Partners from our global FinTech team flew in from Hong Kong, Vancouver, London, Dallas, Johannesburg and Melbourne to join our Singapore team at the SFF 2019 (Singapore FinTech Festival) 11-13 November. The SFF is the world’s largest annual FinTech conference, bringing together over 45,000 FinTech enthusiasts to explore, collaborate and discuss the future of FinTech. We have provided below our key takeaways on three of the hot topics which provoked considerable interest and debate:

Spotlight on supply chain and trade finance

Trade finance market participants’ biggest complaint is – quite simply – paper. Trade finance transactions have onerous documentation requirements involving multiple parties – importers and exporters need to prepare and submit multiple documents like contracts, bills of lading, packing lists and customs declarations, and wait for them to be checked and processed by banks (manually in many cases). The process is lengthy, costly and carries a high risk of fraud and errors. Market participants are increasingly investigating the applications of emerging technologies to try to reduce or eliminate some of these issues.

During the SFF, two key themes prevailed about the adoption of innovative technology in trade finance and in a wider supply chain context:

  • The importance of collaboration with regulators in launching these solutions should not be underestimated, particularly given the multiple participants and complex transaction cycles (some of which in both cases are regulated). Although the most active adopters of innovative technology in the trade finance space are the banks, we are also seeing central banks becoming more active in collaboration with the private sector. Two examples are: (i) the Global Trade Connectivity Network – a collaboration between Monetary Authority of Singapore and the Hong Kong Monetary Authority using blockchain to digitise bilateral trade; and (ii) Masterchain in Russia – a DLT trade finance collaboration between the FinTech Association, the Russian Central Bank and a number of major commercial banks.
  • While DLT / blockchain solutions are often front-of-mind, this is not the only disruptive technology being explored in trade finance and the supply chain world more generally. We discussed an increasing number of use cases involving smart contracting and internet-of-things technology and artificial intelligence. For example, in the food and beverage industry, internet-of-things sensors are being used to track goods from their original source to the consumer. Sawtooth for example, tracks the journey of seafood from ocean to table, recording various characteristics like temperature and movement along the way. DLT and smart contracts are being combined to combat the counterfeiting of luxury goods with on-demand manufacturing (a limited number of goods are made to order, with the order information verified on the blockchain and smart contract technology triggering the production). Production records on DLT platforms also enable consumers to confirm that what they are purchasing is legitimate. These examples also illustrate the use of disruptive technology to promote ethics, sustainability and transparency in trade.

Artificial Intelligence and Financial Services

There was certainly momentum around the launch by the Deputy Prime Minister of Singapore of Singapore’s National AI Strategy on the closing day of SFF, with a view to Singapore becoming a leader in developing and scalable AI with impactful solutions by 2030. The strategy encompasses 3 core principles – take a human centric approach; stay open and connected; and build an AI ready population and workforce. A number of projects were announced in this space. Also, on the first day of SFF MAS announced it would offer more funding for FinTech initiatives with areas including cyber and AI. This is a further step ahead in Singapore’s AI journey, where we have already seen the MAS earlier this year focus on the broadening and deepening of the application of AI in the financial services sector, with the appointment of a specialist adviser on AI to the MAS, the set-up of the AI Development Office within the Fintech and Innovation Group, with a view to developing AI strategy, facilitate AI projects and build up AI capabilities. The MAS has also recently launched the AI and Data Analytics grant ($27 million) to support the AI ecosystem, with 2 tracks the FI track and the Research track. It published the FEAT Principles, to ensure fairness, ethics, accountability and transparency are all considerations when using AI. This is further supported by the AI Framework recently issued by the Singapore data protection regulator, to ensure Singapore takes a holistic, ethics driven approach to managing risk of deploying AI solutions.

Similarly, other Asian jurisdictions are taking a more active interest in the use of AI in the financial services space. The Hong Kong Monetary Authority, for instance, recently conducted a broad survey into the deployment of AI by licensed banks and what the roadblocks to further adoption are. In addition, it issued guiding principles that banks under its supervision should follow when implementing AI solutions in their business models.

We also discussed with our clients the relationship between AI and Machine Learning. Machine learning is one type of AI, and has risen to prominence over the last decade due to three factors: vastly increased availability of data; increased computer processing capability; and research advances in machine learning, in particular, deep learning, which involves multiple machine learning processes running in parallel. Not all application domains have sufficient quantitative data for data-driven machine learning methods to work, and so there is still a role for traditional model-driven approaches to AI to work. Discussion also centred on issues of bias and of automated learning of human norms, sentiments and intentions. Norms and sentiments can currently be learned, but the accurate machine assessments of the sincerity of human promises and intentions is still decades away.

We had good discussions regarding ethical issues involved in implementing AI and many discussed the need to closely analyze ethical issues associated with the implementation of AI. The ethical analysis is distinct from an analysis of whether something is legally permissible or impermissible. A topical issue concerns legal and moral liability in cases where AI decision systems make errors or harm others. It is likely that courts will undertake investigations into the supply chain for AI systems for instance, investigating programs, programmers and their trainers and the writers of program specifications.

There are very differing opinions on what AI would mean for the quality of life, with attitudes ranging from optimism that it would improve living standards and individual happiness to pessimism that it could worsen the human experience.

Our global FinTech team will next be heading to Consensus at New York FinTech week, 11-13 May 2020. In the meantime, catch up on the latest FinTech hot topics and read our thought leadership papers on our FinTech hub, hosted by our NRF Institute: Register.

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