Machine Learning and Predictive Analytics are not the same, the two approach a problem in different ways.

Because it is a technology that gets smarter with use, machine learning is the face of artificial intelligence. Machine learning can be employed independently and relies on algorithms that are fed data and permitted to process it alone. Without being programmed, ML models form their own hypotheses, test them, and develop on their own.

The best application of machine learning in the insurance industry is claim processing. By prioritising claims using an app or a virtual assistant, ML has improved the process. To spot any instances of outliers or even fraud, it can track and spot patterns in claims. It uses internal dashboards to alert brokers to investigate when a potential fraud is found.

ML is just one tool in the predictive analytics toolbox, which also includes data mining and predictive modeling. In order to predict future results, it uses both historical and recent data. For instance, what customer behaviours might be likely to appear in various circumstances or even potential changes in the market.

https://www.simplesolve.com/blog/predictive-analytics-in-insurance