Artificial neural networks in finance have recently gained popularity due to their ability to better handle uncertainty compared to expert systems. Neural networks for financial forecasting can be used to effectively predict future events, based on past data. Since an artificial neural network mimics the human brain’s biological neural network, artificial neural networks in finance consist of many interconnected processors known as neurons. It consists of an input layer, one or more hidden layers, and an output layer. These layers combine to perform many essential financial functions including forecasting, evaluation, and search.
Neural Networks in Finance
So, how can you use neural networks in finance to improve your business predictions and make your financial business more successful?
While a neural network for financial forecasting is a common misconception, neural networks in finance can analyze data and help you uncover opportunities. With a neural network trading strategy, you can easily make better trade decisions based on thoroughly analyzed data you otherwise wouldn’t have access to with traditional analysis methods. Neural network trading is a next-generation tool that offers great potential to detect subtle, non-linear inter-dependencies and patterns that other methods of analysis are unable to uncover, giving you better-informed decisions and the ability to uncover more opportunities.
Loan Application Evaluation
Another use for neural networks in finance is the ability to more accurately evaluate loan applications. When you use neural networks to underwire a loan and decide whether to approve or reject the application, you will minimize the failure rate of your approved loans and maximize the returns on the loans you issue. When you use neural networks in finance, the failure rate of loans approved will be much lower than that of even your best traditional methods. Neural networks in finance can be used to analyze past failures and make current decisions based on past experience.
To remain profitable, credit card companies must continue to obtain ideal customers who spend a lot using their credit card. Since per card revenue is crucial for credit card companies, using neural networks in finance is essential for credit card businesses to remain profitable. By using neural networks in finance, credit card companies can better determine which customers to obtain and eliminate instances in which credit cards are issued to customers who have no need for them. Using neural networks in finance allows for more meaningful questions to be provided on credit card applications to better identify ideal customers and eliminate customers who will not make the business profitable.
A neural network in finance is a next-generation tool that is helping financial companies of all types remain profitable and gain added business value. Does your financial institution use neural networks for financial forecasting or have a neural network trading strategy in place? If, not, now is the time to adopt this next-generation tool to improve your business functions.