A Social engineering scam is one of the hardest types of fraud attacks to detect because it essentially involves a person defrauding him or herself while under the influence of a con artist. Traditional fraud detection measures do not work in this instance – a legitimate person logs in from their own device at the correct location and conducts a fully-authorized transfer.
By leveraging advanced data science and AI techniques, BioCatch’s solution analyzes more than 2,000 behavioral parameters and generates powerful insights that are used for validating a user’s identity and detecting fraud. Among these insights are indicators that suggest a person is conducting a transaction under the influence of a fraudster. By flagging this in real-time, banks are able to prevent significant losses and better protect their clients and assets.
How Does BioCatch Detect Social Engineering Scams?
- Detects behaviors that suggest a person is taking instruction to conduct a transaction
- Analyzes the prevalence of known risky behaviors in confirmed fraudulent sessions versus how legitimate transactions are handled
- Flags suspicious transactions and generates VoiceScam indicators in real-time
