Scam Classification & Mapping System
A structured taxonomy for classifying scam techniques from first contact to financial extraction.
Consumers reported losing $15.9 billion to fraud in 2025, up 27% from the prior year. That figure far outpaces ransomware losses. And reported losses capture only part of the problem.
Defenders and the institutions they work in still describe scam activity using inconsistent terms. In its 2025 national strategy, the Aspen Institute's fraud task force noted that better standardization of fraud and scam data and typologies "may be a critical structural component" of improving the response.
SC&MS was created to fill that gap: a framework built around a structured, lifecycle-based taxonomy of scam techniques. Instead of treating scams only as categories, SC&MS breaks them into reusable components across the ABCDEF lifecycle.
How scams evolve from first contact to financial extraction
Vectors used to initiate first contact with a potential victim
Lures, offers, and alerts used to entice a victim's engagement
Pressure and control tactics used to compel action or maintain compliance
Fabricated or manipulated artifacts used to mislead victims and make the scam believable
Borrowed or cultivated trust used to lower a victim's skepticism
Methods used to extract money, assets, or other value from victims
From security teams to law enforcement, SC&MS gives defenders a common language for classifying scams
Map detection capabilities and identify gaps in anti-scam defenses across the organization
Analyze scam campaigns using standardized terminology for consistent documentation and reporting
Structure and communicate scam tactics and techniques for cross-team collaboration
Categorize and track scam operations with consistent terminology across jurisdictions
Classify fraud incidents and share intelligence with industry partners
Build awareness programs using a structured framework to teach scam recognition and prevention
Get occasional SC&MS updates, release notes, and new research.