Fraud Detection

Fraud Detection Methods

Our methods based on machine learning algorithms will help detect and identify fraudulent and suspicious activities from within your application data.

Key Challenges

It takes time to develop plans to identify and remediate fraud detection activities. Your analysts:

  • Need data to analyze.
  • Need time to model and test corrective actions.
  • Need to develop models that are flexible, so they can be altered easily when fraudulent activities adapt.

Our Detection Support

Based on machine learning techniques:

  • Analyze and understand low level patterns.
  • Identify and help create training and testing data sets.
  • Get coverage of as much data as possible.
  • Make recommendations to update models as needed.

Fraud Detection Areas where We Will Provide Support

Application and Database Level

As transactions are created in your application systems and databases, we will create and apply:

  • Solutions using statistical and machine learning models
  • Update algorithms and fine tune them to match to deal with fraud methods, within the latest transactions.

Across Business Domain

  • Activity is monitored at the business segment level.
  • Suspicious activity patterns will be identified that are specific to the business segment within your customer base.

Business Customer Level

  • User Interactions of a particular customer will be monitored and analyzed.
  • Suspicious activity patterns at the customer level will be identified.

Business User Level

  • User Interactions of a particular account will be monitored and analyzed.
  • Suspicious activity patterns at the user account level will be identified.

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