Credit Fraud Detection with Deep Learning in Banking

Understanding Credit Card Fraud Detection


Online Shopping is a fast-growing trend. Mode of payments involving Credit Card, Debit Card and Net Banking are prone to frauds. Credit Card Fraud occurs Online as well as Offline. Hackers don’t leave a chance to steal information and breach security. Evasion can be bankruptcy, behavioral, application or theft.


Challenges for Credit Card Fraud Detection


    • Fraud Detection transactions are rare and represent a small fraction of total transactions within an organization.
    • Analyze past credit card transactions with fraud ones.


Solution Offered for Enabling Fraud Detection with Deep Learning


  • Fraud Detection Model follows Random Forest algorithm which takes hundreds of decision trees and aggregates and builds the model that to avoid overfitting due to class imbalance.
  • Analysis of at least 20-50 last transactions of the customer is done to identify an underlying pattern.
  • Python and Machine Learning used to build the model.
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