Risk and control automation
The customer challenge is that a major financial institution requires its audit departments to track and evaluate controls that help them determine their level of risk exposure. Considering that any major bank has 250,000+ controls that are mapped to risks, this was not an easy task.
A good business control clearly states who, what, when, how, and where the control is to be used. Banks often suffer due to poorly defined controls. With Cloud Pak for Data, this customer was able to train an ML model to predict the Control quality level of each written control. They used the Watson Studio service to train the model and Watson Machine Learning to deploy and operationalize the model.
The following diagram illustrates the risk and control automation component:
The featured Cloud Pak for Data services include Watson Knowledge Catalog, Watson Studio, and Watson...