Sigma Fraud Score

The Sigma Fraud Score is a statistical measure used to identify potential fraudulent activities or behavior within a given data set. It quantifies the deviation of observed patterns or transactions from the expected or normal behavior, indicating the likelihood of fraudulent actions.

The score is calculated using a statistical method called the z-score, which measures the number of standard deviations a particular data point deviates from the mean. In the case of fraud detection, the Sigma Fraud Score compares the observed values of specific variables (such as transaction amounts, time, or frequency) against the expected values. If the deviation is significant, indicating an anomaly, a higher Sigma Fraud Score is assigned, suggesting a higher likelihood of fraudulent activity. This helps organizations prioritize their efforts and focus on the transactions or patterns that require further investigation or intervention.

The Sigma Fraud Score can be customized based on the organization’s specific needs and domain expertise by incorporating various algorithms and models. It serves as a powerful tool in fraud detection and prevention, allowing businesses to allocate their resources effectively and proactively identify potential fraudulent behavior before it causes significant harm.

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