Machine Learning for Monitoring Risks

Businesses face an ever-growing list of risks. Over the last decade, data security, and more recently data privacy, have been high on the list. In the digital age, where every business, process and task relies on data, the challenge with managing risk is the sheer volume and frequency of data consumption. In the sphere of risk, computers excel at monitoring changes in data and matching profiled risks to data they monitor.

The strength of computers to perform this risk monitoring role lays in their ability to process large volumes of data, and to operate 24/7. Humans don’t have the capacity to economically perform these mundane data processing tasks, neither would they want to. Computers have always been seen to be good at data processing, but less good at making decisions by themselves.

In the data security risk monitoring role, computers perform a critical role today in the prevention of data breaches by auditing thousands of user logins and behaviors every day, picking out those events that are untypical or known to offer a higher degree of risk.