In the ongoing effort to secure online platforms, verifying a user’s identity is more critical than ever. Traditional methods like CAPTCHA and two-factor authentication have their place, but they don’t always provide the full picture. A newer, more insightful approach is gaining traction: email age estimation. This technique analyzes the age of an email address to add a powerful layer of security and trust to the user verification process.
Why does the age of an email address matter?
The age of an email account is a surprisingly reliable indicator of its legitimacy. Fraudsters and bot accounts often use freshly created email addresses to carry out their activities. These “burner” emails are disposable and hard to trace. In contrast, genuine users typically have email accounts that are months, if not years, old. By estimating an email’s age, you can quickly distinguish between a long-standing, trustworthy user and a potential threat. For example, a new account registered with a 10-year-old email address is far more likely to be legitimate than one using an email created just minutes ago.
How does email age estimation enhance security?
Incorporating email age estimation into your verification workflow adds a dynamic layer of risk assessment. It allows you to create smarter, more flexible security responses. If a user signs up with a brand-new email, you can trigger additional verification steps, such as a phone number confirmation or a more complex security question. On the other hand, if a user’s email has a long history, you can streamline their onboarding process, reducing friction and improving their experience. This risk-based approach makes your platform more secure without inconveniencing legitimate users.
What are the benefits beyond fraud detection?
The advantages of email age estimation extend beyond just stopping bots. Understanding the age of a user’s email can help in other areas as well. For marketing, it can help segment users for targeted campaigns, as users with older emails might represent a more established demographic. For customer support, it provides another data point to help verify a user’s identity when they request assistance. Essentially, it adds a layer of intelligence that can be leveraged across various business functions, making your systems smarter and your user interactions safer.