title: ÐÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ Ð´Ð»Ñ Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð¼Ð¾ÑÐµÐ½Ð½Ð¸ÑÐµÑÐºÐ¸Ñ Ð±Ð°Ð½ÐºÐ¾Ð²ÑÐºÐ¸Ñ ÑÑÐ°Ð½Ð·Ð°ÐºÑÐ¸Ð¹ Ñ Ð±Ð°Ð½ÐºÐ¾Ð²ÑÐºÐ¸Ð¼Ð¸ ÐºÐ°ÑÑÐ°Ð¼Ð¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Neural network to detect fraudulent bank card transactions
Creators: name: ÐÐ»Ð°Ð´ÑÐ½, ÐÐ¸ÐºÐ¸ÑÐ°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2019
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
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description: ÐÐ±ÑÐµÐºÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ Ð¸Ð´ÐµÐ½ÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¼Ð¾ÑÐµÐ½Ð½Ð¸ÑÐµÑÐºÐ¸Ñ ÑÑÐ°Ð½Ð·Ð°ÐºÑÐ¸Ð¹ Ñ ÐºÑÐµÐ´Ð¸ÑÐ½ÑÐ¼Ð¸ ÐºÐ°ÑÑÐ°Ð¼Ð¸. ÐÑÐ¸ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð±ÑÐ»Ð¸ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐµ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¸ Ð¸ ÑÑÐµÐ¹Ð¼Ð²Ð¾ÑÐºÐ¸ Ð´Ð»Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ (Tensorflow, Keras, Sklearn, Imblearn, Pandas). ÐÑÐ»Ð¸ Ð¸Ð·ÑÑÐµÐ½Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¿Ð¾ ÑÐ°Ð±Ð¾ÑÐµ Ñ Ð½ÐµÑÐ±Ð°Ð»Ð°Ð½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐ¼Ð¸ Ð½Ð°Ð±Ð¾ÑÐ°Ð¼Ð¸ Ð´Ð°Ð½Ð½ÑÑ, ÑÐµÑÐ½Ð¸ÐºÐ¸ Ð¿Ð¾ Ð´Ð¸ÑÐºÑÐµÑÐ¸Ð·Ð°ÑÐ¸Ð¸ Ð´Ð°Ð½Ð½ÑÑ Ð½Ð°Ð±Ð¾ÑÐ¾Ð², Ð¼ÐµÑÐ¾Ð´Ñ Ð¿Ð¾ Ð½Ð°ÑÐ¾Ð¶Ð´ÐµÐ½Ð¸Ñ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¸ Ð¼ÐµÐ¶Ð´Ñ Ð´Ð°Ð½Ð½ÑÐ¼Ð¸, Ð¸Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¸ Ð¾ÑÑÐµÑÐµÐ½Ð¸Ðµ Â«ÑÐºÑÑÑÐµÐ¼Ð°Ð»ÑÐ½ÑÑ Ð²ÑÐ±ÑÐ¾ÑÐ¾Ð²Â» Ð¼ÐµÐ¶Ð´Ñ Ð²Ð·Ð°Ð¸Ð¼Ð¾ÑÐ²ÑÐ·Ð°Ð½Ð½ÑÑ Ð²ÐµÐ»Ð¸ÑÐ¸Ð½. ÐÐ· Ð¼Ð½Ð¾Ð³Ð¾Ð¾Ð±ÑÐ°Ð·Ð¸Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð² Ð½Ð°ÑÑÐ¾ÑÑÐµÐµ Ð²ÑÐµÐ¼Ñ ÑÑÐµÐ¹Ð¼Ð²Ð¾ÑÐºÐ¾Ð² Ð´Ð»Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð¸ ÑÑÐµÐ½Ð¸ÑÐ¾Ð²ÐºÐ¸ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, Ð±ÑÐ» Ð²ÑÐ±ÑÐ°Ð½ Keras, Ð¾ÑÐ²ÐµÑÐ°ÑÑÐ¸Ð¹ Ð²ÑÐµÐ¼ ÑÑÐµÐ±Ð¾Ð²Ð°Ð½Ð¸ÑÐ¼ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸. ÐÑÐ»Ð¸ Ð²ÑÐ±ÑÐ°Ð½Ñ ÑÐµÑÑÑÐµ ÑÐ°Ð·Ð½ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð´Ð°Ð½Ð½ÑÑ Ð¼Ð¾Ð´ÐµÐ»Ð¸. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð¼ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð½Ð° ÑÐ·ÑÐºÐµ Python 3.5 Ñ ÑÐ¾ÑÐ½Ð¾ÑÑÑÑ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ Ð¼Ð¾ÑÐµÐ½Ð½Ð¸ÑÐµÑÐºÐ¸Ñ Ð¸ Ð½Ðµ Ð¼Ð¾ÑÐµÐ½Ð½Ð¸ÑÐµÑÐºÐ¸Ñ ÑÑÐ°Ð½Ð·Ð°ÐºÑÐ¸Ð¹ Ñ ÐºÑÐµÐ´Ð¸ÑÐ½ÑÐ¼Ð¸ ÐºÐ°ÑÑÐ°Ð¼Ð¸ Ð² 99%, Ð´Ð°Ð½Ð½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¼Ð¾Ð¶ÐµÑ Ð±ÑÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð° Ð² Ð²Ð¸Ð´Ðµ ÑÐ¸Ð»ÑÑÑÐ° Ð¿ÑÐ¸ Ð¾ÑÑÑÐµÑÑÐ²Ð»ÐµÐ½Ð¸Ð¸ ÑÑÐ°Ð½Ð·Ð°ÐºÑÐ¸Ð¹ Ð² Ð²Ð¸Ð´Ðµ Rest Ð¸Ð»Ð¸ Soap Ð²ÐµÐ±-ÑÐµÑÐ²Ð¸ÑÐ°.
description: Neural network, machine learning, banking transactions, credit card fraud. The object of the research is the development of a neural network model for identifying fraudulent credit card transactions. When creating a neural network, software libraries and frameworks for developing neural network models based on machine learning algorithms (Tensorflow, Keras, Sklearn, Imblearn, Pandas) were considered. Algorithms for working with unbalanced data sets, techniques for sampling data sets, methods for finding the correlation between data, their classification and cutting off âextreme emissionsâ between interrelated values ââwere studied. From the variety of currently existing frameworks for creating and training a neural network model, Keras was selected to meet all the development requirements. Four different algorithms were chosen to classify the model data. The result of this work is the developed model of the neural network in Python 3.5 with the accuracy of predicting fraudulent and non-fraudulent credit card transactions at 99%, this model can be used as a filter when performing transactions in the form of a Rest or Soap web service.