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Fraud DetectionToday’s fraud control applications are based on documenting the problem and defining expert rules to stop it. Given the volume and the dynamics of fraud, this method is not effective. POINTER provides a pro-active approach to immediately identify fraud by understanding the source of the transaction as not a “typical” one from the user.

Less fraud and less false alerts

Intelligent Technology

POINTER uses a unique mathematical model and sophisticated data mining techniques to create a dynamic Personal Symbolic Vector.  Auto-learning techniques ensure that the system can incorporate realistic changes in behavior over time. This capability ensures that the user profile is always up to date and that the latest expert rules can be incorporated to detect possible fraud.

  • The system learns without human intervention.
  • POINTER supports and provides the required facilities to enable better risk management by monitoring risk of fraud.

Less Cost

POINTER reduces dramatically the amount of false alerts requiring less research time by personnel and improving customer service at the same time. These parameters can be fine-tuned by the institution to ensure best balance.

  • POINTER reduces costs and improves the effectiveness of fraud monitors.
  • POINTER visual screens with color coded alerts improve personnel productivity.
  • Reduces the number of alerts.

More Effectiveness

POINTER detection mechanism will highlight alarms according to their fraud status probability ensuring that fraudulent transactions can be stopped sooner, thereby reducing the loss to the institution.

  • POINTER allows workgroup alerts improving team work.
  • Alerts are monitored by account and by number of probable fraud transactions.
  • POINTER look and feel is driven by the analysts who can switch the information around at will.

Immediate Detection

Thanks to the technology around the Personal Symbolic Vector (a unique mathematical model) POINTER unifies the knowledge around fraud patterns, around typical user behavior and sector knowledge with expert rules. All of this with a solution that learns systematically from your every day transactions.
POINTER takes this learning capability to generate real-time alerts based on probabilities to assist fraud detection.

Personal Symbolic Vector

This technology, mathematically describes the behavior patterns of a user taking into account the historical transactions.
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With this technology, thousands of transactions can be monitored on-line with the objective of separating atypical ones for this user; which will be the ones that significantly deviate from the standard mean behavior.