Concern 511 · Working draft · editorial review in progress
Synthetic identity fraud
Synthetic identity fraud creates an invented identity, sometimes combining real and made-up details, to obtain services or money.
Understanding the concern
Traditional identity theft impersonates an existing person. A synthetic identity instead assembles a persona that does not correspond to one real individual. AI can add convincing photographs, documents or written histories, making that persona appear more complete.
This type of fraud existed before generative AI. The new concern is how inexpensive supporting material may affect verification. A service needs to check consistency and trustworthy records rather than simply reward a polished application. Safeguards must also allow genuine people to correct errors, because unusual life histories should not be treated as proof of fraud.
An example
An account application presents a coherent-looking identity whose supporting details do not belong to one real person.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Reward
- A signal used in some training methods to favor certain behavior. A high reward score does not necessarily mean a good result for people.
- Synthetic
- Made by a computer or another artificial process rather than directly recorded from the event being described.
Evidence and its limits
The Federal Reserve explains the older fraud category; FinCEN addresses suspected deepfake support. Neither proves that all synthetic identities are AI-generated.
Federal Reserve · 2019 · Official explainer
Federal Reserve System white paper examines the effects of synthetic identity payments fraud ↗ (opens in a new tab)Defines synthetic identity fraud, which predates generative AI.
FinCEN · November 2024 · Official alert
Alert on Fraud Schemes Involving Deepfake Media Targeting Financial Institutions ↗ (opens in a new tab)Based on suspicious activity reporting; suspected deepfake use is not equivalent to a proven case in every report.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
- MIT AI Incident Tracker (opens in a new tab)
incidents
- MITRE ATLAS (opens in a new tab)
framework
- International humanitarian law (IHL)
framework
The body of law that governs the conduct of armed conflict and the protection of people who are not fighting, which applies to AI used in or for conflict.
A question to discuss
How can institutions distinguish fabricated identities from genuine people with incomplete records?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Courage
Courage means acting on a well-grounded responsibility even when it is uncomfortable. It can mean trying something useful, admitting a mistake, or challenging pressure to move too fast.
Make it possible for people to raise concerns without punishment. Support those who point out harm, and be willing to pause a popular project when evidence gives a good reason.
Ask together: What important action are we avoiding because it is difficult?
Stewardship
Stewardship means caring for resources and systems that others depend on, including people who will use them later. It looks beyond the benefit of a quick launch.
Plan for maintenance, energy use, data protection, and eventual shutdown. Ask who will look after the tool when the original team moves on and how future users can avoid inheriting hidden costs.
Ask together: What are we responsible for caring for over time?
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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