Creating an inclusive cashless society
CONVINCING Singaporeans to embrace a cashless society is a crucial step for Singapore's ambition to be a smart nation.
The concept of a cashless society is not new. Back in 1961, aerospace engineer Simon Ramo gave a lecture that exhorted the benefits of going cashless. He could see how information could change the way people would live their lives and provide a better understanding of payment patterns and credit worthiness.
Dr Ramo was ahead of his time and his call was ridiculed by his peers. Financial institutions were unwilling to share information for various security and commercial reasons. Even today, decades later, there remain barriers to creating a truly cashless society globally and in Singapore.
Singapore does not have a truly unified payment system, which makes it painful for consumers to go cashless. AliPay and WeChat Pay are the two dominant forces in China. Sweden has Swish, created by a consortium of Swedish banks, which provides free transfer of cash between individuals. Small businesses and even churches have jumped on the Swish bandwagon.
For merchants in Singapore, the transaction cost of going cashless ranges from 1 per cent to 3 per cent, which explains their preference for cash, though individual transfers are now free and easy with the PayNow platform. Notably, the Singapore Fintech Festival last November saw PayNow linking up with Thailand's equivalent PromptPay system, and the debit retail payment system NETS tying up with its Indian counterpart, the National Payment Corporation of India.
These cross-border collaborations are important for their larger impact of building an Asean-level framework, and directly benefitting consumers on the street through cheaper and faster transfers. They underline the government's acumen at the strategic level.
The government has also sought ideas from merchants on consolidating the fragmented local payments market - and rightly so. Some prominent players have risen to the call but this remains work in progress for now.
A fragmented e-payments landscape is a headache for consumers. Ask anyone who has been stuck at a carpark gantry because they did not have the correct type of cash card, or a traveller in China who has to figure out how to sign up for Alipay or WeChat Wallet. China has a huge domestic market and population, but with Singapore's large tourist and foreign workforce population - any system we implement needs to allow for easy integration for visitors as well as ensure that the old, disadvantaged and underprivileged are not left out. This would preclude any system that is tagged to a bank account.
Underpinning a cashless society, in my opinion, would be a "Super Identity" - a digital identity profile that allows an individual to be plugged into a cashless system without hassle. Singapore is well placed in this regard as it has an established national ID system as well as extensive credit bureau and financial profiles held by companies such as DP Information and the local telcos.
POWER OF MACHINE LEARNING
The government is also actively looking at ways to improve this so that people can safely and conveniently transact with government and private vendors. Visitors are also easily identified by their passports numbers, which can be supplemented by alternative data from their telco, e-commerce and social behaviour - if they allow access.
This Super ID can underlie the e-wallet and transactional platforms, reducing friction by enabling trust between merchants and consumers. It will allow for different systems to speak with one another, reducing monopolistic networks from forming - which is a concern of privacy and rights activists around the world.
Fraud and identity theft is a concern when it comes to cashless payments, and there have been issues in China where enterprising criminals sneakily replace merchant QR codes to divert payments. However, advances in fraud and identity protection technology, powered by AI will help circumvent these concerns.
Artificial intelligence and machine-learning enhances our ability to process and analyse big data. Within real time fraud detection tools are used to detect whether a transaction is legitimate or fake in an undiscernible moment. They do so by a variety of ways, including analysing the device ID, the individual's usage data, and whether it all matches.
To give an example of the power of machine learning and alternative data in credit and financial access, our micro-analytics division was able to know which pre-paid customers were cut off from top-up vendors and stores by the recent devastating floods in Sri Lanka. The team could issue free credits to these in need, so that they could call for help or let their loved ones know that they were ok.
China and Sweden, two countries not usually spoken in the same sentence, have both shown the way in this field. Firstly, payment infrastructures and systems must be convenient for widespread adoption by customers. Secondly, businesses will always look for cost-effective measures to accept payments. And finally, a truly smart nation must surely know to capitalise on cashless payment as it is a sweet spot for both consumers and businesses.
