Anomaly detection in transactional data

Intelligent measures for fraud and money laundering prevention


Customers or bank employees involved in Money laundering and fraud affect seriously banks´ reputation and results. Thanks to Big Data and Machine Learning algorithms, early detection is increasingly more efficient (minimizing false positives).

Fraud in online bank, insurance, commercial transactions or identity cause millionaire losses that could be avoided with Artificial Intelligence. On the other hand, money laundering causes a legal risk problem to entities that must keep alert to comply with due diligence regulations.

Intelligence Observation Systems (IOS) emulate through artificial intelligence the way a person observes, in other words, these systems can compete with an expert´s analytical capacity. IOS provide an innovative way to combine the expert´s knowledge with ML techniques such as classifiers, neural networks and anomalies detectors.

It is specially designed to work in real time and with large volume of data, which allows to learn from data in real time by updating behavior patterns previously defined.

IOS stand out for their early detection capacity in the following cases:

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