Priya Patel
TLDR:
– A joint survey by PwC and the Hong Kong Trade Development Council reveals that data availability and cybersecurity are the main challenges to the use of AI in financial services in Hong Kong.
– About 40% of respondents believe that Hong Kong’s current pace of AI development is on par with other financial hubs, but a majority also identify a skills gap in the workforce and cybersecurity as insufficiently addressed challenges
According to a survey conducted by PwC and the Hong Kong Trade Development Council, data availability and cybersecurity are the major challenges to the use of artificial intelligence (AI) in the financial services sector in Hong Kong, according to more than 60% of Hong Kong financial professionals. The survey also revealed that around 40% of respondents believed that Hong Kong’s current pace of AI development was on par with other financial hubs. However, a majority also said that a skills gap in the workforce and cybersecurity represent insufficiently addressed challenges. Raymund Chao, PwC Asia-Pacific and China chairman, highlighted the need for business reinvention and harnessing the power of AI to respond to a constantly evolving landscape. The survey also found that AI has made inroads into various aspects of financial services, such as virtual chatbots, fraud detection, and biometric authentication. Respondents expressed optimism about Hong Kong’s standing as a global financial hub well-positioned for AI adoption. However, concerns include Hong Kong’s data availability and quality, with more than two-thirds of respondents citing these factors as hindering AI implementation. Data privacy and cybersecurity were also identified as key challenges. One in four professionals said that Hong Kong is not adequately prepared for future AI adoption in terms of workforce availability and readiness. Respondents suggested strategic measures to harness the full potential of Hong Kong as a financial hub and technology centre, including promoting further use of AI in the fintech industry, encouraging data sharing, and strengthening the AI regulatory framework. The survey also highlighted the need for a robust data governance framework, regulatory sandboxes for testing and deploying AI technologies, and a designated regulatory framework for responsible AI use.
