Machine learning has contributed enough to solve complex problems in the domain of natural language processing, image and speech recognition, etc. Recently, Deep learning or Neural Networks has emerged as one the most prominent and powerful methods for learning tasks. The financial sector is also not left untouched by the current wave of Machine learning and artificial intelligence has really benefited the financial sector.
Right now, the financial market comprises humans and machines. There are machines which are trading billions of dollars every day in a response time measured in microseconds popularly known as High-Frequency Trading. Facts say that nearly 73% of everyday trading is executed by machines. Every major financial firm is investing in algorithmic trading because the level and volume of trade carried out by these machines is out of human bounds to process and execute. These machines have been made capable of learning from past financial databases to gather the insights and intelligence. Now, as the market is full with such artificial trading systems, the market is shaping into a complex manner. These all machines compete with each other in real-time for trading.
If we look from the perspective of Machine Learning, regulatory bodies are conducting active research in the field of stock trading, portfolio optimisation, etc. Researchers are constantly trying to learn more and more information from the large volume of data available. A bit older models used only the numerical data available, but today’s system takes into account the financial news before it even reaches the humans and infers outcomes based on the news.
Therefore in future, Machine Learning is going to be a key factor in the financial sector.
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