What types of risk assessments can Stripe's machine learning provide for a charge?

The correct answer, which describes the risk assessments that Stripe's machine learning can provide for a charge, includes categories such as High, Elevated, Normal, Not evaluated, and Unknown. This classification system offers a nuanced approach to risk assessment, allowing for a better understanding of the potential risk associated with a transaction.

Each category serves a specific purpose: "High" indicates a significant risk level, while "Elevated" suggests a heightened but not critical risk. "Normal" reflects typical transaction behavior with expected risk levels, while "Not evaluated" signifies charges that have not yet undergone analysis. "Unknown" highlights cases where the risk status cannot be determined, possibly due to insufficient data or new patterns that the algorithm has yet to learn.

This detailed categorization helps businesses make informed decisions on how to proceed with transactions, enabling a balance between security and user experience. Other options do not encompass the wide-ranging classifications provided by Stripe’s machine learning, which is designed to support sophisticated fraud prevention strategies.