With the trend towards increasing computational resources and larger datasets, the application of machine learning (ML) in finance has gained attraction. Financial Institutions are interested in how and where ML models can be of added value in their business model.
According to Moore’s law, computing power doubles up each two years. This performance increase in computing power makes machine learning increasingly efficient each year, and widely applicable. But does this also apply to credit risk issues?
Machine Learning for Financial Institutions Terms like big data, machine learning and data science are used in many fields of business. In recent years, also financial institutions have shown increasing interest in these subjects. The expectations are that the machine learning can assist with things such as compliance, credit underwriting, client communication and risk analysis. […]