BI.ZONE Cloud Fraud Prevention
Check payment transactions in the real time
Prevent fraudulent operations
Manage risks and incidents
is a mean amount of money theft from legal entities in Russia in 2017
is a loss caused by Buhtrap cybercriminal group in the year of 2015-2016
is usually stolen from a compromised mobile device per day
Access tо the most extensive expertise and black lists of fraudulent companies and persons available.
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.
BI.ZONE Cloud 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.
Machine learning and rules
risk scoring based on machine learning
customized features for model and rules
rules export and import
events view by clients
search for similar events by clients
events view by different payment channels
profile client devices
easy integration SDK/js
collect detailed device features
use the collected data in 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 BCFP. BCFP also collects information about client's behavior and device. All the collected information is used to build the client's profile.
BCFP uses approaches based on rules and models, and assesses transactions' risk and makes a verdict: allow, review or deny. Then, BCFP returns the verdict back to your system.
Transaction approval or rejection
Depending on BCFP verdict, your system could either perform, reject or stop the transaction, and form a notice to the client.
Then, the client calls to your contact center and confirms the transaction. According to the investigation result, 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 BCFP for the model training. Every day, according to these data, BCFP 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.