Real-time, long-term profiling
Brighterion’s profiling solution creates hundreds of new features on the fly that are used for scoring. The features generated are derived fields such as grouping, mappings, sets, expressions and more, creating real-time, long-term profiles that track entity behavior.
Brighterion’s profiling uses proprietary algorithms that are database independent and can profile any entity in real time: merchant, agreement, outlet, terminal, merchant segmentations and others. It’ll allow you to monitor a wide variety of merchant data such as production purchasing patterns, suspicious changes in activities, number of transactions over a window of time, entity transaction frequency, comparison of transaction versus authorization to detect anomalies, and trends in the number of chargebacks over time. There is no limit to the number of profiling criteria that can be defined.
- Real-time profiling – The time window for aggregation can be anywhere from several seconds to several weeks. The counters are updated in real time as transactions are processed
- Long-term profiling – Profile the same entities over a long time period, from a few months to several years. Long-term profiling is used to establish the baseline behaviors for entities, such as users, IP addresses, and devices. At any time, a window can be defined for aggregation and the user can specify the refresh rate to automatically update the profiling values
- Recursive profiling – Gain a full view of user behavior by being able to track and monitor the normal behavior of an entity. An example would be to compute the maximum number of times a user logs on to online banking in a week
- Geo-location profiling – Compute the distance in real time between two zip codes, IP addresses, or other geo-location data to detect abnormal behaviors
- Multidimensional profiling – Profile multiple entity interactions to link suspicious behaviors together and identify unknown entity links
- Peer comparison profiling – Compare entities, such as merchants, to their peers in real time to detect any suspicious activity