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Generative AI is not creating an entirely new kind of fraud; it is making familiar scams cheaper to run, easier to personalize and harder to recognize. Criminals can now produce convincing voices, videos, profile photos, identity documents and multilingual conversations at scale. That helps them impersonate relatives, banks, employers, executives and celebrities, while also creating synthetic identities that combine real personal data with invented details.
The evidence is serious but needs careful reading. The FBI recorded more than $632 million in reported 2025 investment-scam losses with an AI nexus and almost $13 million in AI-involved employment-scam losses. Those are complaint figures, not a forensic total of all deepfake fraud. The FBI also recorded nearly $21 billion in reported cybercrime losses overall, while the FTC reported $3.5 billion in 2025 imposter-scam losses, many of which did not involve AI. Sources: FBI 2025 IC3 Annual Report, FBI announcement and FTC data.
What the terms mean
Deepfake fraud
A deepfake is synthetic or manipulated audio, video or imagery used to impersonate someone or create apparent evidence of an event. Examples include a cloned family member asking for emergency money, a fake CEO video call authorizing a transfer, a celebrity investment endorsement or altered “proof-of-life” media in a virtual-kidnapping scam. The FBI warns that criminals use generative AI for voices, videos, profiles and fraudulent documents.
Synthetic-identity fraud
A synthetic identity is a fabricated person assembled from real and invented information—for example, a genuine Social Security number paired with a false name, address, employment history and generated face. The criminal may build credit or account history before borrowing heavily or moving money. This differs from identity theft, where a criminal generally uses one real person’s information as that person. Sumsub describes these distinctions at its identity-fraud guide.
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Related scams
- Stolen-identity fraud: use of a real person’s identifying information without materially fabricating the identity.
- Account takeover: control of an existing account through phishing, credential theft, SIM swapping or support-desk manipulation.
- Impersonation scams: pretending to be a bank, agency, employer, relative, romantic partner or celebrity. AI can strengthen the disguise but is not required.
What generative AI changes
AI changes the economics and quality of social engineering more than it changes criminals’ underlying goals.
- Lower production costs: One operator can create convincing text, images, voice clips, documents and video without advanced media skills.
- Personalization: Public posts and data brokers can be turned into messages tailored to a victim’s job, family, location or investments.
- Language and localization: Translation removes many spelling, grammar and cultural clues that once exposed scams.
- Social proof: Fake experts, comments, testimonials and investment-group members can make a fraudulent community appear active.
- Automated conversations: Bots can answer objections and manage many victims before handing the most promising cases to human operators.
- Document and biometric attacks: Generated identity documents, face swaps, replayed video, camera injection and virtual cameras target onboarding and selfie checks.
The FBI describes AI as increasing fraud’s scale and believability, while Europol’s IOCTA 2026 assessment identifies AI-assisted social engineering as an enabler of larger online-fraud operations.
The scams most likely to reach your phone, wallet or workplace
Family-member voice clones
A caller imitates a child, spouse or parent and claims to be arrested, injured or stranded. A short public recording can be enough for a voice clone; a visible deepfake is not necessary. Verify by calling a saved number and asking a prearranged family question.
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Executive, supplier and invoice impersonation
Criminals study an organization, imitate an executive or supplier and create urgency around payroll, an acquisition, a legal matter or changed payment instructions. A voice or video call may be added when an employee hesitates. A familiar face or voice is not authorization: confirm through a known, separate channel.
Fake bank, government and law-enforcement alerts
A message may claim that an account is under attack and instruct you to move money to a “safe” account, reveal a one-time code or install remote-access software. Caller ID can be spoofed. The FTC says costly impersonation scams often start with fake security alerts appearing to come from a bank.
Celebrity and investment scams
AI-generated videos can depict celebrities, executives or financial commentators promoting fake trading platforms and chat groups. The FBI reported more than $632 million in 2025 investment-scam losses involving a reported AI nexus; the figure reflects victim complaints and does not prove AI caused every loss. Overall investment-scam losses exceeded $8 billion in that report.
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Romance scams
AI helps criminals maintain attractive profiles, coherent biographies, voice messages, video calls and long conversations—sometimes with several coordinated personas. The relationship is still operated by criminals; AI makes the maintenance layer cheaper and more scalable.
Employment and remote-interview fraud
Fake recruiters, AI-written résumés, synthetic applicants and interview deepfakes can be used to steal money or gain access to an employer’s systems. The FBI recorded almost $13 million in reported losses from AI-involved employment scams in 2025 and noted that some schemes appear aimed at network access rather than immediate theft.
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An attacker claims a loved one has been kidnapped and supplies manipulated audio, photos or video as “proof of life.” Do not pay while on the call. Contact the person and local authorities independently.
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Synthetic identities at account opening
A fraudster may combine a real Social Security number with a fabricated name, address, phone number, document and selfie, then use a new device or bank account linked to other identities. A document-and-selfie match shows resemblance to the document photo; it does not prove that the identity is genuine, that the presenter owns the underlying data or that the account is economically legitimate.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How deepfakes and synthetic identities reinforce each other
A synthetic identity creates a fabricated person; a deepfake supplies fabricated evidence of presence, identity or endorsement. A typical pipeline is:
- Acquire personal data through breaches, phishing, brokers or social media.
- Combine real data with invented attributes.
- Generate a face, voice, résumé, address history or business profile.
- Produce a manipulated document or supporting media.
- Use linked devices, phone numbers, addresses or bank accounts to pass initial checks.
- Build account history and apparent trust.
- Commit credit, payment, laundering or account-takeover fraud, then reuse the components elsewhere.
That chain is why a deepfake detector alone cannot identify a suspicious phone number, reused address, device farm, stolen Social Security number or coordinated group of accounts.
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Why a selfie check or detector is not enough
Content analysis
Tools may examine lip synchronization, lighting, reflections, audio artifacts, frame inconsistencies and metadata. Re-encoding, screen capture, poor video quality and newer generation methods can reduce accuracy. Treat a detector as a risk signal, not a universal truth test.
Liveness and presentation-attack detection
Liveness checks test whether a person appears physically present. Replay attacks, camera injection, virtual cameras, masks, screen presentation and sophisticated face swaps can still challenge them. Entrust places motion liveness and presentation-attack detection within a broader stack: Entrust fraud detection.
Identity, device and behavior signals
Effective review also compares authoritative identity data, document consistency, phone and address history, device reuse, IP or proxy activity, account age, transaction behavior and links to other accounts. Synthetic identities may look normal on day one and become suspicious only after months of activity.
Human judgment
Reviewers can be persuaded by convincing audio, video and documents. Give them independent evidence, reason codes, audit logs and authority to pause a transaction instead of asking them to decide from appearance alone.
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- Pause on urgency. A demand for immediate secrecy or payment is a warning sign.
- Verify independently. Call a saved number or use the bank’s official app; do not use contact details supplied in the message.
- Use a family phrase. A prearranged question can defeat a voice clone.
- Reject “safe-account” instructions. Legitimate banks and agencies do not require transfers to protect money.
- Protect authentication data. Never disclose one-time codes, passwords or remote-access permissions.
- Check investments separately. Verify the firm’s registration and withdrawal history through trusted regulators, not a promoted link.
- Limit public voice and identity material. Public videos and personal details give attackers better cloning inputs.
- Preserve evidence. Save messages, numbers, URLs, screenshots, payment instructions, wallet addresses and recordings where lawful.
Controls for employers, banks and platforms
- Payment procedures: dual approval, cooling-off periods for new beneficiaries and callbacks using pre-existing contact information.
- Onboarding: document authenticity, liveness, device and phone risk, duplicate-identity analysis, authoritative-data checks and manual review for contradictions.
- Workforce security: phishing-resistant MFA, strict help-desk verification, privileged-access reviews and training for voice and video impersonation.
- Lifecycle monitoring: watch shared devices, addresses, beneficiaries, transaction timing, dormant-to-active changes and sudden credit use.
- Incident response: freeze payments, disable sessions, preserve logs, notify processors and assess whether personal data or money laundering is involved.
What to do after a suspected deepfake or synthetic-identity scam
- Stop communicating with the scammer and do not send more money.
- Contact the bank, card issuer, payment app, cryptocurrency exchange or wire provider immediately and request a recall or freeze.
- Change exposed passwords, revoke active sessions and replace compromised authentication methods.
- Notify your employer or platform security team if a work account or customer account is involved.
- Preserve all media and transaction details; do not delete “obviously fake” material.
- Report the incident to the FTC and FBI Internet Crime Complaint Center.
- Review credit reports and consider freezes or fraud alerts when personal identity data was exposed.
How to judge fraud-prevention products
For a business choosing a service, ask whether it covers deepfake and injection attacks, forged documents, synthetic and stolen identities, account takeover, device farms and transaction networks. Compare false declines by geography, language, device and document type; reason codes and auditability; privacy and biometric retention; integration; human review; and full cost, including minimums, add-ons, screening and storage. A product’s marketing percentage is not an independent measurement unless methodology and population are disclosed.
The central test is not merely “Is this video fake?” It is “Who is this, what are they authorized to do, and does the surrounding identity, device, behavior and payment evidence make sense?”
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