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The finance firms are using machine learning to improve their productivity by eliminating manual and repetitive work.
FREMONT, CA: The speed of disruptive technologies such as Artificial Intelligence (AI) and Machine Learning (ML) in Finance has been rapidly accelerating in recent years due to improved software and hardware. In particular, the finance sector has seen a steep increase in the use of machine learning technologies to promote better results for customers and businesses.
Machine Learning in Finance
Currently, the primary users of AI and ML in finance were only hedge funds, but in recent years, ML applications have expanded to many other fields, like banks, fintech, regulators, and insurance companies, to name a few.
The various use cases of Artificial Intelligence and Machine Learning have a significant effect on the financial sector, from the acceleration of the underwriting process, portfolio structure and optimization, model validation, robo-advising, business impact analysis to providing different credit reporting methods.
In order to automate time-consuming, mundane processes, and deliver a much more streamlined and personalized customer experience, the finance industry, like banks, trading, and fintech companies, are increasingly implementing machine algorithms.
Machine Learning Use Cases in Finance
Here are a few instances where machine learning algorithms in the financial sector can/are used.
To boost network security dramatically, machine learning algorithms can be used. Data scientists are always working on training systems to identify signals like money laundering methods that can be avoided by financial monitoring. The future holds a strong potential for machine learning technology to power the most sophisticated networks for cybersecurity.
Making Investment Predictions
Compared to conventional investment models, the machine-learning-enabled technologies offer advanced market insights so that fund managers can detect specific market changes easily.
Process Automation
Machine Learning powered systems allow finance companies to eliminate manual work by automating repetitive tasks for improved business performance through intelligent process automation. Some examples of process automation in finance using machine learning are chatbots, paperwork automation, and employee training gamification. This helps finance firms to enhance their customer experience, reduce costs, and scale up their services.