American Express: Analysis of Big Data Opportunities and Challenges

This report provides an analysis of the application of big data within American Express (Amex). It highlights the opportunities, such as fraud detection, new customer applications, and improved customer and merchant experiences, which are driven by the use of predictive analytics and machine learning. Amex leverages big data to analyze trends, retain customers, and maintain merchant relationships through targeted marketing. The report also explores the challenges Amex faces, including a scarcity of data scientists, organizational adaptation to change, and the need for appropriate infrastructure. These challenges involve issues related to employee retention, the establishment of a data-centric culture, and the implementation of effective data processing systems. The report references insights from various sources to provide a comprehensive view of Amex's big data journey.

BIG DATA

Opportunities of Big Data in Amex
Amex has been a major edge of technology and data science. The big data provides the unique
and valuable data sets to help in making their products and services more relevant for their
customers. Apart from this, there is a support between the card members and the merchants for
managing the risks. There has been a major improvement in speed and performance with huge
proprietary asset to deliver the innovative products in payments and commercial space that helps
in providing value to the customers (Cameron, 2013). The focus is on the analysis of the
different trends that includes the information for a specific level on cardholders. The algorithms
are built for providing a better offer which is for attracting and then retaining the customers as
well. There are use of the big data setup and the other models of learning that is able to produce a
higher level of discrimination, when there is a need to understand about the customer behavior.
Through this, there are predictive models which are able to help in taking different marketing
measures for retaining the customers (Liyakasa, 2017). Amex has been able to analyze the trends
to retain customers and then leverage the information which is mainly to maintain the
relationships with the other merchants. This is done through using the target marketing method.
Hence, the company has been able to focus on:
a. Fraud Detection: This is for detecting the fraud transactions and the machine learning
makes use of the different inputs or the spending details to flag the transactions.
b. New Customer Applications: The direct mail campaigning is done through reducing
costs.
c. Improved customer and merchant experiences: Amex works on providing credits to
customers with better services for merchants to process transactions for establishing
connection on a personalized offers.
Challenges of Big Data in Amex
The Big Data has different problems and some of the challenges are the major scarcity of the
scientists, proper adaptation of the organization to the changes and then setting the right
infrastructure as well (Moreno-Munoz, Bellido-Outeirino, Siano, and Gomez-Nieto, 2016). The
scarcity of big data is mainly due to the lack of training in the organization and there is a need to
ensure that the recruits are able to understand the context for business setup. There are problems
of retention of employees from the other competitors. The organizational forging data centric

internal culture is a major hurdle, where the old processes are habituated to be obliterated. There
are challenges to change through learning and improvement. The setting upon the right
infrastructure with Amex includes the data back-end processing which is incapable to handle the
tall orders of analytics (Randy, 2016). The company needs time to settle the Hadoop Mapr with
the ideal data processing infrastructure. There are challenges to reap the returns from the strategy
and to meet the industry standards of benchmarking.
References
Cameron Nadia. “How predictive analytics is tackling customer attrition at American Express”.
2013,
https://www.cmo.com.au/article/458724/how_predictive_analytics_tackling_customer_attrition_
american_express/
Liyakasa Kelly. “American Express Expands The Ways Marketers Can Use Its Cardholder
Data.” 2017. https://adexchanger.com/ad-exchange-news/american-express-launches-data-
business-dubbed-amex-advance/
Moreno-Munoz, A., F. J. Bellido-Outeirino, P. Siano, and M. A. Gomez-Nieto. "Mobile social
media for smart grids customer engagement: Emerging trends and challenges." Renewable and
Sustainable Energy Reviews 53. 2016: 1611-1616.
Randy Bean. “Inside American Express' Big Data Journey”. 2016.
https://www.forbes.com/sites/ciocentral/2016/04/27/inside-american-express-big-data-journey/