The development of m-wallet technology is being hindered by a number of ‘hidden controls’ which remain for the most part unexplored in the public domain, according to Mobey Forum’s latest white paper (view press release). The white paper, dubbed ‘Mobile Wallet: The Hidden Controls’, takes a look at the future and considers the external forces that will dictate how consumers and merchants engage with m-wallet technology in their day to day lives. The paper defines and analyses a series of ‘hidden control points’ which map the commercial areas where stakeholders will compete to influence both acceptance and adoption of m-wallet technology.
“As the first wave of mobile wallet solutions start to appear, the market’s attention remains fixed on mobile wallet apps and the devices where they reside,” said Amir Tabakovic, Head of Market Development at PostFinance and Chair of the Mobey Forum Mobile Wallet Taskforce. “We think this is unbalanced – the mobile wallet ecosystem is highly complex and its component parts are interdependent. The market’s failure to adequately consider the external forces influencing the mobile wallet is preventing the technology from fulfilling its full potential.”
The paper is the third in a series of Mobey Forum m-wallet white papers.
Whitepapers
Related reading
Central banks best suited to issue digital currencies
By Aaran Fronda A recent report by the Official Monetary and Financial Institutions Forum (OMFIF) said that central banks rather than private ... read more
Instant payments: innovations inbound for corporates
In 2020, instant payments look set to continue their current trajectory to become the biggest trend in payments. While these schemes already offer numerous benefits to corporates, leveraging innovations such as APIs and request to pay will go some way to unlocking their full potential, argues Michael Knetsch
Obstacles exist for banks to meet ECB’s instant payments goal
The cost of joining instant payment platforms will be one of many hurdles banks and payment services providers must overcome to meet ... read more
Banks must be aware of “biases” in data used to train ML models
Financial institutions need to be conscious of biases in the historical data that is being used to train machine learning (ML) models, ... read more