DFD prevents fraud and access with criminal intent in real time through machine learning technologies designed to detect faults and frauds during on-line payments or in case of accounts hacking, synthetic identities and organised theft groups.
The system checks the consistency of thousands of data related to the user identity in order to detect any faults in real time.
DFD uses behavioural profiling to verify each transaction and previous information in real time.
Connections between people, bank accounts and telephones are easily analysed by means of graph analysis in order to identify any suspicious activities.
Humans cannot compete with computers when it comes to querying data: artificial intelligence is able to analyse and act on patterns too complex for the human brain to identify.
Our graphical data model improves fraud detection in order to fight several financial crimes in real time, including first-party bank fraud, credit card fraud, e-commerce fraud, insurance fraud and money laundering.
As technology improves, fraudsters devise new techniques and schemes: our job is to help companies develop new techniques and strategies aimed at IT security.