The adoption of generative artificial intelligence in Hong Kong’s financial sector is gaining momentum and shows steady signs that the process will continue.
The mentioned statement is confirmed by the results of the study published on Wednesday, April 9, and conducted by the Hong Kong Institute for Monetary and Financial Research (HKIMR), the research arm of the Hong Kong Academy of Finance. The specified data suggests that 75% of surveyed companies have designed or implemented at least one use case for generative artificial intelligence. Preliminary forecasts suggest that the corresponding figure will increase to 90% over the next three to five years.
The data released on Wednesday also shows that the adoption rate of generative artificial intelligence is higher among large financial institutions. In this case, 83% of the survey participants rolled out at least one case for using generative AI or performed certain actions in the appropriate direction. At the same time, among small companies, the mentioned indicator was recorded at the 63% mark.
Enoch Fung, chief executive officer of the Academy of Finance and executive director of HKIMR, stated that in the financial services industry, generative artificial intelligence apps can contribute to a more curated customer experience and more efficient ways of processing and utilising digital information.
A total of 55 entities across the insurance, wealth, and asset management sectors participated in the survey. The combined share of these companies in total deposits in the Hong Kong banking industry is 57% and 48% of the gross premiums in the insurance area.
Generative artificial intelligence enables models to learn from patterns in their training data to create outputs such as text, images, audio, or video.
At the same time, it is worth noting that the adoption of generative AI is associated with certain new risks and challenges. In this case, for example, concerns about the accuracy of machine intelligence models are relevant. Artificial intelligence as a technology can indeed be more attentive and thorough when performing a wide range of tasks than a human, but there is a nuance. Certain errors in the databases on which the AI is trained can cause an incorrect task result. Moreover, there is a danger of malfunction in the process of functioning of artificial intelligence models. Also, in the context of the adoption of machine intelligence, the risks associated with the privacy and security of user data are relevant. Moreover, the corresponding process at a certain stage of implementation may face the problem of constraints related to a lack of resources and talents. It is worth noting that the relevance of this aspect varies depending on the region. The mentioned problem will not be critical and even more insurmountable in countries with a high level of technological development.
In Hong Kong, authorities have launched an updating of regulatory guidelines and initiatives aimed at supporting the responsible adoption of generative artificial intelligence and innovation. In this case, it means updated circulars and guidelines on the use of generative AI models, the introduction of the corresponding category of digital intelligence sandbox, and the promotion of industry-wide events that support knowledge exchange.
Enoch Fung stated that the adoption of generative artificial intelligence requires a critical focus on safety, trust, and integrity.
The Academy of Finance argues that to further advance the mentioned process, the Hong Kong financial services sector needs to promote a level playing field and strengthen local technology and talent ecosystems. In this case, actions such as expanding financial literacy programs, enhancing industry infrastructure, and further collaboration among stakeholders to address issues like accountability, data localization, data sharing, and data protection are implied.
It is worth noting that, in general, for the fintech industry, which is what corresponds to such a formulation as a cutting-edge functional space, the adoption of artificial intelligence is as natural and logical as possible.
As we have reported earlier, Bank of America to Spend $4 Billion on AI and New Tech Initiatives.
