Today, machine learning in finance has more uses than before! Finance professionals are using machine learning through banking apps, chatbots, and search engines. The consumption is high in volume and presents accurate historical records. From approving loans, credit scores, looking after assets, and managing risks, machine learning is an integral part of the financial ecosystem. Machine Learning, which is interchangeably called Artificial Intelligence, is being actively used in the below applications.
You must have come across the term ‘Robo-advisor’ in portfolio management. This term was not known five years back but now it creates algorithms to create a financial portfolio with minimal risk. Many investors today rely on Algorithmic trading which is nothing but complex machine learning systems to make fast trading decisions. Most financial institutions are not admitting openly their AI approach for trading, but it is said that machine learning is playing an important role in their trading process. Machine learning is also pivotal in fraud detection. It detects unique activities and flags them to the security team. ML is used heavily in social media, news analysis and to predict stock markets. Previously, fraud detection systems relied heavily on a complex set of rules, but modern fraud detection contains less risk.
Username, password, or fingerprints are used in the banking system as these methods of authentication are very reliable. In addition to anomaly-detection applications, facial recognition, voice recognition, and biometric data will be provided to all the account holders and will make these methods more robust. Machine Learning is helping the financial institutions to improve their customer service like instead of having a monotonous conversation like, “Hey! how can we help you?” the chatbot is answering complex questions like “what were my expenses last month?” ML has aimed to do more advancement in the field of finance in the next five years.
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