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4 Trends Shaping How We Combat Money Laundering In Asia Pacific

Fintech News

The Asia-Pacific (APAC) region faces significant challenges in combating money laundering due to its diverse economies, large volume of cross-border trade, and varying levels of regulatory enforcement across different countries — the trends of money laundering in Asia Pacific are constantly evolving.

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Hawk Raises $56 Million in Series C Funding to Help Banks Fight Financial Crime

Finovate

AI-powered anti-money laundering (AML) company Hawk has raised $56 million in Series C funding. Hawk , a company offering AI-powered anti-money laundering (AML), screening, and fraud prevention solutions, has secured $56 million in Series C funding. The company was founded in 2018.

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APAC Sees 23% Decline in Crypto Fraud

Fintech News

Crypto fraud rate, %, Source: State of the Crypto Industry 2025, Sumsub, Feb 2025 According to the report, these results can largely be attributed to advancements in fraud prevention technologies, with innovations like biometrics checks and artificial intelligence (AI)-backed automation significantly enhancing security and fraud detection.

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Visa Unveils 2025 Payment Trends, Shaping Vietnam’s Digital Landscape

Fintech Finance

Visas AI-powered Anti-Money Laundering AI enhances fraud detection and prevention, while tokenization reduces fraud risk by replacing sensitive card details with unique tokens. Enhanced Security: With the rise of digital payments, security is paramount.

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Navigating the rise of AI-enabled fraud

The Payments Association

As payment systems become more digitised and interconnected, the attack surface expands, and the stakes for payments firms to invest in robust, AI-driven fraud detection and prevention systems have never been higher. fingerprints, facial recognition), and behavioural biometrics (e.g., keystroke dynamics or mouse movements).

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Machine Learning Fraud Detection: Why Custom Models Beat Off-the-Shelf Solutions

Fraud.net

Explore how machine learning fraud detection reduces false positives, improves accuracy, and adapts to emerging fraud trends.

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No New AI Rules Needed, Just Better Guidance, Says Innovate Finance

The Fintech Times

Common use cases include fraud detection, anti-money laundering, cybersecurity and back-office automation. Around 41 per cent of firms report using AI to streamline internal processes, while 37 per cent cite cybersecurity as a primary application, and 33 per cent focus on improving fraud detection.

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