BI.ZONE Fraud Prevention (BFP)

А platform for assessing and blocking suspicious transactions

Check payment transactions in the real time

Prevent fraudulent operations

Manage risks and incidents

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STATISTICS

$13500
is a mean amount of money theft from legal entities in Russia in 2018

$40M
is a loss caused by Buhtrap cybercriminal group in the year of 2015–2016

$150
is usually stolen from a compromised mobile device per day

The solution can be delivered in two options:

On-premise

  • BI.ZONE Fraud Prevention is installed inside the customer’s perimeter
  • Licencing: contingent on the channels and number of clients

In-cloud

  • BI.ZONE Fraud Prevention is installed in the cloud infrastructure
  • Licencing: contingent on the number of transactions

BUSINESS VALUE

Extensive expertise

Access tо the most extensive expertise and black lists of fraudulent companies and persons available.

Multi-channel monitoring

Protects payments in differnet channels such as online payments of private and legal persons. Enables multi-channel anti-fraud monitoring.

Powered by cutting edge and reliable technologies

Statistics and machine learning are used to identify abnormal behavior and new fraud schemes.

Cost-effective solution

BI.ZONE Fraud Prevention solution allows you to reduce costs spent on an effective anti-fraud system and almost completely exclude capital expenditures and lower operational costs.

Transaction analysis

A client conducts a transaction (for example, tries to log in or to make a payment). If the response rule is configured for this transaction, then the transaction is checked by BFP. BFP also collects information about client’s behavior and device. All the collected information is used to build the client’s profile.

HOW BFP WORKS

Risk scoring

BFP uses approaches based on rules and models, and assesses transactions’ risk and makes a verdict: allow, review or deny. Then, BFP returns the verdict back to your system.

Transaction approval or rejection

Depending on BFP verdict, your system could either perform, reject or stop the transaction, and form a notice to the client.

The client, in ints tern, calls to your contact center and confirms the transaction. Based on the communication with the client, the contact center employee marks the transaction as legitimate or fraudulent.

Data intelligence and machine learning

The results of transactions processing and incidents’ investigations are sent to BFP for the model training. Every day, according to these data, BFP recalculates the weights in the models, self-learns and adjusts its procedures. The risk system daily receives information about cyberthreats from banks and BI.ZONE response team.

DEMO

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