Group-IB vs BioCatch: Fraud Protection Comparison

Both platforms score the live session in real time. Where they differ is what stands behind that score, and that layer decides whether a scam alert is a lone anomaly your analysts start investigating from zero, or the visible end of a campaign the platform was already tracking.

Modern fraud runs as a campaign: supply chains, infrastructure networks, role-specialised teams, with each transaction the final stage of a process begun weeks earlier. A model bounded by the session is a model that defends events while the adversary runs campaigns. The transaction is not where fraud happens. It is where fraud ends.

A payment ecosystem is only as protected as its least covered stage. The table below walks the ecosystem from account opening to cross-institution intelligence and shows what runs at each stage. The BioCatch column describes scope, and where that scope stops. The stages also map to monitoring across the payment journey, from pre-authentication through authentication, in-session monitoring, and payment, the direction payment-fraud regulation has been moving. That walk covers every fraud type in scope, account opening fraud, account takeover, bot fraud, malware-driven fraud, scams, and authorised push payment fraud, the type regulators are now moving liability onto institutions for, with ACI Worldwide’s Scamscope projecting APP scam losses of $7.6 billion by 2028 across six markets (the US, UK, India, Brazil, Australia, and the UAE) [verify figure and scope before publish].

Notice what the stages have in common. At every one of them, BioCatch’s answer is a reading of the victim’s behaviour, designed to establish that something is wrong. Naming who is behind it draws on adversary research the session does not carry. Group-IB answers each stage twice: with the session signal, and with the identity of the operation behind it. That second answer is Cyber Fraud Fusion. In an earlier Gartner Emerging Tech report on digital commerce fraud, Group-IB was identified as one of two vendors implementing the cyber fraud kill chain as fraud intelligence. It is the difference between defending events and disrupting campaigns, the single most important strategic shift in financial crime prevention today.

A behavioural platform can say a session deviates from a user’s norm. It cannot say which trojan is driving it, whose infrastructure it runs on, or which credential dump the login came from. Those answers live in the criminal ecosystem, not in the session.

Speed is why this matters: research on UK banking data shows 28% of stolen funds are gone within fifteen minutes of the transfer, so a flag raised at the payment arrives after the money. The engine has to know before the session, and that is what the Fraud Matrix, Group-IB’s implementation of the cyber fraud kill chain, provides. It maps a campaign’s techniques across the full chain, so kit deployment, credential trade, device farming, and mule seasoning register as pre-fraud indicators, actioned before the fraud event exists. Illustratively, each layer extends the warning: minutes to hours at the session, days to weeks through the fusion loop, weeks to months at the network layer. The question to ask of any fraud control is not what it catches, but how early it warns.

Behavioural biometrics reads the symptom. The intelligence layer reads the cause: who is scamming, on what infrastructure, and who they will target next.

A vendor’s published research shows what its platform can actually see. Group-IB’s fraud research is a continuous body of work that names malware families, maps infrastructure, and ships into the platform as detection logic and Fraud Matrix scheme entries. Five research streams matter most for this comparison.

The pattern to notice: each research stream ends inside the product. The trojan gets a detection signature, the scheme gets a Fraud Matrix entry, the methodology gets a metric. And the research travels beyond the platform, cited by press and across the fraud and identity industry, so when the market needs a reference for an evolving fraud TTP, an infostealer campaign, or underground activity, this research is among what it cites.

Where BioCatch covers a capability, the table says so, together with the boundary of that coverage. The BioCatch column describes scope and model, never absence.

Group-IB was named a Leader in the inaugural Gartner Magic Quadrant for Cyberthreat Intelligence Technologies (2026), one of five Leaders among eighteen vendors evaluated, with the Cyber Fraud Fusion model cited among its strengths. Separately, in an earlier Gartner Emerging Tech report on digital commerce fraud, Group-IB was identified as one of two vendors implementing the cyber fraud kill chain as fraud intelligence. Fraud Protection is validated by an independent Forrester Total Economic Impact study commissioned by Group-IB.

Gartner, Magic Quadrant for Cyberthreat Intelligence Technologies, 2026; and Gartner Emerging Tech report on digital commerce fraud [confirm exact title and year with Gartner before publish]. GARTNER and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates and are used herein with permission. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact.