GitHub repository: mominnawaf/creadit_card_fraud_detection_using_artifitial_neural_network_and_self_organiaing_maps
Primary language: Python
Created: 2019-03-24T06:36:35Z
Description: The credit card business has increased speedily over the last two decades. Corporations  and establishments  move components of their business or entire business, towards online services providing  e-commerce, data and communications for services for aim of permitting their customers with high potency and accessibility. Regardless of location shoppers will continue to make as they formally did “Over the Desk”. The evolution is a huge step towards potency and accessibility and profitableness of view nevertheless, it additionally has some drawbacks. The is threaten by the bigger vulnerability to threat. The matter with creating business through internet card lie within the fact that neither the card nor the user need to be present at point of sale. Thus, it is impossible for merchandiser to check weather the cardholder is real or not. Payment card fraud is major downside thought the world. Companies loose immense amount of money due to credit card fraud and fraudsters ceaselessly obtain new ways to commit unlawful activities. The good news is that frauds tends to be perpetrated to some patterns which it’s potential to sight such that the fraud. Using information from the credit card issuer, a neural network based  fraud detection system was trained on an outsize sample of tagged credit card accounts and tested on holdout account set that consider all the account activities over a resulting two months of periods. The neural network was trained on samples of fraud due to loss, stolen cards, application fraud, counterfeit fraud. As we know Artificial Neural Network works as human brain when trained properly. Yet, it is impossible for ANN to emulate human brain, both depend on small functional unit called Neuron. We have also implemented SOM for accuracy purpose. We tend to discuss the performance of the network and accuracy.