Detecting and Preventing Identity Fraud with Machine Learning: Managing Potentials and Perils

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Description

The number of cyberattacks and fraudulent acts has been proliferating rapidly. Fraudsters have successfully made their way to access a victim’s financial resources through different schemes like stealing a victim’s personally identifiable information (PII).

Because failure to have a robust data solution can be costly and risky for the user and business alike, companies must adopt an identity fraud prevention tool to keep their platforms safe and their users verified. Leveraging a data science and machine learning model that could streamline the authentication of customer-provided data and predict fraudulent users are also crucial.

In this LIVE Webcast, Data Science Manager Dusan Bosnjakovic (TeleSign Corporation) and Quantitative Analytics Specialist Lian Yu (Wells Fargo) will provide the audience with an in-depth discussion of identity fraud detection and prevention with machine learning. Speakers will offer practical tips and strategies to help businesses while avoiding drawbacks and unwanted costs.

Key issues include:

  • Identity Fraud: Trends and Statistics
  • Leveraging Machine Learning in Financial Institutions
  • Identifying Potential Identity Fraud with Machine Learning
  • Best Fraud Defense Techniques
  • Red Flags