WU started to handle Big Data and underwent digital transformation

Customer: Western Union

Industry: Finance

Solution: Big Data Managment

Technology: Big Data

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«We will continue to be proactive—anticipating, adapting to and addressing the ever-changing needs of our customers, always striving to stay one step ahead».

Hikmet Ersek, President and Chief Executive Officer

Business Need

Western Union has built significant scale in the money transfer business with 242 million consumer-to-consumer transactions and 459 million business payments in 2013 alone. The company faces increasing competitive pressure from emerging technology players. The company is transforming and focusing on developing an omni-channel approach that includes retail, web and mobile. Western Union wants to expand into new markets with e-commerce and other digital products with a goal of reaching customers with a more tailored and personalized experience.

At that time Western Union processed more than 29 transactions per second, on average, which generated a significant amount of structured and unstructured data that must be integrated from diverse sources (legacy, mobile and online data). The company needs to cost-effectively deal with this data complexity, while simultaneously scaling access, storage, and processing. Data scientists must rely upon the data platform to conduct statistical modeling and predictive analysis, systematically noting trends in sending and receiving behaviors.


Western Union built a data platform based on Hadoop (Cloudera) and Informatica Big Data Management. Western Union is one of a handful of very early adopters of Hadoop on such a global scale.


Due to the platform and effective performance of its solutions, data scientists and analysts are provided with reliable data. They analyze big data effectively, so that WU can introduce new digital products successfully. Also, this analysis can be implemented for decision-making process in the company.

Data scientists can rely on data when they are looking for insights. These insights can be used to develop personized offers for clients.

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