JP Morgan Treasury Services launches ACCESS mobile banking platform
JP Morgan Treasury Services today launched its new m-banking ACCESS platform in Asia Pacific. The platform allows account holders to check their balance and recent transactions from their smartphone or tablet device. The platform is currently available in Australia, New Zealand, Indonesia, Japan, Singapore and Thailand and is expected to be introduced to other key Asian markets later this year.
The ACCESS mobile platform allows clients to view multi-currency cash balances, transaction details and alerts for JPM ACCESS and third-party bank accounts in core Asian markets and worldwide. It also includes a ‘Quick decision’ feature which enables account holders to forecast cash positions based on planned transactions and target balances. Customisable business alerts are also available.
The platform’s security features include secure encryption and secondary authentication protocols, the ability to deactivate if lost or stolen and the option to erase screen if the application is left inactive for a while.
Various other enhancements are planned including wire payments approvals and multi-language navigation in Chinese, Japanese and Spanish.
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
