are revolutionizing the way people use and spend money. China has leapfrogged
other markets when it comes to cashless payments, primarily through mobile
phone payment systems like Alipay and WeChat Pay. The success of the cashless
nation has received attention from other countries, including Singapore who is
replicating digital payments best practices from China as part of its Smart Nation initiative, a drive for
the digital transformation of government.
CLICK TO TWEET: CommScope's Gavin Milton-White explains how big data is changing the e-payment world.
The e-payment race
ago, Singapore announced the launch of a single standardized SGQR
that will replace the plethora of QR (quick response) e-payment codes currently
in the market, demonstrating its move towards a cashless society. Combining
multiple e-payment solutions into one, the SGQR code will put consumers and
businesses on a unified payment system.
Benefits include faster moving queues, quicker processing of payments and
new opportunities for non-banking players and fintech organizations, according
to Channel News Asia.
The race is
on for India too. The demonetization of 500 and 1000-rupee currency notes is forcing
citizens to access a formal banking system, accelerating India’s digital
economy. A new transaction system through Unified Payments Interface
instant fund transfer between two bank accounts on a mobile platform. The
beneficiary’s bank account details are not required, making this a giant leap
into e-payment. Digital transactions could reach USD 1 trillion annually in the
with four out of every five transactions being made digitally by 2025.
digital payment brings convenience, organizations must continue to address
challenges around data privacy and security (cybercrimes).
Data is changing e-payment
Big data refers to a process that is used
when conventional data extracting, and handling techniques cannot uncover the
insights and meaning of the underlying data.
While a unified e-payment
system aims to make payment easy, convenient and accessible for consumers and businesses,
a consolidated payment landscape would mean that more data is needed for
aggregation and analysis, in the case of Singapore and India. Data mining and
data analytics help business to transform large volume of data into insight for
smarter decisions. The financial sector is turning to predictive and deep
learning to combat fraud and risk.
As organizations turn
to digital payments to offer a better customer experience, they must ensure
they have a reliable and fast network coupled with the right data
infrastructure. Financial institutions
and their partners must take a holistic view of their network infrastructure
and ensure the potential of data is unlocked for better decision-making in this