Detection

/frɔːd dɪˈtɛkʃən/

noun — "catching sneaky transactions before they ruin your balance."

Fraud Detection is the process in information technology and cybersecurity of identifying and preventing unauthorized or deceptive activities, particularly in financial systems, e-commerce, or sensitive data environments. It relies on analyzing transaction patterns, user behavior, and system logs to flag suspicious activities before they cause losses or breaches.

Technically, Fraud Detection involves:

/əˈnɑːməli dɪˈtɛkʃən/

noun — "finding the needle in the data haystack before it ruins your day."

Anomaly Detection is a field in information technology and data science focused on identifying unusual patterns, outliers, or unexpected behaviors in datasets, systems, or network traffic. These anomalies may indicate errors, security breaches, fraud, system malfunctions, or rare but important events. Detecting anomalies helps organizations respond proactively to irregularities that could affect performance, security, or decision-making.

/ˌstɛɡəˈnæləsɪs/

noun — "detecting hidden information in media."