As regulators in mainland China, Hong Kong and neighbouring jurisdictions push for more frequent and granular reporting, firms face greater challenges extracting large volumes of high-quality data, creating pressing demand for regulatory technology (RegTech) solutions.
In the wake of the launch of Europe’s AnaCredit initiative in 2011 to enhance the collection of granular loan and borrower information, Asian authorities have worked to establish new reporting standards.
‘Integrating new RegTech tools with existing systems is a significant undertaking’
The Hong Kong Monetary Authority (HKMA)’s Granular Data Reporting programme, for example, standardises transactional data collection from financial institutions on mortgages, corporate loans, interbank lending and debt holdings. Launched in 2019 as a residential mortgage and corporate loan pilot, it has since expanded to cover 50 banks.
Tightly regulated
In mainland China, the financial sector is tightly regulated by key agencies including the China Banking and Insurance Regulatory Commission, the China Securities Regulatory Commission and the People’s Bank of China, which collects granular data from financial firms across areas like loans and deposits to monitor risk and stability.
‘Not only do banks have to ensure they can compile the necessary transaction-level data sets, [but they also need] to deal with questions from regulators who have aggregated the granular data, comparing it to other data sources,’ says Tom Jenkins, head of financial risk management at KPMG China.
Jenkins cautions that unless banks adopt technologies, ‘they will be one step behind regulators who are already using these techniques’.
Adapting infrastructure
In light of the evolving landscape, some large regulated firms opt to build extensive in-house compliance capabilities.
‘If the financial institution is big, it may wish to implement the RegTech internally over time without sharing trade secrets with integration partners or third parties,’ says Jack Poon, professor of practice (fintech and entrepreneurship) at The Hong Kong Polytechnic University.
‘One key area where RegTech firms can differentiate themselves is in supporting local languages’
To balance technical requirements with ease of compliance, the HKMA has developed rules and more detailed guidance with banks to address their concerns, such as the resources and time needed to update legacy systems.
But these systems often lack the agility required, says Poon. For example, legacy data in non-machine readable formats cannot be easily updated; simply digitising paper through optical character recognition is prone to errors.
‘Integrating new RegTech tools with existing systems is a significant undertaking,’ says Isabel Shi, founder and CEO of Bitrace Tech, a Hong Kong-based RegTech company. Financial institutions must decide ‘whether to quickly adopt new RegTech tools to keep pace or wait until regulations are more defined before taking action’.
As Basel IV capital requirements continue to be phased in across Europe and other major banking jurisdictions, financial institutions increasingly look to RegTech solutions, applying artificial intelligence (AI), advanced analytics and automated reporting tools to more easily collect, process and generate the heightened volumes of risk and capital data required.
Customisation constraints
But a major implementation roadblock is the lack of standardisation. ‘When regulated licensees [operate] within the same industry and provide similar services, their processes may differ for various reasons,’ says Poon.
A case in point: a brokerage firm focusing on institutional investors is likely to have very different onboarding and trading requirements than one focusing on retail investors. This creates a need for high customisation, creating higher customer acquisition costs and longer implementation timelines for third-party RegTech providers, potentially rendering some solutions infeasible.
Regulatory expertise is another barrier, as providers need proficient knowledge of each jurisdiction’s regulations, says Poon: ‘A provider familiar with regulation in mainland China may have to re-establish its regulatory expertise in Hong Kong.’
Similarly, while Hong Kong and the US both require electronic reporting, only the US uses a standardised XBRL format, hampering interoperability, according to Poon.
In a white paper, KPMG pointed out that data privacy and sovereignty also complicate RegTech’s adoption. As Hong Kong financial institutions expand into the Greater Bay Area, evaluating any crossborder data transfers in transnational operations is more important than ever.
‘One key area where RegTech firms can differentiate themselves is in offering the ability to support local languages and host data in local jurisdictions,’ says Jenkins.
Supporting guidance
On the regulatory front, the HKMA has taken steps to bolster RegTech adoption in the banking sector. Following a 2020 consultancy study that identified constraints around budget, capabilities and tailored solutions, the HKMA developed a two-year promotion roadmap to promote RegTech, including the FiNETech platform that brings together 100 banks, securities and insurance companies for sharing knowledge.
‘Both the rules and the supporting guidance are formulated with extensive consultation with the industry to ensure that they are appropriate to banks, having regard to local circumstances as well as their implementation and compliance challenges,’ an HKMA spokesperson tells AB. According to the HKMA, 90% of banking institutions in Hong Kong have now adopted RegTech for credit, liquidity, operational and compliance risk management.
RegTech plays a big role in enhancing know-your-customer (KYC) and anti-money laundering (AML) procedures for many firms, says Shi. These solutions use AI and big data to analyse more external data sources like blockchain, real-time payments and social media.
‘Regulatory normalisation and refinement are inevitable trends’
Meanwhile, AI comes into play in several ways. ‘Transaction monitoring uses AI to detect anomalous transactions with fewer false positives and identify new money-laundering patterns,’ says Shi. ‘Predictive risk modelling with AI [forecasts] specific regulatory risks, and reporting automation ensures institutions meet deadlines while reducing administrative costs.’
Market nuance
RegTech solutions must account for each market’s regulatory nuances, says Penny Chai, vice president of business development, APAC, at verification platform Sumsub.
‘Sumsub’s solutions are designed to comply with the HKMA regulations, which require financial institutions to conduct thorough KYC and AML checks during customer onboarding,’ she says. ‘Our local data processing capabilities also align with the Personal Data (Privacy) Ordinance in Hong Kong.’
As financial innovation evolves through areas like internet finance and cryptocurrency, Shi believes RegTech’s core competitive edge lies in accumulating new data sources like blockchain and developing stronger risk identification and criminal behaviour detection models. Bitrace Tech, for its part, is exploring investigative approaches in AI models to better prevent risks.
‘Regulatory normalisation and refinement are inevitable trends,’ says Shi. ‘To meet compliance requirements, financial institutions need to enhance real-time capabilities, automation and intelligence in their processes.’
More information
Watch our sessions on technology at our annual conference, Accounting for the Future. Register to attend any or all of the sessions live (26–29 November) or to watch on demand – and earn up to 21 free CPD units.
