What are the five possible risk assessments that Stripe's machine learning can assign to a charge?

The correct choice identifies the five risk assessments that Stripe's machine learning system can assign to a charge: High, Elevated, Normal, Not evaluated, and Unknown. This classification is essential for understanding the different levels of risk associated with a transaction, allowing businesses to tailor their responses based on the assessed level of fraud risk.

The "High" and "Elevated" categories indicate more significant concerns regarding potential fraud, prompting closer scrutiny or additional verification. "Normal" signifies standard transactions that carry a typical risk level. "Not evaluated" is used when a transaction hasn't undergone a risk assessment yet, whether due to an issue with the data or its timing. "Unknown" represents instances where the system lacks sufficient information to make a definitive risk assessment.

Other options feature variations in terminology that do not align with Stripe’s machine learning classifications, showing different groupings or terms that do not accurately describe the risk assessment process implemented by Stripe. Understanding this framework is crucial for effectively managing risk and enhancing transaction security.