What can predictive models provide insights into, besides customer defection?

Predictive models are powerful tools used in various domains to analyze data and forecast future events or behaviors. Their primary strength lies in their ability to identify patterns and trends based on historical data. In addition to predicting customer defection—which is critical for maintaining customer retention—predictive models can also be adept at identifying potential fraudulent activities.

Fraud detection often relies on recognizing unusual patterns that deviate from established behaviors observed in historical data. By using predictive modeling techniques, organizations can effectively analyze transactions, customer behaviors, and other relevant data to isolate anomalies that may signify fraudulent activities. This proactive approach enables businesses to take preventive measures before substantial losses occur.

While the other options may involve valuable insights, they do not capture the full scope of what predictive models can achieve as effectively as potential fraud detection. Sales trends, operational efficiency, and market expansion are important facets of business intelligence, but they do not leverage the unique capabilities of predictive models in the same targeted manner as identifying fraud does.