BUSINESS VALUE
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.
Statistics and machine learning are used to identify abnormal behavior and new fraud schemes.
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.
THE SOLUTION CAN BE DELIVERED IN TWO OPTIONS:
- BI.ZONE Fraud Prevention is installed inside the customer’s perimeter
- Licencing: contingent on the channels and number of clients
- BI.ZONE Fraud Prevention is installed in the cloud infrastructure
- Licencing: contingent on the number of transactions
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
STATISTICS
is a mean amount of money theft from legal entities in Russia in 2018
is a loss caused by Buhtrap cybercriminal group in the year of 2015–2016
is usually stolen from a compromised mobile device per day
HOW BFP WORKS
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.
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.
