Deepfakes are synthetic media that have been digitally manipulated to replace one person's likeness convincingly with that of another. Deepfakes are the manipulation of facial appearance through deep generative methods

Deepfakes are usually created using artificial intelligence (AI) to manipulate existing footage. This technology can seamlessly superimpose a person's face onto another body, or even generate entirely realistic audio of someone saying things they never uttered. While deepfakes can be a source of amusement or even satire, their potential for fraud is raising major concerns. 

As this technology becomes more sophisticated, fraudsters are finding increasingly creative ways to exploit deep fakes for financial gain. This article will explore the world of deepfakes, how they're used in fraud schemes, and what can be done to mitigate these risks.


What are Deepfakes?

The term "deep fake" is a blend that combines two key elements:


1. Deep Learning


This refers to a specific type of artificial intelligence (AI) inspired by the structure and function of the human brain. Deep learning algorithms are trained on massive amounts of data, allowing them to identify patterns and perform tasks like image recognition or speech generation.


2. Fake


This simply means the content is not genuine. Deepfakes leverage deep learning to create highly realistic and convincing manipulated media.

How Do Deepfakes Work?


To know how deep fakes work, you must understand that:


a. Deepfakes rely on Generative Adversarial Networks (GANs)


Imagine two AI systems pitted against each other. One system (generator) creates new content, while the other (discriminator) tries to identify if it's real. Through this competition, the generator learns to produce increasingly realistic forgeries.


b. Training data is crucial to deep fakes


Deepfakes require a substantial amount of real footage or audio of the target person to train the AI. This data can be scraped from social media, public appearances, or even leaks.


What Are The Various Forms Deepfakes Come As?


Deepfakes come in various forms, depending on the targeted media. They include:


i. Video deep fakes


These are the most common and can convincingly replace a person's face in an existing video or create an entirely new video with a manipulated performance.


ii. Audio deep fakes


AI can be used to mimic a person's voice, allowing fraudsters to create fake voice recordings for phishing scams or impersonations.


iii. Image deep fakes: 


While less common, deep learning can be used to manipulate photos, creating scenarios or situations that never happened.


How Do Fraudsters Use Deepfakes?


Unfortunately, as the power of technology and Artificial Intelligence continue to evolve, deepfakes have become a growing concern in the realm of fraud. Their ability to create realistic and believable portrayals is a boon for fraudsters, who are devising new schemes to exploit this technology. Here's a look at how deep fakes are being weaponized:


a. Impersonation Scams: A Mask of Deception


Unfortunately, deepfakes are the masters of impersonation, allowing fraudsters to masquerade as trusted figures. They do this through the following ways:

  • Targeting Individuals: Imagine receiving a call from your bank, seemingly from a familiar customer service representative (courtesy of a voice deepfake). The "representative" warns of suspicious activity on your account and urges you to transfer funds to a "secure" location – actually, a fraudulent account controlled by the scammer. This tactic preys on fear and urgency, making it difficult to distinguish between real and fake.
  • Targeting Organizations: Deepfakes can also target entire organizations. A fraudster might create a video deepfake of a company's CEO instructing employees to process a large payment to a seemingly legitimate supplier. However, the supplier is a cleverly disguised front for the fraudster. This "CEO fraud" can result in significant financial losses for unsuspecting companies.


b. Account Takeover: Bypassing the Gatekeepers


Deepfakes pose a threat to security measures like facial recognition and voice authentication. A fraudster could use a deepfake video to mimic a user's face during a login attempt, potentially bypassing security protocols and gaining access to a victim's account. Similarly, a voice-deep fake could be used to trick voice authentication systems.


c. Synthetic Identity Fraud: Building a House of Lies


Deepfakes can be used to create entirely fictional identities. By combining deepfake images and fabricated information, fraudsters can manufacture synthetic identities to apply for loans, credit cards, or even access government benefits. These fake identities can be incredibly convincing, making it difficult for traditional verification methods to detect the fraud.

The emergence of deepfakes in fraud necessitates increased vigilance and awareness. By understanding these tactics, individuals and organizations can better protect themselves from becoming victims.


What Are The Impact Of Deepfakes On Fraud?


Deepfakes, the AI-powered masters of manipulation, are casting a long shadow on the world of finance. Their ability to create near-flawless replicas of reality is making it increasingly difficult to detect fraud, leading to a multitude of negative consequences.


a. It Is Difficult To Detect


One of the most concerning aspects of deepfakes is their ability to blur the lines between genuine and fabricated content. Traditional fraud detection methods often rely on identifying inconsistencies or red flags. However, deepfakes are becoming so sophisticated that even trained professionals can struggle to distinguish them from the real thing. This makes it harder to identify fraudulent activity before it's too late, allowing scams to fester and inflict more damage.


b. Deep Financial Losses


The financial implications of deepfakes are stark. From individuals falling victim to personalized phishing scams to entire companies succumbing to CEO fraud, deepfakes have the potential to inflict significant financial losses. Imagine a deepfake video of a CEO greenlighting a multi-million dollar transfer to a seemingly legitimate account, only for it to be a cleverly disguised front for the fraudster. Such scenarios highlight the potential for deepfakes to disrupt financial operations and cause major losses.


c. Causes An Erosion of Trust


Perhaps the most insidious impact of deepfakes lies in their ability to erode trust. In an age where manipulated media can appear genuine, it becomes increasingly difficult to know who or what to believe. This breakdown in trust can have a ripple effect, impacting not just financial transactions but also social and political discourse. Deepfakes can be used to spread misinformation, damage reputations, and sow doubt in legitimate institutions.


How To Mitigate The Risks Of Deepfakes


The ever-growing threat of deepfakes in fraud necessitates a multi-pronged approach to mitigate their risks. By combining user awareness, technological advancements, and potentially even future regulations, we can build a stronger defence against these deceptive tactics.


a. The First Line of Defense: User Awareness


Empowering individuals is crucial in the fight against deepfakes. The following are some sure ways to do just that:


  • Critical Thinking: Developing a healthy dose of scepticism is essential. Don't rush into decisions based on information received through calls, emails, or videos. Take time to verify the sender's identity and the legitimacy of the request.
  • Identifying Red Flags: Be wary of unsolicited calls or messages, especially those creating a sense of urgency or panic. Watch out for inconsistencies in communication style, grammatical errors, or unusual requests for personal information or financial transfers.


b. The Technological Counteroffensive: Deepfake Detection Tools


Technology can be a powerful weapon against deepfakes. Advancements in the field of deep fake detection offer promising solutions:


  • AI vs. AI: Researchers are developing sophisticated AI algorithms specifically designed to identify deepfakes. These tools can analyze subtle inconsistencies in facial movements, lip-syncing, or audio patterns, potentially revealing manipulated content. Youverify AI-powered liveness detection coupled with Identity and electronic identity verification makes it difficult for fake IDs to pass through.  
  • Digital Watermarking: Embedding invisible codes into digital media can help track its origin and identify potential alterations. While not foolproof, it can add another layer of verification.


c. The Legal Landscape: Regulatory Measures on the Horizon


As the deep fake threat evolves, regulatory bodies may need to consider implementing measures to curb their misuse:


  • Legislation: Laws could potentially criminalize the creation and distribution of deepfakes for malicious purposes. This would deter bad actors and establish clear legal boundaries.
  • Platform Accountability: Social media platforms and other online content providers might face increased scrutiny and potential regulations to ensure responsible handling of deepfakes.



Having discussed what are deepfakes and how fraudsters use them, we can stand on the fact that deepfakes are a growing threat to the integrity of financial systems and the foundation of trust in society. As this technology continues to evolve, it's crucial to develop robust detection methods, educate individuals and organizations on how to identify deepfakes, and potentially implement regulations to combat their misuse. 

The challenges posed by deepfakes are not insurmountable. By taking the proactive measures mentioned above and working together, we can build a more secure digital environment where trust and truth prevail. Remember, vigilance and a healthy dose of scepticism are key to staying ahead of these ever-evolving deceptive tactics.


See how 1,000+ global companies use Youverify eIDV and liveness detection for KYC and AML screening of customers for compliance and real-time risk detection against deep fakes. Request a demo today.