The sandbox was created to answer the questions raised about the opaqueness of the processes involved in machine learning and artificial intelligence.
Hong Kong’s financial services industry has raised concerns about the use of technology such as machine learning and artificial intelligence as part of regulatory compliance efforts, as these measures will have the effect of reducing the ability of these institutions to meet their accountability commitments, to customers as well as regulators, according to a recent report.
The concerns come amid a push by the Hong Kong Monetary Authority to facilitate the wider adoption of regulatory technology, or regtech. The deputy chief executive of the HKMA, Hong Kong’s de facto central bank, introduced four regtech initiatives last week during the annual conference of the Hong Kong Institute of Bankers.
The increased use of AI and machine learning creates challenges for banks, wherein they must account for decisions made by these technologies. The use of regtech could reduce their ability to be accountable for the decisions made.
The head of APAC financial crimes, analytics and intelligence at a network that enables financial institutions worldwide to send and receive information about transactions in a standardised environment said that the outcome of a bank’s internal model will dictate how it, for example, off-boards certain types of customers even before they have conducted any financial crimes.
The expert stated that he would like to see how regulators will address a bank off-boarding a certain profile of customers after their internal model has dictated that they are beyond the bank’s stated risk appetite.
Deep learning, which uses sophisticated mathematical modelling to process data in complex ways, offers few clues on how it arrived at a conclusion. The expert said that such lack of transparency was a “pain point” regulators would have to accept with regard to regtech.
In perhaps an admission of the challenges that lie ahead, the deputy chief stated that it is not technology at any cost. Financial institutions cannot outsource the responsibility to technology firms – authorities expect banks to understand why a machine makes the recommendations it does.
To help develop a regtech ecosystem, the HKMA will open a fintech “supervisory ‘sandbox’ to regtech projects or ideas raised by banks and technology firms, expected to be effective soon.
The sandbox – a highly controlled environment used to test unverified ideas – will allow the banks and their technology partners to conduct pilot trials of newly developed technology, without the need for full compliance.
The development and use of regtech by banks to achieve regulatory compliance and automate risk management has grown in recent years. The use of regtech for surveillance, in particular, has grown rapidly as part of anti-money-laundering and anti-terror financing measures.
The HKMA initiatives will also spearhead the use of regtech for prudential risk management, as well as the use of technologies related to machine-readable regulations and supervisory processes and activities.
The deputy chief said that the number of suspicious transactions reported by Hong Kong banks had grown on average by 40 per cent annually over the past five years; some banks were using machine learning and artificial intelligence to help detect suspicious behaviour and patterns, which had freed up analysts to focus on high-risk cases.
This, thereby, enhances the overall effectiveness and efficiency of banks’ transaction monitoring processes.
The chief executive and managing partner at consultancy firm said that the industry did welcome the HKMA’s exploration of machine-readable regulations.
Machine-readable regulations help banks automate the interpretation of regulatory requirements. If regulators provide two to three pages of guidelines, on what regulations mean that would help a regtech provider understand how the regulations are going to work.
In the CE’s words, a regulator’s job is to set the tone and make regulations as clear as possible.
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