Main Reference PaperCost-sensitive payment card fraud detection based on dynamic random forest and k-nearest neighbors, Expert Systems With Applications, 2018 [R]
  • In payment card fraud detection, a similarity measurement on basis of transaction time and k-nearest neighbors (KNN) algorithm is used to determine the similarity between a cardholder’s incoming transaction and past transactions. In the next stage, the dynamic random forest algorithm is employed in initial fraud detection, and the minimum risk model is applied in cost-sensitive fraud detection.

Description
  • In payment card fraud detection, a similarity measurement on basis of transaction time and k-nearest neighbors (KNN) algorithm is used to determine the similarity between a cardholder’s incoming transaction and past transactions. In the next stage, the dynamic random forest algorithm is employed in initial fraud detection, and the minimum risk model is applied in cost-sensitive fraud detection.

  • To predict the fraudulent transactions.

  • To improve the classification accuracy.

Aim & Objectives
  • To predict the fraudulent transactions.

  • To improve the classification accuracy.

  • The dataset is collected for different fraud labels and analyzes the differences in the fraudulent behaviors observed in various types of frauds.

Contribution
  • The dataset is collected for different fraud labels and analyzes the differences in the fraudulent behaviors observed in various types of frauds.

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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