Let Customers in,
Keep Fraudsters Out

Traditional fraud controls miss what BioCatch solutions see. Our behavior-first solution continuously analyzes web and mobile sessions in real time detecting subtle anomalies across behavior, devices, networks, and installed applications. By anticipating account takeover threats before fraudsters strike, BioCatch delivers the protection legacy systems can’t.

Protect your customers
and your reputation

ATO fraud is complex, driven by an ever-evolving and diverse range of threats. BioCatch’s ATO solution utilizes continuous behavioral intelligence and advanced profiling to detect anomalies in real time, comparing user activity against genuine behavioral patterns while identifying traits associated with fraudsters. These subtle deviations, when analyzed together, can signal potential criminal intent. This proactive approach delivers a strong, adaptive defense against a wide spectrum of ATO attacks.

Partner with BioCatch, and take back
control of account takeover threats

173 x ROI

In the UK market, for every £1 invested in BioCatch, the customer saved £173

£ 300 k

Average savings per month from detection of authorized push payment fraud

66 %

Increase on fraud detection rates, minimalizing operational impact

95 %

Reduction in residual Zelle fraud losses in only two months after integration

Stop account takeover fraud before money disappears

Does the behavior in the session resemble a genuine user or criminal?

Everyone interacts with their device differently. Profile genuine users and fraudsters based on unique digital behavior traits such as mouse movements, typing cadence, and swipe patterns.

Do the movements show typical human behaviors?

Human patterns are imprecise with natural curves and shakes. Automated scripts and movements created by bots look different.

Are expert user patterns present?

Fraudsters often display advanced computer skills, use keyboard shortcuts, leverage remote access tools, and open developer tools or programmer consoles..

Are there timing anomalies?

Familiarity with data, applications, and payment processes can indicate whether a user is genuine or a fraudster. OTP vishing can be detected through typing cadence during OTP entry

Are the device, IP and network attributes known?

Device, IP and network data are an important part of detecting common types of fraud and creating behavioral insights.

Fraud detection ecosystems: How behavioral intelligence is elevating customer safety in digital banking

Download the white paper to uncover how behavioral intelligence is being used by financial institutions, both large and small, to increase the effectiveness of existing solutions within their fraud detection ecosystem, provide a shared technology framework to improve operational capabilities, and elevate customer safety in digital banking.

Account takeover use cases

Remote access attacks

Legacy fraud controls struggle to detect remote access tools, as banks see a genuine device fingerprint with no signs of proxy, malware, or location spoofing.

Bots and credential stuffing

Fraudsters bypass bot mitigation by using open banking platforms to test smaller, frequent credential batches instead of
large-scale attacks.

Phishing site detection

Over 90% of cyber attacks begin with phishing via email, text, or call. With AI tools like ChatGPT, fraudsters now craft convincing messages that fool even savvy users.

SIM swapping

Fraud involving SIM swapping is growing around the world. Fraudsters gain control over the victim's mobile number and intercept OTPs enabling them to navigate around traditional ATO controls.

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