Fraud Prevention

Overview

Fraud Prevention provides transaction and session analysis enhanced with threat intelligence from a wide range of sources. The product would benefit both banking and online services.

Find out about Fraud Prevention features:

Banking systems

Online services

Finds cross‑channel fraud schemes via instant monitoring of remote banking and card transactions

Identifies criminals who create numerous accounts and the devices they use

Helps counteract emerging schemes based on fraud analytics from large organizations

Detects suspicious activities involving accounts

Simplifies authorization for legitimate users with RBA technology

Components

Payment operations protection module

Identifies and blocks illegitimate financial transactions through a rule‑based approach and detection of abnormal user behavior. The module supports various payment channels and enables cross‑channel monitoring

Flexible rule management

The system allows you to configure rules for detecting and responding to suspicious events. You can also create reference books and additional parameters for future rules

Operation in real time

The module automatically blocks fraudulent transactions with a response time as low as 0.1 seconds

Machine learning

User profiling helps reduce false positives and uncover new fraud schemes

In-depth session analysis and global profiling module

Processes over 300 parameters in real time to find anomalies. Creates global user profiles for a more effective and accurate detection of fraud

Device profiling

Helps determine whether a device is used legitimately, including through a global reputation database

User profiling

Analyzes and accumulates the main parameters recorded during online‑service sessions

Detection

Identifies the signs of potential fraud for a detailed analysis. The indicators include remote connections, the use of VPN or Tor, spoofing of banking details, bot activity, and 30+ other criteria

How it works

1. The user performs an action—logs in to the system or makes a payment

2. If a response rule is set for the action, your automated systems send it to Fraud Prevention for analysis and a verdict. They also send information about the customer’s activity along with an extended set of user data collected by SDK or JS. This information is required for user and device profiling

3. Fraud Prevention assesses the risk of an operation by applying a rule-based approach to input data and a model-based approach that uses mathematical models and machine learning algorithms. This involves all the accumulated information on the user’s behavior in the channels: the platform detects deviations from typical patterns

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4. Based on the risk assessment, Fraud Prevention produces the verdict to allow, suspend, or block the action. Then the platform returns the verdict to your automated systems

5. Depending on the verdict, the automated systems perform, block, or suspend the operation and inform the user accordingly

6. If the operation is blocked or suspended, an incident is created in the system. A bank officer verifies the information and determines whether the operation is fraudulent or genuine. Some cases would require a call to the user: either from a fraud monitoring operator or a bot assistant

7. The results of operations processing and incident investigations continuously enrich our mathematical models

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Fraud Prevention

Overview

Components

How it works

Ask our experts how to prevent fraud in banking systems

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