Throughout the past few decades, there has been a dramatic surge in the currency market. The adjustments show a vital role in balancing the market’s characteristics. As a result, accurate change price forecasting is essential to improve the success rate of many businesses and fund managers. Despite the fact that the market is renowned for its erratic behaviour and volatility, there are organizations like Agencies, Banks, and others. In order to estimate the extraneous interchange rate of the dollar against the rupee by a high degree of accurateness, we used three distinct types of methodologies in this article. This research uses three different types of neural network models: ANNs (Artificial Neural Networks), LSTMs (Long Short-Term Memory Networks), and GRUs (Gated Recurring Units). The results depict that GRUs model is out performing the other two models.