrant for fraud platforms.

The Transaction Fraud solution is the product closest to this category. Feedzai says it combines behavioural, non-monetary and monetary data to detect fraud across every payment channel. Its 360-View Customer Profiles build a risk profile for each customer from behaviour patterns, transaction history and cross-channel activity, an approach the vendor calls segment-of-one profiling. TrustScore adds network-wide intelligence from Feedzai's customer base, and the vendor states that clients detect four times more fraud with half the alerts compared with rules alone. Explainable AI, integrated case management and analyst tools are listed as part of the product.

Integration is designed for existing fraud estates. Feedzai says the platform ingests data from databases, transaction systems and third-party tools, can enrich its decision engine with custom rules or external scores, and supports importing and exporting machine learning models. Behavioural biometrics and device intelligence are offered alongside transaction monitoring, and a separate AML capability lets institutions run fraud and anti-money laundering on the same platform.

No prices are published, and buyers request a demo. The fit is a retail bank, card issuer or processor that needs real-time scoring across many channels and has the data and model governance to use a configurable platform. Ecommerce merchants looking for a checkout plugin will find the guarantee-based vendors on this page closer to their needs.

Featurespace is a transaction monitoring company that builds AI tools for financial institutions to prevent fraud and financial crime. Visa announced on 19 December 2024 that it had completed its acquisition of Featurespace. The announcement said the business would join Visa's Risk and Identity Solutions unit and that Featurespace's product portfolio would be incorporated into Visa's existing offering over the following months. Buyers evaluating Featurespace should therefore ask how the product is packaged and sold today.

The Featurespace Platform, earlier marketed as ARIC Risk Hub, is built around Adaptive Behavioral Analytics and Automated Deep Behavioral Networks. The vendor describes these as machine learning techniques that profile each customer's actions, compare them with peer groups and analyse scam behaviour, adapting as behaviour changes. The platform is designed specifically for financial institutions. The homepage says it is live in large banks, payment processors, merchant acquirers, insurance companies and gaming organisations, and is deployed on-premises or as a fully hosted cloud service in more than 180 countries.

The solutions page adds a single integrated risk-scoring product for scams and account takeover, and a multi-tenancy capability that lets issuers and acquirers control the experience offered to their own customers. That is relevant to processors that run fraud detection on behalf of many client institutions. Featurespace publishes case studies with NatWest on scam detection and TSYS on fraud losses. The results in those studies are vendor-reported, and the volume figures quoted on the homepage and solutions page differ, so buyers should confirm current figures directly.

No prices are published. The fit is a bank, card issuer, acquirer or processor with in-house fraud strategy teams and a need for real-time behavioural scoring, particularly for authorised push payment scams. Online merchants are not the buyer described on the vendor's pages.

NICE Actimize is the financial crime division of NICE and also appears on the StatWharf AML software page. This entry covers its fraud products. The Enterprise Fraud Management page presents IFM as an AI-driven fraud management platform that applies AI across detection, strategy, investigations and operations, together with data orchestration. The vendor describes intent-based AI, granular customer profiles and collective industry intelligence, with protection across all channels and payment types.

IFM is organised by use case. Scams and Mule Defense looks for suspicious activity patterns across the customer lifecycle, including money mule accounts. Payments Fraud provides real-time monitoring of payments. New Account Fraud targets onboarding. Investigations brings investigation functions and data into one platform, and Authentication Management helps institutions manage customer authentication across channels and set fraud strategy in real time. The resource library on the page covers check fraud, fast payments fraud, authorised push payment scams and the UK shift of reimbursement liability, which indicates the problems the product is built for.

Smaller institutions have a separate route. Xceed is described as real-time fraud detection and prevention for small and mid-sized banks, and the Xceed page presents Xceed AI FRAML as fraud prevention and AML compliance in a single platform for credit unions and community banks. It has three parts: Xceed AI Fraud for transaction monitoring across channels and payments, Xceed AI AML, and Xceed AI Investigations, which uses AI agents to triage and automate routine investigation work.

No prices are published, and both product pages lead to demo requests. The fit is a bank or credit union with an established fraud function, especially one consolidating fraud and AML operations. Online merchants and early-stage fintechs will find lighter, API-first options elsewhere on this page.