The new enhancements include a Merrill Edge app for Android, remote check deposit functionality for iPhone, bill pay functionality on the iPad and a new Investment Product Education Centre on MerrillEdge.com. (view press release)
The Merrill Edge Android app enables users to check investment balances, place trades, research investments and transfer funds between linked banking and investment accounts. Customers with an iPhone can deposit checks into their investment account remotely by photographing and submitting the check from the phone and iPad users can schedule and manage online bill payments through their tablet. The Investment Product Education Centre provides access to news, research reports, education, articles and analysis and allows customers to research stocks, options, ETFS, mutual funds and fixed income products.
“The November Merrill Edge Report indicated that a quarter of mass affluent respondents are avid users of mobile banking, and use it to check account balances, transfer funds and pay bills,” said Merrill Edge executive, Alok Prasad. “We continue to invest in new tools and enhancements to allow customers to access and manage their investment accounts anywhere anytime.”
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