Advanced technology, such as artificial intelligence (AI) can no doubt increase the competitiveness of businesses that use it, including the finance sector. But a smooth AI adoption journey requires not only technological know-how but also customer trust. But AI generates as much apprehension as it does anticipation and fear of its abuse is quickly growing. The benefits of AI may be stymied if consumer trust isn’t earned along the way.
Banks and insurance companies across the world have plans to accelerate the introduction of advanced technology. The Economist Intelligence Unit (EIU) interviewed more than 300 senior executives and C-suite leaders in marketing, information technology, customer service and finance in North America, Europe, and the Asia Pacific during the epidemic in February and March this year. Nearly 80 percent of the respondents say that unlocking the value of artificial intelligence (Al) is the key to business success.
This aligns with the Hong Kong Monetary Authority’s report on the application of Al in the Hong Kong banking industry released at the end of last year. It included an industry-wide survey that was conducted in Q3 2019 with local banks, industry associations, and FinTech companies. Almost 90 percent of the surveyed retail banks have adopted or plan to adopt AI applications.
The three most popular applications include customer experience, automation & quality control, and risk management. For example, banks will use Al to analyse customer data to offer personalised wealth management services. They’ll also trust AI to confirm customer identity for remote customer onboarding by reading customer information with AI. They can also use optical character recognition to process cheques, to respond to customer enquiries with chatbots and robotic process automation, and to use historical data to generate predictive models to conduct credit risk assessments for SMEs. Al also monitors IT infrastructure to prevent potential attacks.
After researching 300 global cases, PwC expects AI to contribute global economic benefits of US$15 trillion in 2030.
Holding AI back
On the other hand, however, the Hong Kong Monetary Authority’s study found that many local banks had reservations about the adoption of Al. The biggest concern is its black box thinking. Even if the results obtained by the AI algorithm are very accurate, its recommendations may not be comprehensible because its logic of analysis is not accessible to its users. It is contradictory to the trend towards transparency and mutual trust. Personal privacy issues are also worrying as personal data may be used for purposes unknown to the owner.
In an article in Hong Kong Lawyer, the official journal of the Law Society of Hong Kong, The Privacy Commissioner wrote last year that Al’s popularity had raised ethical and privacy concerns. For example, in the era of AI with widespread video cameras and sensor devices, individuals might have not been aware that their personal data was being collected or shared. They are rarely consulted on the collection. They don’t know how they are constantly recorded, analysed and classified by sophisticated data analytics. Regulations set in the past fail us. Personal data protection regulations created in the past are no longer adequate.
What’s a SAR to do?
This is a very challenging issue. Hong Kong’s regulators should consider following the European Union’s General Data Protection Regulation (GDPR), requiring companies to use the highest possible privacy settings when processing personal data. Users should have the right to request the deletion of personal data.
Hong Kong can refer to a pilot program called DEcentralised Citizen-owned Data Ecosystems (DECODE) in Barcelona, Spain, to use blockchain to record all activities in using personal data. Users have the right to decide what personal data is stored, how it is shared, and with whom. All of the proposed solutions can help to restore the public’s confidence in the technology so that companies can use IT to enhance service and competitiveness.
Dr. Winnie Tang
Adjunct Professor, Department of Computer Science, Faculty of Engineering; Department of Geography, Faculty of Social Sciences; and Faculty of Architecture, The University of Hong Kong