Fraud Detection in Credit Card Transactions; Using Parallel Processing of Anomalies in Big Data

Fraud Detection in Credit Card Transactions; Using Parallel Processing of Anomalies in Big Data

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In parallel to the increasing use of electronic cards, especially in the banking industry, the volume of transactions using these cards has grown rapidly.Moreover, the financial nature of these cards has led to the desirability of fraud in this area.The present study with Map Reduce approach and parallel processing, Kontekstualisasi Fungsi Bagas Godang dan Sopo Godang Sebagai Sumber Pembelajaran Sejarah Lokal applied the Kohonen neural network model to detect abnormalities in bank card transactions.For this purpose, firstly it was proposed to classify all transactions into the fraudulent and legal which showed better performance compared with other methods.

In the next step, we transformed the Kohonen model into Drivers or Pedestrians, Whose Dynamic Perceptions Are More Effective to Explain Street Vitality? A Case Study in Guangzhou the form of parallel task which demonstrated appropriate performance in terms of time; as expected to be well implemented in transactions with Big Data assumptions.