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What is Data analysis for fraud detection?

Data analysis for fraud detection is the application of analytical techniques, including machine learning and statistical modeling, to identify fraudulent activities in financial transactions, insurance claims, and cybersecurity. It detects anomalies, suspicious behavior, and risk patterns to prevent fraud and minimize financial losses.

Data theft
Data theft is the unauthorized access, copying, or exfiltration of sensitive data, often for malicious purposes such as financial fraud, identity theft, or corporate espionage. It occurs through cyberattacks, insider threats, or security vulnerabilities, making data protection measures such as encryption and access control essential.
Text Mining
Text mining refers to the process of extracting valuable insights from textual data using NLP, machine learning, and analytics techniques. It is applied in research, business intelligence, and automated content classification.
Speech Recognition
Speech recognition refers to the technology that converts spoken language into text using AI and linguistic models. It powers virtual assistants, transcription services, and voice-activated systems in various industries.

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