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AuDaScience Fraud BRAINs™

Detects internal frauds and embezzlement

The AuDaScience Fraud BRAINs is an advanced machine learning based application, capable of revealing data security, data leakage and internal fraud threats that have no prior records or signature. It reveals what you don’t know that you don’t know. By sensing thin anomalies in users’ behavior with completely legitimate characteristics, the AuDaScience Fraud BRAINs alerts fraud and data leakage when other systems remain silent.

Main features

  • R based, Big-data, unsupervised learning engine
  • Not based on pre-programmed rules
  • Detects legitimate yet abnormal employee behaviors and events
  • Complements legacy financial and data anti-fraud system
  • Intuitive GUI for quick deployment by security, auditing and risk management teams

To comply with anti-fraud and information security regulations and with internal auditing, organizations and enterprises today implement various data surveillance and monitoring tools. These tools constantly monitor interactions and transactions between employees, customers, automatic processes etc. These processes are part of any organization’s interaction with its business environment and it covers front line representatives, support and sales desks, cashiers, traders, purchasing managers etc. The analysis of these processes and events is based on accumulated experience and assumptions, summed up to a set of predefined rules that clearly classify events as legitimate or suspicious.

Unfortunately, the wrongdoer is already one step ahead. The scam tactics are discovered when it is already too late and damage is irreversible. This state calls for a system that sets its rules dynamically, independent of human assumptions, programming and ruling.

By using predictive analytics processes, sophisticated machine learning and unsupervised prediction techniques Fraud BRAINs is finding qualitative anomalies in employee’s behavior. It constantly monitors and aligns each event to thousands individual characteristics, user segments, periodical routines and many other variants and classifiers, to alert on developing security issues in advance.

Invaluable opportunities for improving the organization’s immunity to fraudulent behavior hide in the organization’s Big Data - Fraud BRAINs puts them to work.
The result is highly accurate prediction of deviations that require immediate attention and further investigation.

Typical use cases:

  • Leak prevention of classified and sensitive information
  • Trade room embezzlement detection
  • Retail store cashiers frauds
  • Financial institutions tellers and clerks
  • Call and service center operators
  • Sales and purchasing managers
  • Accounts payable/receivable