Research On Forensic Investigation Of Ai-Generated Deepfake Content In Criminal Fraud Cases
1. Arup Group deepfake video corporate fraud (Hong Kong / UK)
Facts:
A global engineering firm (Arup) was the target of a large‑value fraud in early 2024 in which an employee received a video‑call purportedly from the company’s overseas Chief Financial Officer (CFO). In that call, the employee was instructed to transfer substantial funds (“HK$200 million” ≈ US$25 million) to accounts under the fraudsters’ control. The fraud was enabled by deepfake video and voice impersonation of senior management.
Forensic / investigation highlights:
The video conference appeared extremely realistic: face, voice, accent of the CFO, the setting, etc. Investigation found that the image/voice had been cloned or synthetically generated to mimic the real executive.
After the funds were moved, tracing of the money became very difficult – the funds had gone through multiple offshore accounts, making recovery extremely challenging.
The corporate victim’s audit and forensic team reviewed the log of internal communication, identified anomalies: unusual urgency, bypass of standard verification steps, mismatch in authentication procedures (for example absence of two–factor sign‑offs, no call‑back to the real CFO).
Key legal/forensic issues:
Attribution: Proving that the voice and video were synthesized rather than genuine. This required forensic audio‑video analysis (lip‑sync anomalies, voice‑signal forensics, digital artefacts) and comparison with known genuine recordings.
Control/process failure: The victim company’s internal controls were circumvented, raising questions of organisational negligence and the necessity of enhanced verification when dealing with executive instructions.
Jurisdiction / traceability: The perpetrators operated across borders; money moved offshore. This complicated legal/regulatory response.
Implication:
This case exemplifies how deepfake media can be used in high‑value corporate fraud by impersonating trusted individuals, how forensic investigation must incorporate audio/video authentication, and how standard corporate verification procedures may need strengthening to detect synthetic media.
Case 2: Share‑trading deepfake investment fraud (India)
Facts:
In Pune, India, a businessman was shown an advertisement on Instagram making promises of high returns: invest a small amount (₹21,000) and in 28 days it would grow to ₹17 lakh. The advertisement included a video featuring recognizable figures (in this case the well‑known founder of an Indian company and his wife) endorsing the platform and the AI‑based trading tool. Investigation revealed the video was a deepfake: the likeness of the real persons was used without their consent, manipulated to endorse the platform. The victim transferred funds and then was coerced by hundreds of calls to transfer more (eventually losing ₹43 lakh).
Forensic / investigation highlights:
Forensic review indicated that the video of the endorsements had subtle inconsistencies: unnatural lip movement, voice mismatches, and metadata suggesting it was synthesized or cloned.
The investment platform directed victims to a WhatsApp group, then an app download, and then further requests for personal/financial details. The fraud included deepfake media + social engineering + crypto/foreign‑dollars layer.
Police launched FIR and traced money flows through bank accounts; they also filed complaint about misuse of identity of public figures.
Key legal/forensic issues:
Deepfake detection: Need to establish that the media was AI‑generated or manipulated. This requires video/audio forensic expertise.
Victim reliance: The misuse of known public person’s likeness and voice increased credibility of the scheme; proving that this led to inducement of the investment is key.
Misrepresentation/fraud: The platform claimed “AI based trading tool” but did not deliver; combined with deepfake endorsement, this forms basis for fraud.
Implication:
This case shows how deepfakes are being used in the investment fraud space: forging endorsements of trusted public figures + promises of AI‑powered returns. Forensic investigators must treat the media as a core piece of evidence and trace both the synthetic media production and the subsequent financial flows.
**Case 3: Virtual “Court” deepfake extortion of elderly couple (India)
Facts:
An elderly couple (in Chennai) were targeted by fraudsters who told them they were under “digital arrest” and forced them to transfer a large sum (₹2.27 crore). The scammers used a fake virtual courtroom, complete with a “judge”, audio‑video segments, voice‑cloned officials, and virtual “custody” to terrorize the victims. The combination of voice synthesis, video simulation and psychological isolation pressured the couple into compliance.
Forensic / investigation highlights:
The video/voice of the “judge” and officials were analysed for authenticity; investigators determined that the visual and audio elements were generated using AI tools (avatars, voice‑cloning).
The fraud involved blocking the victims’ communication, psychologically isolating them, and then controlling their actions via synthetic media.
Investigators mapped the money‑flow and traced SIM‑cards, bank accounts, identifying that the system used multiple layers of fraud.
Key legal/forensic issues:
Novel use of deepfake media for psychological coercion and extortion, not just impersonation for tricking an employee or investor.
Proving the synthetic nature of media and linking that to the victim’s decision to transfer funds.
Investigating the digital supply‑chain: how did the fraudsters create the virtual courtroom, what tools did they use, where are the servers.
Implication:
This case demonstrates how deepfake media can be weaponised for high‑psychological‑trauma frauds targeting vulnerable persons. Forensics must include audio/video synthetics detection, digital behavioural tracing (SIMs, communications), and victim‑impact assessment.
**Case 4: Deepfake video of a share‑fraud syndicate (India: Fake “expert” video)
Facts:
In another Indian case, a deepfake video of a “share‑trading expert” was used: several suspects created a video using an expert’s likeness and voice (without his consent) that promoted a fraudulent investment/crypto platform. A victim was directed via the video link to download an investment app and then coerced into transferring funds. Police arrested five men across Madhya Pradesh and Delhi in connection with the case.
Forensic / investigation highlights:
The video was determined through forensic review to be deepfake: voice‑clone, face‑clone, manipulated scene.
Investigators traced the WhatsApp group, app download link, and bank accounts used for transfers; found pattern of pooling funds into accounts and moving them abroad via crypto route.
Digital forensic logs (device info, IP addresses, SIM registrations) were used to identify suspects.
Key legal/forensic issues:
Use of deepfake impersonation to build trust and drive victims into fraudulent platform.
Mapping fraudulent app downloads and tracing flows into crypto / offshore accounts complicates recovery.
Forensic challenge of linking the media with app usage, device usage, and distinguishing orchestrated syndicate from individual fraud.
Implication:
This case again highlights deepfake‑enabled investment fraud, but tracks a syndicate-level operation and shows the need for forensic coordination across media‑analysis, device/tracing, bank/crypto tracing, and law‑enforcement.
Summary: Forensic Investigation Considerations
From the cases above, a number of key forensic and investigative themes emerge:
Detection of synthetic media (deepfake) is foundational.
Investigators must verify whether audio or video is genuine or manipulated. This typically involves analysing lip‑sync, voice spectral features, digital artefacts, metadata, comparing known reference recordings, detecting inconsistencies.
Without proving the media is synthetic or manipulated, it is harder to attribute victim deception or tie the media to the fraud. (See general commentary on deepfake forensic challenges.)
Linking the deepfake media to the fraudulent act.
It’s not enough to show that a video was fake; you must show that the victim saw it, relied on it, and that this caused their action (transfer of funds, downloading an app, etc).
Forensic logs (communications records, app downloads, bank transfers) must be correlated with the timing of the deepfake media exposure.
Tracing the digital supply‑chain and money flows.
Fraudsters often combine deepfake media with social engineering, app downloads, bank/crypto transfers, offshore accounts.
Investigators must trace SIM cards, device identifiers, IP addresses, bank accounts, crypto wallet addresses.
In corporate fraud cases, investigation may include email logs, internal communication audit trails, video call logs, internal verification process logs.
Attribution of intent and human/organisational responsibility.
Demonstrating that the media was created intentionally to deceive (rather than accidental or user modified) supports criminal prosecution.
For corporate victims: showing that internal controls were bypassed and that the target acted in reasonable reliance on the fake media.
International/jurisdictional issues complicate attribution when perpetrators are abroad.
Victim vulnerability and psychological manipulation.
Some scams target older or vulnerable individuals using fear, authority, isolation (the virtual court case). Investigation must include the psychological aspect of coercion.
Because deepfakes can look and sound very real, the victim’s perception of authenticity is key.
Legal/regulatory frameworks and evidence admissibility.
Many jurisdictions are still adapting to how AI‑generated media is treated as evidence, how to authenticate it, how to address cross‑border offenders.
Forensic practitioners must prepare chain of custody for digital evidence, preserve original files, log metadata, preserve communication logs, preserve device dumps, etc.
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