By Tanner Call
I’ve recently been the target of a clever direct mail scam. It involves convincing the potential victim that their vehicle’s warranty is about to expire and that they need to renew it soon. The letter includes “official” components such as a barcode, logo, reference number, and even a chart with a summary of terms.
The document looked so official and complex that my first reaction was to call the phone number to speak to a real person. I was confused. I couldn’t make sense of the coverage explanation, platinum options, or program terms (which legitimate insurance quotes have). The only reason I realized this was a scam was because of typos and no reference to a specific company or government agency (such as a car dealership or the DMV).
The combination of document complexity and confusing content made this scam much more deceptive than other attempts. When industries create a culture of complicated language, it can make already-vulnerable customers more likely to fall for scams that take advantage of unclear content. Criminals fill their scams with such complex jargon (common for insurance companies) that it’s impossible for their victims to understand. Then they call the number and give the scammer their personal information.
Companies could provide insurance documents and quotes that are easy to understand. This plain language could have two possible benefits:
- First, customers could more easily understand the content and better navigate their fees, benefits, and coverage.
- Secondly, it would reduce scammers’ ability to trick people by masking their fraud in complex language.
In this situation, plain language would create a win-win scenario: customers would be more aware of their actual policy components and companies would see fewer cases of fraud. The only losers are the scammers, but that would be okay.
About the author: Tanner Call is currently in his second year in Georgetown’s MA in Language and Communication. He also works as a linguistic consultant for Verilogue and is deeply passionate about using real-life language data to improve society.