Fiserv has announced that the number of mobile bill payment transactions processed through its biller direct solutions and MyCheckFree website, a direct to consumer payment portal, tripled within the past 24 months, rising from about 4% of bill payment transactions to about 15%.
Biller direct solutions enable consumers to receive and pay bills directly at the company’s site, while MyCheckFree enables consumers to receive and pay bills from multiple companies at a single site.
“The rapid growth of mobile bill payments is having a significant impact on billers,” said Gwenn Bezard, Research Director, Aite Group. “Billers of all sizes and across all verticals are responding to deliver better mobile bill payment capabilities, with options such as mobile-optimized websites and even company-branded apps, as more consumers turn to their smartphones and tablets to conduct financial transactions.”
The Biller Mobile Bill Pay Benchmark Study commissioned by Fiserv indicates that billers are turning to the mobile channel to enhance and extend customer service (94%); increase paperless billing (82%), increase customer usage of self-service (76%) and meet customer demand (74%).
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