
Powering Agricultural Bank of China’s payment processing and AML systems
ACI Worldwide, a provider of payment systems, has made public details of an agreement made earlier this year with Agriculture Bank of China (view press release). Through the deal the bank will implement ACI Money Transfer System and ACI Proactive Risk Manager as its wholesale payment processing and anti-money laundering (AML) solution to assist with its expansion into the US market.
The Money Transfer System is designed to help advanced payment management, execution and streamlined banking operations. It also allows global processing needs to be centralised in a single location or distributed via a configurable network. In addition, the Enterprise Sanction Filter of the solution has been created to provide a set of services which position banks to maintain continuous regulatory compliance. The Risk Manager is a financial crime management solution which aims to help card issuers, merchants, acquirers and financial institutions combat fraud and money-laundering schemes.
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