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In the contemporary digital world, the proliferation of deepfake technology and generative AI heralds an era fraught with online scam challenges, notably within the financial sector in Asia. Economic Ramifications of DeepfakeScams The global impact of impersonation scams can be far-reaching, and expensive.
The integration of Sumsub’s compliance solutions will help financial institutions deal with the growing threat of fraud and financial crime. This includes a global, fourfold increase in AI-driven deepfakescams. This will enable them to onboard customers faster and comply with international KYC/AML regulations.
Dan Yerushalmi , CEO of AU10TIX “FaaS has elevated cybercrime, enabling a whole cohort of the population to join in on global fraud by launching large-scale attacks involving up to over 8,000 incidents,” explained Dan Yerushalmi , CEO of AU10TIX.
According to a recent report by the National Crime Agency (NCA), GenAI represents one of the most substantial threats to the fraud landscape today. Fraudsters are exploiting GenAI tools such as large language models (LLMs), voice cloning, and deepfakes to carry out increasingly sophisticated scams that are harder to detect and prevent.
In response to the growing threat of deepfake technologies, Ant International has also developed an advanced anti-deepfake electronic Know Your Customer (e-KYC) tool. This system, which has a detection success rate exceeding 99%, was developed over two years to counter AI-assisted fraud and bolster transaction security.
However, regulators have been expanding accountability beyond financial institutions to the digital channels used in fraudscams, such as telecommunications and social media. An AI Arms Race The emergence of AI has added a new dimension to this battle, with both scammers and fraud prevention efforts leveraging advanced technologies.
While this marks a significant step toward protecting consumers from authorised push payment (APP) fraud, concerns remain that the reduced compensation cap may leave some victims vulnerable. Further, it is unclear whether the rules address the complexities and evolving fraud tactics. AI is a double-edged sword in fraud prevention.
AI-powered fraud-as-a-service (FaaS) platforms have enabled these mass-scale attacks, contributing to APAC now holding the highest global fraud rate, with 3.27 Bots and deepfakes The rise of bots using deepfake technology to create convincing fake profiles poses an additional challenge.
How can the technology driving novel and increasingly sophisticated fraud activities be harnessed to combat scams and cyber risks cost-efficient and effectively? These advancements have changed the way we approach cybersecurity and frauddetection. Learn More Sources : 1.
Historically, companies have resorted to a patchwork of point solutions and variegated tools across a fraud-fighting tech stack, leading to fragmented data and operational inefficiencies from switching from one solution to the subsequent and obfuscated risk views.
As a result, organizations face large volumes of fraudulent data, necessitating heightened vigilance and advanced detection methods to protect themselves – and their customers or users. Other AI applications include enhancements to traditional scams, such as phishing and social engineering attacks.
The rise of artificial intelligence (AI), machine learning (ML) and automation have all added new layers of complexity to fraud prevention at an unprecedented scale. For instance, fraudsters now leverage innovative technologies to create deepfakes, bypassing traditional identity verification methods like document ID checks and biometrics.
STACK implements various behind-the-scenes procedures — tokenization, identity verification and automated frauddetection, for example — and provides customer-facing options that give users a sense of control and transparency.
Fighting deepfakes and fraudulent identities – Jumio’s holistic approach to building identity trust” with “Jumio Delivers Adaptive Verification as AI Fraud Projected to Hit US$40 Billion. Hong Kong police recently arrested 27 individuals linked to a deepfakescam that swindled victims out of $46 million.
As payment systems become more digitised and interconnected, the attack surface expands, and the stakes for payments firms to invest in robust, AI-driven frauddetection and prevention systems have never been higher. fingerprints, facial recognition), and behavioural biometrics (e.g., keystroke dynamics or mouse movements).
Within wider AI-driven topics frauddetection was an interesting one, in the session Dealing with AI, Fighting on both sides of Financial Fraud, experts discussed the dual role of AI, both as a weapon for fraudsters and a defence mechanism for financial institutions. Her words landed with weight.
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