New Scoring System Flags Who's Most Likely to Fall for Online Scams

The Internet is full of scams — fake tech support, romance fraud, phishing emails — and some people are much more likely to get hurt than others. But the old ways of measuring risk don't tell the whole story. One tool only looks at technical flaws in software. Another looks at the vulnerability of whole communities, like poverty or lack of resources. Neither captures the human side: Do you know the warning signs? Do you panic when someone says your bank account is compromised? Have you been scammed before?

This new research from nine academics proposes a single score called the Social Cyber Vulnerability Index, or SCVI. It's built from two parts: one that measures an individual's exposure to scams — their awareness, behavior, psychological traits, and whether they've been tricked before — and another that looks at how dangerous the attack itself is, including how often it happens, how much damage it does, and how sophisticated it is. By blending these, the score aims to show who is most at risk and why.

The researchers tested the index using two very different sources: a nationwide survey of nearly 4,600 U.S. adults, and roughly 450 real-world scam reports posted on the Reddit community r/scams between 2016 and 2024. They even showed it can be calculated automatically from people's social media posts using AI to detect risky signals. The new score distinguished scam victims from non-victims far better than the existing technical or community-based tools. It also revealed regional and demographic differences — for example, certain age groups or locations showed higher vulnerability.

Why does this matter? Because scam losses are enormous and growing. The authors note their tool could help identify high-risk populations and prioritize interventions, especially as AI makes scams more convincing and harder to spot. It's not a perfect crystal ball — the study admits the score depends on some judgment calls about what weighs most heavily. But it's an important step toward understanding the human side of cybercrime, not just the technological side.