Anomaly detection is a machine learning technique used to identify unusual or anomalous patterns in data. The goal of anomaly detection is to find observations that deviate significantly from normal or expected behaviour.
In other words, anomaly detection is a technique that allows artificial intelligence systems to identify data that does not conform to expected patterns, which can be very useful in detecting fraud, security intrusions, system failures, and other unexpected events that may have a negative impact on the performance or security of a system.
Anomaly detection is a widely used technique in industry and can be applied to a variety of fields, such as critical infrastructure monitoring, disease detection in the medical field, error detection in industrial production, and financial data analysis.
Normally the acronym NPLs (Non Performing Loans) is used in the financial sector and is a reality in Spanish banks as well as in banks [...].
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