Apply machine learning to financial risk management - IBM Code

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Financial institutions need to continually weigh the risks of their transactions, and they determine their risk level through credit scoring. Leading up to the 2008-09 financial crisis, almost all large banks used credit scoring models based on statistical theories; that crisis, largely brought about by underestimating risk, proved the need for better accuracy in their scoring. The combination of increased requirements and the development of advanced new technologies has given rise to a new era: credit scoring using machine learning. Machine Learning for IBM z/OS gives organizations the ability to quickly ingest and transform data. They can now create, deploy, and manage high quality self-learning behavioral models, using large corporate data sets residing on IBM Z.

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