
Showing concern for consumers
The OFT has today issued a set of principles for businesses using continuous payment authorities (CPA’s). The concern is that many traders are failing to make clear to customers that they are being signed up for recurring payments.
Once agreed by a customer, a CPA allows a business to take a series of payments using a customer’s debit card or credit card without having to seek express authorisation for every payment. The OFT claims many consumers are unaware of their cancellation rights. As a result it has set out principle guidelines it believes businesses should apply.
For example, businesses should be fully transparent about terms before a consumer signs up to a CPA arrangement. Furthermore, it must ensure the consumer has given informed consent to the use of a CPA, and do not use ‘opt out’ provisions or other means to automatically assume the consumer has given consent. Providing adequate notice of any changes such as the amount or timing of payments as well as clear and prominent information on how to cancel a CPA is also suggested.
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