5 Ways Neural Networks and AI with Change Banking pdf-converted

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MasterCard organizations are continually chasing for the best clients for their organizations to guarantee that they get supportable income.

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5 Ways Neural Networks and AI with Change Banking The artificial neural network is like biological neural networks within the human brain. They are made of interconnected processes. The neural network model develops algorithms which can be used to model intricate patterns. Some applications where they can be used are risk profiling credit scoring and trading. 1-Consideration of Loan Applications To approve a loan application the banks try to reduce the failure rate of the loan application and ensure that they get the best returns on loan issued. It’s why more and more banks are now turning to use the latest neural network model to help them in deciding on granting the loan application. It usually works on the analysis of past failures and

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making the decisions that are based on past experiences. The results are 85 to 90 per cent accuracy in the decision making and that’s a lot of improvement. 2-Finding Best Customers for Credit Card Companies Credit card companies are always hunting for the best customers for their business to ensure that they get sustainable revenue. If the customer isn’t making adequate use of the card the profit of the bank would be impacted severely and the costs would exceed revenue. It will result in a loss-making business. More and more credit card providers are using neural networks to identify the best customer who will generate sufficient revenue after looking at their credit card usage habits. 3-Stock Market Predictions This new tech has found its use in the prediction of stock market indices and value of individual stocks. It uses historical data and different parameters to make these predictions. The accuracy is significantly enhanced with the use of hidden layers and the inclusion of more training variables. 4-Fraud Detection The ANNs can take multiple inputs process them to deduce hidden as well as close relationships. ANN can play a significant role in image and character recognition. It means more and more bank is taking advantage of ANN to detect fraud better. For instance the banks could identify whether the two signature images are from the same person. Then it is also being used to detect AML and pattern detection. Anti- money laundering refers to the procedures and the laws that are designed to stop the ways to generate income with unfair means. The money launderers through a series of steps clean the money. It may

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look like as it came from sources that are legal and is earned legitimately. The banks across the world are shifting from the use of regular software to AI-based systems which are robust and intelligent to the anti-money laundering patterns. With time these systems will become more accurate 5-Chat Bots These are automated chat systems which simulate the human chats that too without any human interventions. With the time they become intelligent and then they adapt to the user behavior and sever the need of the customer in an even better way Finally With the use of appropriate neural network model they become even more effective and intelligent. As their application is increasing more and more banks will go for them Resource Link: - http://bit.ly/2vOBMm8