The A-List highlights the most highly recommended private practice lawyers across various fields within China’s legal market. Following months of rigorous market research, China Business Law Journal has identified the key players and business leaders who are instrumental in driving growth within law firms. These distinguished lawyers are recognized for their extensive practical experience, exceptional legal expertise, and their active engagement at the forefront of the industry, all while maintaining an outstanding reputation and remarkable revenue-generating capabilities.

We would like to take this opportunity to thank CBLJ for the recognition and express our gratitude to our clients for their continued trust and support.

For more information, please contact our Partners Heidi Chui and Rodney Teoh, or click here to see the rankings on The CBLJ.

《电子交易条例》（香港法例第553章）（下称「该条例」）于2000年首次通过，其立法原意旨在促进电子交易的合法性及普及性，为电子签署及电子合约的法律效力提供法律框架。该条例的主要目的是确保一般电子交易在法律上与传统的纸质交易具有同等法律效力，从而促进电子商务及数字经济的发展。

该条例第17条订明电子合约不妨碍合约的有效性及可强制执行性。相比纸质交易，该条例为交易各方提供以下便利：

随着电子交易日趋普及，香港政府以《2024年电子交易（豁免）（修订）（第2号）令》（L.N. 142 of 2024）（下称「修改令一」）及《2024年电子交易条例（修订附表3）（第2号）令》（L.N. 143 of 2024）（下称「修改令二」）修订了该条例及《电子交易（豁免）令》（香港法例第553B章）（下称「该附属条例」），以适应新的市场需求和技术发展。修订于2024年12月13日起实施，其摘要如下：

上述修订突显香港政府致力透过法律来适应科技发展的决心。该条例及该等附属条例不仅有助提高交易效率，亦减少纸质文件的需求，从而降低运营成本。就金融机构而言，这意味着可以更快地处理交易，提升客户体验，并加强市场竞争力。本所预计，随着香港继续发展成为国际创新及科技中心，该条例及该附属条例将作进一步修订，以扩大电子服务的应用范围，进一步巩固香港作为国际金融中心的地位。

本摘要仅供参考，并非旨在提供正式的法律意见。

[1] 根据该条例第2条（释义），「电子纪录（electronic record）」指资讯系统所产生的数码形式的纪录，而该纪录（a）能在资讯系统内传送或由一个资讯系统传送至另一个资讯系统；并且（b）能储存在资讯系统或其他媒介内。

[2] 根据该条例第2条（释义），「电子签署（electronic signature）」指与电子纪录相连的或在逻辑上相联的数码形式的任何字母、字样、数目字或其他符号，而该等字母、字样、数目字或其他符号是为认证或承认该纪录的目的而签立或采用的。

[3] 根据该条例第11(1)条，常任秘书长可藉于宪报刊登命令，将本条例原本适用的任何条例，或任何条例内的特定规定或准许，或任何条例内的某类别或种类的规定或准许，豁除于第5、6、7或8条的适用范围之外。

[4] 根据该条例第50条，局长可藉宪报刊登的命令修订附表1、2及3。

On 28 November 2024, the Hong Kong Monetary Authority (“HKMA”) has officially launched the Digital Bond Grant Scheme (“DBGS”), a key initiative announced in the 2024 Policy Address. The scheme aims to accelerate the development of the digital securities market and encourage the adoption of tokenisation technology in capital market transactions. By providing financial incentives to eligible issuances, the DBGS seeks to position Hong Kong as a global leader in digital finance.

1. Financial Support for Digital Bond Issuances

The DBGS offers funding to cover 50% of eligible expenses for digital bond issuances, up to:

To ensure a broad distribution of resources, each issuer and its associates can receive subsidies for a maximum of two digital bond issuances.

2. Basic Eligibility Requirements

To qualify for the scheme, digital bonds must meet the following criteria:

(1) The bond must be issued in Hong Kong, with at least 50% of the lead arrangers recognised as Hong Kong-based; and
(2) The issuance must either:
– involve a digital team with substantial operations in Hong Kong (assessed based on factors such as team size, composition, and seniority); or
– take place on a distributed ledger technology (“DLT”) platform operated by the Central Moneymarkets Unit (“CMU”).

3. Additional Criteria for Full Grant

Issuances seeking the Full Grant must meet the following additional requirements:

(1) DLT Platform: The bond must be issued on a distributed ledger technology platform independent of the issuer.
(2) Issuance Size: The bond must have a minimum issuance size of HK$1 billion.
(3) Investor Distribution: The bond must be distributed to at least five investors unaffiliated with the issuer or the platform provider.
(4) Listing Requirements: The bond must be listed on either (i) The Stock Exchange of Hong Kong Limited (“SEHK”); or (ii) a virtual asset trading platform (“VATP”) licensed by the Securities and Futures Commission (“SFC”).

4. Reimbursement of Eligible Expenses

The scheme also provides reimbursement for various issuance-related costs, including fees paid to DLT platform providers, arrangers, legal advisers, auditors, accountants, and rating agencies, provided these service providers are based in Hong Kong and are independent of the issuer. Listing fees for SEHK or SFC-licensed VATPs, as well as lodging and clearing fees charged by the CMU, are also covered under the scheme.

5. Coordination with Green and Sustainability Bonds

For issuances classified as green, social, sustainability, or transition bonds, the DBGS may work in conjunction with the GSF Grant Scheme to cover issuance costs. However, issuers must ensure that the same expenses are not claimed under both schemes, as dual funding for identical cost categories is prohibited.

6. Application Process and Oversight

Applications for the DBGS are now open and will be accepted for the next three years. Detailed guidelines have been published by the HKMA, outlining the eligibility criteria, application process, and reimbursement procedures. The HKMA has also indicated that it will monitor market developments closely and may refine the scheme’s structure if necessary. All decisions regarding eligibility and subsidy amounts will be at the sole discretion of the HKMA.

7. Conclusion

The launch of the DBGS underscores Hong Kong’s commitment to advancing its position as a global leader in digital securities. By fostering innovation and promoting tokenisation technology, the scheme is expected to attract issuers and investors, contributing to the long-term development of the city’s capital markets.

Please contact our Partner Mr. Rodney Teoh for any enquiries or further information.

This news update is for information purposes only. Its content does not constitute legal advice and should not be treated as such. Stevenson, Wong & Co. will not be liable to you in respect of any special, indirect or consequential loss or damage arising from or in connection with any decision made, action or inaction taken in reliance on the information set out herein.

A. Introduction
The Securities and Futures Commission (“SFC”) has released a circular (the “Circular”) detailing expectations for licensed corporations (“LCs”) adopting generative artificial intelligence language models (“AI LMs”). While being supportive of the use of AL and AL LMs by LCs, the SFC also acknowledges that AI LMs are susceptible to risk and require necessary safeguards. In particular,  the uses of AL LM for providing investment recommendations, investment advice or investment research to investors are considered to be high-risk use cases.

B. Scope of the Circular
The scope of the Circular is intended to cover LCs offering services or functionality provided by AI LMs or AI LM-based third-party products in relation to their regulated activities, irrespective of whether the AL LM is developed by the LC itself, its group company, an external service provider or sourced from open platforms.

C. Core Principles for Managing AI LMs
The SFC emphasises four core principles to guide LCs in the responsible adoption of AI LMs:

1. Senior Management Oversight
Senior management is responsible for ensuring proper governance throughout the AI LM lifecycle, from development and deployment to decommissioning. They should establish effective policies, procedures, and internal controls to manage risks and oversee the implementation of AI systems.

Senior management should also ensure qualified staff from business, risk, compliance, and technology functions are involved in overseeing AI LM adoption. Staff should possess competence in AI, data science, and regulatory compliance to address risks effectively. For high-risk use cases, such as investment recommendations or financial advice, heightened governance and additional risk controls are required to protect clients and investors.

While LCs may delegate certain functions, such as model validation, to their group companies, ultimate responsibility for compliance with legal and regulatory requirements remains with the LC.

2. AI Model Risk Management
An LC should implement a robust AI model risk management framework to ensure AI LMs remain fit for purpose. Key measures include conducting thorough validation before deployment and when significant changes are made to the model’s design or inputs, testing the model’s performance across all processes, including input, output, and any related systems and regularly monitoring and reviewing AI LM performance to address potential drifts or degradations over time.

For high-risk applications, LCs should adopt additional safeguards, such as human oversight of AI outputs and testing for consistency across variations in input prompts. Comprehensive documentation of all testing, validation, and monitoring activities is required.

The SFC distinguishes between off-the-shelf AI LM products and models developed or customised by LCs. While off-the-shelf products also require proper model management, customised models demand more rigorous oversight.

3. Cybersecurity and Data Risk Management
AI LMs are susceptible to adversarial attacks, data breaches, and other cybersecurity threats. LCs should implement robust controls, such as periodic adversarial testing, encryption of sensitive data, and measures to prevent data leakage through browser extensions or user inputs.

To ensure data integrity, LCs should mitigate biases in training data and comply with data protection laws. Particular care should be taken to protect sensitive information, such as client data, from being inadvertently exposed or exploited through AI LM training or use.

4. Managing Risks of Third-Party Providers
The SFC advises LC to exercise due skill, care and diligence to assess third party providers’ expertise, controls, and risk management frameworks.

The LC should evaluate the whether the third party provider itself has an effective model risk management in place and if the performance of the AL LM is appropriate for the LC’s specific use. The LC should also assess the third-party providers’ data management and consider if a breach by the third party provider of applicable personal data privacy or intellectual property laws could have a material adverse impact on the LC.

LCs should also prepare contingency plans to address service disruptions or operational failures stemming from third-party dependencies. Supply chain vulnerabilities and data leakage risks should be carefully monitored.

D. Notification and Compliance Requirements
LCs intending to use AI LMs for high-risk applications are reminded to comply with the notification requirements under the Securities and Futures (Licensing and Registration) (Information) Rules. Notifications are required significant changes in the LC’s nature of business and types of services provided. Early engagement with the SFC during the planning and development stages is recommended to address potential regulatory implications.

The SFC expects LCs to review and update their existing policies to comply with the circular’s requirements. Although immediate compliance is required, the SFC acknowledges that some LCs may need time to fully implement the necessary measures.

E. Conclusion
The SFC’s guidance underscores the importance of balancing innovation with responsibility in adopting AI LMs. By implementing robust governance, risk management, and cybersecurity measures, LCs can harness the benefits of AI while safeguarding against potential legal, operational, and reputational risks.

LCs are encouraged to engage proactively with the SFC to ensure alignment with regulatory expectations.

Please contact our Partner Mr. Rodney Teoh for any enquiries or further information.

This news update is for information purposes only. Its content does not constitute legal advice and should not be treated as such. Stevenson, Wong & Co. will not be liable to you in respect of any special, indirect or consequential loss or damage arising from or in connection with any decision made, action or inaction taken in reliance on the information set out herein.

The Issuer is a state-owned company which is indirectly controlled by Xichang Finance Bureau and ultimately controlled by Xichang People’s Government. The main business scope of the Issuer includes building materials sales, scenic spot operation and maintenance services, urban transportation services, house rental and management services, travel services and other services.

Our team was led by Partner Rodney Teoh, supported by Associate Angela Lau, Paralegal Austin Kot (pending admission), Trainee Solicitor Trendy Leung and Paralegal Jay Lee.

Please contact our Partner Rodney Teoh for any enquiries or further information.

Ming Shing is primarily operated through their indirectly wholly-owned Hong Kong operating subsidiaries. They mainly engaged in wet trades works, such as plastering works, tile laying works, brick laying works, floor screeding works and marble works.

Our Partners, Hank Lo and Gordon Tsang, and Associate Ben Chan, acted as the Hong Kong legal counsel for the Joint Underwriters in the Nasdaq Listing and provided comprehensive Hong Kong legal services.

Please contact Hank Lo or Gordon Tsang for any enquiries or further information about this transaction.