Antifraud - Fraud Detection Software

Fraud Detection Features

Protect against browser-based attacks.
Antifraud identifies behavioural biometrics associated with known Man-in-the-browser attacks, as well as other browser-based malware and trojans. This allows your teams to automate a response that prevents the customer becoming a victim of fraud. Without Antifraud, these types of attacks are extremely difficult to detect.

Take a ‘fingerprint’ of every user.
Antifraud creates a detailed behavioural fingerprint for each customer. This fingerprint is made up of dozens of device, browser and behavioural signals. These signals go way beyond geolocation data, forming an unmistakable user signature.

A unique on-premise deployment for your organisation - avoiding recognisable patterns. High-profile fraud detection tools often have a major weakness: predictable patterns of deployment that make it easy for fraudsters to detect and work around. We've solved this problem by making each Antifraud deployment unique, avoiding predictable patterns. The Antifraud JavaScript Agent is easy to hide within your existing JavaScript files as part of your build pipeline.

Runs privately and securely on your own servers.
Antifraud runs on your own servers and sends encrypted fraud detection analytics data to your fraud analytics platform of choice. It’s designed for use with Splunk, ELK, and other analytics solutions that ingest JSON data. Enable monitoring, alerting, and automated responses based on Antifraud’s fraud telemetry data, helping you to measurably reduce fraud losses.

Antifraud upholds data privacy and regulatory compliance by ensuring your sensitive PII never leaves your own internal systems.

Automate a response to suspicious users.
Once you’ve associated a behavioural fingerprint with suspicious activity, you can set up alerting around this fingerprint and automate a rapid response using your existing toolchain. Profile the fraudster’s connection, create a ticket, block access, or gather intel. Your workflows are the only limit.

Always ready to detect new threats.
We ensure Antifraud is kept up-to-date, able to detect the latest threats to your customers. Antifraud can also protect against custom malware created specifically to defraud your organisation. If you’re facing a new threat, we’ll ensure Antifraud is up to the challenge.

Works with your existing analysis tooling

Antifraud produces fraud detection telemetry in JSON format, ready for ingestion by your pre-existing fraud analysis tools. Antifraud integrates painlessly with Splunk or ELK, or any log management or fraud analysis tooling with the capability to ingest JSON data.

Built for Banking and FinTech First

Antifraud has its origins in fraud prevention for banking, since banks face many of the toughest fraud detection and prevention challenges imaginable. When it comes to banking fraud detection, Antifraud is ready to detect and prevent common forms of banking and payments fraud including identity theft, account opening fraud, money laundering and money mule accounts, phishing, and browser-based malware.

Its suite of powerful features mean Antifraud has quickly become one of the best fraud detection tools in banking.

Solutions

Antifraud is used to prevent many different kinds of fraud and money laundering, including:

• Browser-based Malware and Trojans. Antifraud identifies behavioural biometrics associated with known browser-based malware and trojans.
• Account Takeover Fraud. Automatically monitor user sessions to reveal suspicious actions.
• Payment Fraud. Identify and respond to unusual payment behaviours.
• Money Laundering and Mule Accounts. Behavioural biometrics can track the way users interact with online banking platforms or financial applications. Sudden changes in these interaction patterns, especially if they involve high-value transactions or transfers, could raise red flags for potential money laundering and money mule activities.
• Phishing and Social Engineering Attacks. Identify anomalies in user behaviour that could be the result of phishing or other social engineering attacks.

Use Cases

• Banks and other financial institutions
• FinTech
• Critical infrastructure
• eCommerce
• Digital marketplaces
• Government
• Service providers
• Other high-volume fraud targets