Overhauling its iPad payment system
Square is cutting short its New York taxi trial. According to reports, Square pulled the plug as its attempts to overhaul its iPad-based card payment system to meet new rules. In a letter sent last week to the Taxi and Limousine Commission, Square indicated that it needed to overhaul its payment system to adhere to the commission’s policy on credit card payments in cabs
Under an agreement with the New York Taxi and Limousine Commission (TLC), Square has been running a small-scale trial, involving around 15 cabs, for the past few months. The system consists of an iPad fitted with a card reader in the taxi partition and an iPhone in the front, enabling customers to pay their fare with a swipe.
“Square has determined, in light of developments in prospective taxicab regulations in New York and other markets, and based on what we have learned conducting the Pilot Program to date, that we wish to pursue a different hardware and software solution,” the letter said.
The agreed 45 day notice period has been waived by the TLC while those taxi drivers taking part in the scheme will be reimbursed. Square will also pay for retrofitting cabs with technology from VeriFone or Creative Mobile Technologies, the two incumbents.
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
