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HKMA Releases Report on AI Application in Banking

HKMA Report on AI Application in Banking

The Hong Kong Monetary Authority (HKMA) published a report titled “Reshaping Banking with Artificial Intelligence” on 23 December 2019, a recent press release reported.

The report is part of a series of publications on the study of the opportunities and challenges of applying AI technology in the banking industry.

This year, the HKMA commissioned a consulting firm to conduct a study on the application of AI technology in the Hong Kong banking industry.

The findings of the study are presented in the report, which summarises insights from academics and industry experts.

The report also shares the result of an industry-wide survey on banks, industry organisations and fintech firms conducted in Q3 2019, with one of the key findings showing almost 90% of the surveyed retail banks have adopted or plan to adopt AI applications.

To help the industry understand the risk and potential of applying AI technology, the report covers the latest development trends, potential use cases, status of AI development in banking, challenges and considerations in designing and deploying the technology, as well as the market outlook.

The Senior Executive Director of the HKMA stated that AI will bring profound changes to the way in which the banking industry operates. The appropriate adoption of the technology may have the potential to reshape banking in the future.

Understanding the technology and its implications from the outset is crucial to fully unleashing the power of AI. It is hoped that AI report, as well as the subsequent reports, will offer the industry some useful references for further adoption of the technology.

Among the many new technologies to have had an impact on the corporate world in recent years, AI looks to be a critical disruptor for the banking industry, the report states.

According to PwC’s AI Impact Index, which looks at 300 AI use cases around the globe, the technology could contribute US$15.7 trillion to the global economy by 2030, boosting the GDP of individual countries by up to 26%.

In its conclusion, the report noted that Artificial Intelligence is a term that has been in use for over half a century. Despite its familiarity, for much of its lifetime, this nascent technology has failed to live up to its billing. While computing power grew exponentially, advances in AI were modest and incremental.

However, the paper showed that, in the last few years, a number of critical factors have aligned and transformed a long-anticipated concept into reality.

Anyone who has used freely available online translation software in the last couple of years will have noticed the consequent and astonishing pace of technological progress.

This was brought about, firstly, by the transition from rule-based to non-rule-based learning, then through the development of complex algorithms and, critically, the ‘fuel’ of vast amounts of data to facilitate machine learning.

As a result, the basic building blocks, components and techniques enabling AI to support banking and other industries are now in place.

However, the ongoing technical difficulties of harnessing AI are now combined with other challenges. These include user acceptability, finding and retaining expert talent, integrating newly-enabled products and services into a well-established business strategy, and so on.

One of the most critical issues for financial institutions and any other organisation built on trust is the concept of ‘explainability’.

Encouraging familiarity with, and eventually confidence in, ‘black box’ processes is a daunting challenge from both a risk management and a customer experience perspective.

Despite this, the potential to dramatically improve customer experience, reduce costs and better manage risk, is something no bank can ignore. The drivers for AI adoption are just too compelling.

Moreover, the research cited in the paper highlights that there is also a high degree of ‘market pull’, as customers demand more personalised and relevant tools to manage their financial and other goals.

To fully unleash the potential of AI in the banking industry, best practices need to be leveraged and learned from. Hong Kong can develop into a leading AI hub by drawing on some of its core strengths, such as its deep and long-established expertise in banking and professional services.

However, other aspects of the city’s human capital will also need to be intensively nurtured. Few players in Hong Kong’s banking industry would claim to have a fully-fledged AI strategy or a thorough, all-round understanding of how the regulatory landscape will change because of AI.

For these and other reasons, knowledge-sharing of tried and tested use cases across Hong Kong’s banking AI community is essential.

This should encompass success stories, as well as stories of those that fell short, either technically or due to a lack of real demand.

In this way, Hong Kong’s financial institutions will be able to develop an industry-wide understanding of the rules of the road for this new technology.

OpenGov Academy

In line with smart nation efforts of encouraging AI technology adoption, OpenGov has launched its OpenGov Academy, in collaboration with AlphaZetta.

The OpenGov Academy facilitates and promotes AI masterclasses, workshops and customised courses that are conducted by AlphaZetta and supported by OpenGov.

This academy will feature masterclasses across various levels: C-suite, management, business, and, expert.

The classes have been created to impart understanding – taught in an intuitive, accessible way, keeping formulae and mathematics to a bare minimum and taking an innate, visual approach.

Data literacy, AI and data science, and strategic decision making with data are some of the classes offered by the academy.

For more information, visit: OpenGov Academy


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