Deepfakes aren’t new, but this AI-powered technology has become a pervasive threat in spreading misinformation and increasing identity fraud. The pandemic has made matters worse by creating the perfect conditions for malicious actors to take advantage of organizations’ and consumers’ blind spots, further aggravating fraud and identity theft. Fraud from deepfakes dope during the pandemic, and poses significant challenges for financial institutions and fintechs to accurately authenticate and verify identities.

As cybercriminals continue to use tools like deepfakes to trick identity verification solutions and gain unauthorized access to digital assets and online accounts, it’s critical for organizations to automate the process of identity verification to better detect and combat fraud.

When deepfake technology escapes fraud detection

Fraud-related financial crime has steadily increased over the years, but the increase in deep-seated fraud in particular poses real danger and presents a variety of security challenges for everyone. Fraudsters use deepfakes for several purposes, from celebrity impersonations at impersonations of job applicants. Deepfakes have even been used to carry out scams with large-scale financial implications. In one case, the fraudsters used fake voices to round a bank manager in Hong Kong to transfer millions of dollars to fraudulent accounts.

Deepfakes have been a theoretical possibility for some time, but have only gained widespread attention in recent years. The controversial technology is now much more widely used due to the accessibility of deepfake software. Everyone, from the ordinary consumer with little technical knowledge to state-sponsored actors, has easy access to phone apps and computer software that can generate fraudulent content. Additionally, it is becoming increasingly difficult for humans and fraud detection software to distinguish between real video or audio and deepfakes, making the technology a particularly malicious vector of fraud.

The Growing Fraud Risks Behind Deepfakes

Fraudsters are leveraging deepfake technology to perpetuate identity theft and theft for personal gain, wreaking havoc across industries. Deepfakes can be exploited in many industries; however, industries working with large amounts of personally identifiable information (PII) and customer assets are particularly vulnerable.

For example, the financial services industry processes customer data when onboarding new customers and opening new accounts, making financial institutions and fintechs vulnerable to a wide range of identity thefts. . Fraudsters can use deepfakes as a vehicle to attack these organizations, leading to identity theft, fraudulent claims, and new account registration fraud. Successful fraud attempts could be used to generate false identities on a large scale, allowing fraudsters to launder money or take control of financial accounts.

Deepfakes can cause material damage to organizations through financial loss, reputational damage, and reduced customer experience.

• Financial loss: Financial costs associated with deep fraud and scams resulted in losses ranging from $243,000 to $35 million in individual cases. In early 2020, a bank manager in Hong Kong received a call, allegedly from a client, to authorize money transfers for an upcoming acquisition. Using voice-generated artificial intelligence software to imitate the voice of the customer, the bad actors cheated the bank out of $35 million. The money could not be traced once transferred.
• Reputation Management: Misinformation from deepfakes inflicts hard-to-repair damage to an organization’s reputation. Successful fraudulent attempts resulting in financial loss could negatively impact customer trust and the overall perception of a business, making it difficult for companies to make their case.
• Impact on customer experience: The pandemic has challenged organizations to detect sophisticated fraud attempts while ensuring a smooth customer experience. Those who fail to meet the challenge and are riddled with fraud will leave customers with unwanted experiences at almost every stage of the customer journey. Organizations need to add new layers of defense to their onboarding processes to detect and protect against deepfake scam attempts early on.

Future-Proof Identity: How Organizations Can Fight Deep Fraud

Current fraud detection methods cannot verify 100% of real online identities, but organizations can guard against deep-seated fraud and minimize the impact of future identity-based attacks with a very high degree of security. efficiency. Financial institutions and fintechs must be particularly vigilant when onboarding new customers to detect third-party fraud, synthetic identities, and attempted impersonations. With the right technology, organizations can accurately detect deepfakes and combat other fraud.

In addition to validating PII in the onboarding process, organizations must verify identity through extensive multi-dimensional liveness testing, which assesses liveness by analyzing selfie quality and estimating depth cues for the face authentication. In many cases, fraudsters may attempt to impersonate individuals by using legitimate personal information combined with a headshot that does not match the individual’s true identity. Traditional identity verification is inaccurate and uses manual processes, creating a large attack surface for bad actors. Deepfake technology can easily bypass flat images and even liveness tests in identity verification – in fact, Meta’s deepfake detection contest winning algorithm detected only 65% ​​of analyzed deepfakes.

This is where graphic-defined digital identity verification comes in. The continuous supply of digital data during the image validation process gives customers confidence in the identities they do business with and reduces their risk of fraud. Organizations also gain a holistic and accurate view of consumer identities, can identify more good customers, and are less likely to be tricked by deepfake attempts.

While fighting all types of fraud is difficult, security teams can stop deepfake technology in its tracks by evolving beyond legacy approaches and embracing identity verification processes with AI predictive analytics /ML to accurately identify fraud and build digital trust.

Mike Cook is Vice President of Fraud Solutions, Marketing at Socure