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Hong Kong FinTech Week x StartmeupHK Festival 2025: United for decade of innovation and scaling

  • Bias Rating
  • Reliability

    70% ReliableGood

  • Policy Leaning

    -72% Very Left

  • Politician Portrayal

    34% Positive

Bias Score Analysis

The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.

Sentiments

Overall Sentiment

48% Positive

  •   Liberal
SentenceSentimentBias
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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

60% : The Chief Executive Officer of the IA, Mr Clement Cheung, emphasised that the key takeaway from the technological advances in the past few years is that "development is paramount but has to be balanced with regulation".
60% : Taking a dual approach in balancing regulation and development to foster sustainability, he highlighted a series of milestone initiatives of the IA that promote the adoption of advanced technologies and strengthen operational resilience of the industry, including the Open API Framework, the Cyber Resilience Assessment Framework, and the AI Cohort Programme.
59% : They are not only the crucial driver in cultivating innovation but also conducive to obtaining valuable views and feedback from the market for better review and enhancement to existing policy and regulatory frameworks.
58% : Ms Leung also discussed the recent joint consultations by the SFC and Financial Services and the Treasury Bureau on the regulatory framework for virtual asset dealers and custodians, noting positive feedback received.
58% : She also highlighted real-world crypto and NFT (non-fungible token) applications, such as luxury goods authentication and bandwidth sharing, and praised Hong Kong's progressive blockchain regulation as a model for innovation.

*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

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