Natural Language Processing is the process by which machines understand human language (mainly text and speech). The most common NPL techniques help summarize big amounts of data, retrieve all the relevant information from a text, and convert unstructured data into tabular data points (structured data). Along with text reading, summarization, interpretation, and translation, Natural Language Processing finds extensive use in voice recognition and chatbots. The financial industry has started using NPL techniques to analyze news, financial statements, reports, and perform sentiment analysis. Besides from being extremely time-saving, these techniques have added value and insights to predictive modeling. Major investment banks and hedge funds are currently using NPL and Machine Learning to extract precious information from market prices, financial statements, news, social media posts etc. and improve stock market predictions and Quant strategies. Along with customer care, NPL is extremely demanded for fraud detection and prevention. Through customized algorithms, machines are able to detect and classify malicious incoming phone calls or misleading financial information.