What is meant by Fraud detection?
The term "Fraud Detection" refers to the methods and techniques used to identify and prevent fraudulent activities within a system or process.
Typical software functions in the area of "Fraud Detection":
- Pattern Recognition: Automated detection of unusual patterns or deviations in transaction data that may indicate potential fraud.
- Rule-based Analysis: Application of predefined rules and algorithms to examine transaction characteristics for suspicious activities.
- Machine Learning-based Analysis: Utilization of machine learning models to identify new fraud patterns based on historical data.
- Real-time Monitoring: Continuous monitoring of transactions and events in real-time to enable immediate action on suspicious activities.
- Fraud Prevention: Implementation of mechanisms and controls to prevent fraud attempts before they occur.
- Case Management: Management and tracking of fraud-related cases and investigations through the software.
- Reporting and Audit: Generation of reports on detected fraud cases and audit functions to review the effectiveness of fraud detection measures.
Examples of "Fraud Detection":
- Irregular Transaction Patterns: Identification of unusual purchases or withdrawals on bank accounts.
- Suspicious Account Access: Detection of unauthorized access to online customer accounts.
- Credit Card Fraud: Tracking unauthorized use of stolen credit card information.
- Identity Theft: Detection and prevention of attempts to steal or misuse individuals' identities.
- Phishing Detection: Identification and blocking of phishing attempts through fraudulent emails or websites.
- Manipulation of Customer Reviews: Detection and prevention of fake customer reviews on online stores.
