Stopping scams targeting older consumers

Older consumers are targeted the most by online fraudsters

Since the lockdown, the data by the Charity Age UK reported that more than £5m  was lost to the covid related scams, and £16m was lost to scams involving online shopping where the victims were those in the age over 55 years. Such fraudsters target the most vulnerable class of society who are unequipped and unaware of their tech tricks. 

They have poor cognitive abilities and experience various problems while interacting and communicating with people. They are not tech-savvy, and the attackers succeed in creating pressure or portraying themselves as service providers. Also, they have higher savings or may own a home or have a good credit rating. 

These conmen use various practices like stealing data and payment details and their account logins. In addition, they make use of the personal information filled during the registrations, often used in CNP – Card-not-present cases. 

How does it happen?

Older consumers are falling victim to a range of financial frauds. The cases against the adult population increased during the epidemic, and it requires serious consideration to help those who have lost the retirement money. 

The impersonation cons often target older consumers. The policy warns people against such threats if they have elderly relatives, often targeted by a telephone scam where a person calls and says they are from the police department from some local police station or a fraud department. 

Sometimes, they claim to be from an authorised financial firm or administration agency. They use various tricks to obtain information related to bank details, or they may ask the victim to tell them about the personally held money or valuables. 

For example, they may threaten the victim that they will have to face regulatory complications and get arrested or have an authorised house search if they do not divulge the details.

In the recent tech support scam targetting older, the caller pretends to be from a technical support team or a government department, offering technical support or a virus scan or other types of tech solutions. Alternatively, the criminals aim to ploy the victim to pay for some bogus technical fix. 

Other such scams where the older victims are targeted, e.g. the companies sending mailers to the people to tell them they won some prize money in millions and the recipient, need to pay a small amount of charge to get the prize, are growing. 

The criminals may indulge in a data takeover where the consumer believes that they are into a legitimate business. Then they seek access to the victim's computer to repair a fault and ask to enter the card details to pay for the repair. 

The fraudsters use other ways to get the information, as they call over phones stating a warrant has been released against their unpaid tax charges. 

The client is asked to pay the fine to avoid the arrest, or they may be asked to buy goods by making online payment, and as they enter the credit card details, the scammer applies it to transfer the money into their accounts.

How to avoid it?

One should know the police never asks to tell what valuables you own or have in your house. Likewise, they never ask you to tell details about the bank accounts. So if you get any such calls, immediately hang up and call the police. 

Then, you can pass the message to the family or friends who may not have access to social media. The FTC has a long work experience in helping people get protection against the before-mentioned issues. It works to help older adults in every community.

The merchants can use various methods to detect and stop such crimes, like checking the geographical location of the purchases, the IP address, and the device type to see if the method used for buying products is unknown. 

Retailers need to help and educate older customers to avoid it. They need to create stop points during the purchase process and give pop-ups and warning messages to the buyer. Machine learning can identify and stop frauds like Card-not-present by be spotted by AI.

A behavioural analysis system can recognise certain patterns of the consumers ordering products online. For example, it may involve a high purchase amount without browsing the websites, and all purchases are made at high velocity. 

So a customer who has been ordering low-cost items cannot suddenly make highly valuable purchases in huge amounts where the items are mostly laptops, videogames and other gadgets.