
Praised for mobile banking apps
Citizen Bank’s mobile banking apps for iPhone and Android have been named the ‘best integrated apps’ in the industry by Javelin Strategy & Research, following a customer ratings review in the Apple App Store and in Google Play (view press release). The average rating was 4.25 out of 5 stars, tied only by USAA.
Earlier in the year, Citizens Bank added new features to its app for iPhone users, and introduced a similarly fully featured app for Android users. From October 2011 to October 2012, the apps have seen use by the bank’s active mobile customers grow by around 130%.
“We are honoured to receive this recognition following our recent enhancements to Mobile Banking for iPhone and our launch of the Citizens Bank app for Android,” said Michael Cleary Executive VP and Head of Consumer Banking Distribution for RBS Citizens Financial Group. “This finding is especially gratifying because it is based directly on what our customers are saying in their own reviews. Increasingly, our customers turn to their mobile devices to do their banking, and we are committed to continuing this level of investment to ensure we will continue to meet the needs of our customers.”
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