Fraud Detection

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Did you know? Businesses lose over 5% of revenue annually to fraud, making real-time fraud detection essential.

1. What is fraud detection?

Fraud detection is the process of identifying and preventing deceptive or illegal activities, such as identity theft, financial fraud, or cyberattacks. It uses rules, data analysis, and machine learning to spot suspicious patterns in real time.

2. What is an example of a fraud detection model?

A common fraud detection model is a machine learning classifier trained on historical transaction data.
Example: A bank uses a logistic regression model to flag unusual spending behavior, such as a sudden high-value purchase in a foreign country, as potential fraud.

3. Why is detecting fraud important?

Detecting fraud is critical because it:

• Protects customer trust and financial assets
  
• Reduces operational losses and chargebacks
  
• Ensures regulatory compliance
  
• Prevents reputational damage

Early detection helps businesses act before losses escalate.

Detect and stop fraud early using compliance, AI and real time monitoring