
Big Data initiative
The Western Union Company has announced an internal Big Data initiative designed to help define and capture growth opportunities within the company’s digital, retail and stored value businesses.
Working with TIBCO Software Inc., Western Union will leverage internal Big Data analysis to anticipate consumer trends, and ultimately customize the company’s customer engagement strategies according to an individual’s unique needs. In addition, the company will work with TIBCO to streamline the systems integration process for Western Union’s Global Share stored value platform.
“We manage a considerable amount of data—last year alone we completed more than 231 million consumer-to-consumer transactions and 432 million business payments,” said David Thompson, executive vice president, global operations and technology, chief information officer, Western Union. “Big Data analysis of our information will increase Western Union’s productivity and support innovation by capturing the right information, at the right time, so we can act on it in a proactive manner.”
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