The financial services industry is fundamentally an information processing industry. An investment fund processes information in order to evaluate investments, an insurance company processes information to price their insurances, and retail bank processes information in order to decide which products to offer to customers. It is, therefore, not a surprise that the financial industry was an early adopter of computers.
Machine learning skills are essential for anybody working in financial data analysis. You can use machine learning to automate manual tasks, identify and address systemic bias, and find new insights and patterns hidden in available data.
Machine Learning for Finance shows you how to build machine learning models for use in financial services organizations.
Let’s see what Jannes has to say about using machine learning and AI in the field of Finance:
1. How is machine learning used in finance? How is AI used in finance and banking?
There are many applications that usually revolve around either forecasting or information extraction. Financial forecasting is as old as the industry itself. Analysts try to forecast stock movements or even specific line items to make recommendations to their customers. This is currently done with models that are quite restricted, run on a lot of assumptions, and require ...
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