← Portfolio Home · Work Library
In a scam flow, the useful moment for product intervention may be only a few seconds before money moves. That is why this concept focuses less on long-form education and more on short, contextual actions before, during, and immediately after a risky transfer.
Type: Product Concept Stage: Working Hypothesis Evidence basis: Public scam patterns, payment-flow reasoning, and product inference Last updated: July 2026 Boundary: A product hypothesis—not a fraud-classification standard, legal-advice system, or claim that risk signals establish wrongdoing.
Quick orientation: Context → Thesis → Product concept → One-line positioning
Experience logic: Before transfer → During transfer → Post-transfer → Pathway lens
Critical review: AI role → Success metrics → Risks and guardrails → Open questions
Vietnamese users increasingly face scam scenarios that happen inside high-pressure payment moments: fake sellers, urgent family impersonation, fake rewards, fake customer support, fake investment tasks, QR transfers, and social-engineered bank transfers.
Most anti-scam experiences still behave like education tools: they explain what scams are, list warning signs, or ask users to read long guidance pages. That is useful for awareness, but it often appears too early, too late, or too far away from the actual decision point.
The critical moment is not when the user wants to learn about scams. It is when the user is about to send money, confirming a risky transfer, or trying to recover immediately after sending money.
A scam is often not only an information problem. It is a timing, pressure, and workflow problem.
Users do not need a long AI explanation during a risky payment. They need a short intervention that changes the next action.
Typical failure pattern: