The Application of Artificial Neural Networks in Financial Risk Assessment: A Methodical Approach

This study explores the use of artificial neural networks (ANN) in finance, where they excel in risk assessment. An overall overview is presented where the basic principles of artificial neural networks are defined. As well as the characteristics of these networks including how to solve complex problems that cannot be solved by classical mathematical techniques. This makes them well suited to their applications in the field of financial analysis and management. The study reveals the key elements for successful ANN adoption using a neural network model with five input factors to the analysis system (wide availability of top-notch data, strong and reliable technology setup, training qualified personnel, transparent moral principles and tactical execution strategy). The output of the system is the determination to what extent companies can apply this tool, helping to identify areas for improvement and facilitating the right choices. This methodical strategy offers a structured way to understand and apply ANN in today's business systems, ensuring the best use of this tool.