Top 7 guiding principles for anomaly detection systems

Anomaly Detection Systems are built to identify and measure the root cause of error, abuse, fraud and waste. Anomaly detection also referred to as outlier or novelty detection, identifies events or observations that deviate significantly from the expected result, or a majority of the data, or do not conform to a well-defined notion of normal behavior. These are often identified as behavioural events of error, waste, abuse, or fraud.

Industries that rely on third parties to deliver complex services to end-users, ranging from health services, education, wealth management, capital markets and taxation services to franchise operations.

This environment is susceptible to error, waste, abuse, and fraud as the service deliverer, or intermediary, behave in a way inconsistent with the organization’s intention and expectations.

When designing an anomaly detection system, some guiding principles, or strategic drivers, of the design and implementation are:

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