This work predicts the nature of currency price movements using SOM neural networks and particle swarm optimization, allowing all parties take corrective actions. Artificial neural networks are commonly utilized in financial and insurance purposes. In order to predict insolvency, artificial neural networks are used. Back propagation networks and the SelfOrganizing Map (SOM) neural network of the banking sectors are used as examples of (un)supervised artificial neural networks, in the same order. The use of the particle swarm optimization PSO and artificial neural networks methodologies for the prediction of the financial distress based on selected financial ratios demonstrate the network's enable us to see the patterns that correspond to the bank's financial distress.