As technology continues to advance, so do the methods of scammers looking to take advantage of unsuspecting consumers. In 2022, the Federal Trade Commission (FTC) reported that US consumers lost a staggering $330 million to text scams.
Text scams, also known as smishing, involve scammers sending fraudulent text messages to individuals in an attempt to obtain personal information or money. These messages often appear to be from a legitimate source, such as a bank or government agency, and may include a link or phone number for the recipient to contact.
One common type of text scam is the phishing message, which attempts to trick individuals into providing sensitive information such as passwords or social security numbers. Another type is the lottery or prize scam, which claims that the recipient has won a large sum of money but must pay a fee or provide personal information in order to claim the prize.
The FTC reports that text scams have become increasingly prevalent in recent years, with a 50% increase in reported incidents from 2020 to 2022. This rise can be attributed in part to the COVID-19 pandemic, which has led to an increase in online activity and reliance on digital communication.
To protect themselves from text scams, consumers should be cautious when receiving unsolicited messages and avoid clicking on links or providing personal information. It is also important to verify the legitimacy of any message or request before taking action, such as contacting the supposed sender directly through a verified phone number or website.
In addition, consumers can take steps to protect their personal information by using strong passwords and regularly monitoring their financial accounts for suspicious activity. Reporting any suspected text scams to the FTC can also help prevent others from falling victim to these fraudulent schemes.
While text scams may continue to evolve and become more sophisticated, staying informed and vigilant can help consumers protect themselves and their finances from these harmful attacks.
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- Source: Plato Data Intelligence.
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