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Predictive alerting is technology that is able to provide predictions of certain events or inputs. It is related to machine learning because the technology is able to learn from the data it is regularly processing and based on its learning, is able to make predictions which are actionable. The technology is used in many industries such as telecommunications, banking and finance, and defense.
Predictive alerting is the output of a computing system able to learn from the data it has been processing over a period of time. For example, the system stores and processes financial data in a large bank and a certain number of users are given conditional access to the system and each user has certain ways to access the system. If a user tries to access the system in a different way, say, with a new device, the system sets off a predictive alert.
Predictive alerting is highly useful in applications such as preventing fraudulent transactions in the banking sector or predicting customer churn in companies. Predictive alerting is different from other alerting systems such as rule-based alerting because it adapts and learns from new data sets which can be varied and complex in nature. Rule-based alerts, on the other hand, can work only based on preconfigured rules and may not be suitable for real-life scenarios.