Advantages and disadvantages of fraud monitoring

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One example of machine learning being used in fraud monitoring is the use of neural networks to detect anomalies in transactions. These algorithms can analyze user behavior and recognize complex patterns that were not anticipated by the original rules.
Example: If a fraudster uses multiple cards to make purchases on one website, classic fraud monitoring systems may not detect these actions as fraudulent. However, a system using ML is able to analyze the user's behavior and recognize that the transactions are actually made by one person, which raises suspicion.
Biometric identification
Biometrics is becoming an important part of fraud monitoring, especially in the online uganda consumer mobile number list banking and financial services industry. Biometric methods such as facial recognition, fingerprints, and iris recognition help to increase security by further confirming the user’s identity.
Example: If a user tries to log into their account from a new device, the system may request biometric authentication to confirm that they are indeed the account owner and not an intruder.

Like any technology, fraud monitoring has its advantages and limitations. Let's look at the main pros and cons of using fraud monitoring systems.
Advantages
Increased Security : The main benefit of fraud monitoring is the ability to prevent fraud, reducing the risk of losses for the company and its customers.