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MAS Seeks Feedback to Close Regulatory Gaps for Crypto Service Providers

Fintech News

The aim is to mitigate the risks associated with such businesses. The purpose of these requirements is to address the risks of money laundering and terrorism financing, to which DTSPs may be particularly exposed due to their cross-border operations.

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MAS Warns Financial Institutions of Quantum Computing Cyber Threats

Fintech News

In response, the National Institute of Standards and Technology (NIST) has initiated a global effort to standardise post-quantum cryptography (PQC), which includes identifying quantum-resistant cryptographic algorithms compatible with existing communication protocols to safeguard against CRQC threats.

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Real-time P2P seems risky, but the security is solid

Payments Source

There are lots of layers technology risk-mitigation features, and in addition, network level mitigation is provided as well, writes Robb Gaynor, chief product officer at Malauzai.

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Implementing AI Becomes Top-Two Priority for 31% of UK Executives Reveals Accenture

The Fintech Times

Of all the risk factors that have increased in the last two years, disruptive technologies were the second most significant for UK executives, only behind regulatory and compliance risks (33 per cent). Disruptive technology risk ranked fourth among global executives.

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How to Create a GDPR-Compliant Password Policy?

VISTA InfoSec

A GDPR-compliant password policy should enforce unique passwords for each account to mitigate the risk of credential stuffing attacks. MAS-TRM compliance: Technology risk management guidelines by the Monetary Authority of Singapore. NESA compliance: Standards set by the National Electronic Security Authority in the UAE.

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Hong Kong’s SFC Lays Out Regulatory Pathway for Tokenisation

Global Fintech & Digital Assets

Digital Securities that do not qualify under the narrower subset of Tokenised Securities are securities with no links to extrinsic rights or underlying assets and that have no controls to mitigate the risks that ownership rights may not be accurately recorded. through transfer restrictions or whitelisting).

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What is Test Time Training

Nanonets

To mitigate this cost, consider: Parameter-Efficient Fine Tuning (PEFT) : During the training of LLMs, training with LoRA is considerably cheaper and faster. Latency : Not suitable for real-time LLM applications with current technology. Risk of Poor Adaptation : Fine-tuning on irrelevant examples may degrade performance.