Financial Institutions cannot work without data and require them in order to keep up with changing customer expectations and comply with legal regulations. JoAnn Stonier, Chief Data Officer of Mastercard, shared how her company deals with this challenge, which include migration to a multicloud infrastructure, careful consideration of data quality and security, and continuous improvement with advanced analytics tools.
Citi, another multinational financial company, is currently tackling the issue of data sprawl. Citi’s main focus is to consolidate the data from multiple legacy systems and make sure that the tech stack remains as lean as possible. Additionally, the company will use external data providers such as Experian, FICO and TransUnion to gain insights. To further improve data efficiency, Citi has taken up the use of open-source tools such as PySpark and Python. The company also has its own in-house analytics tool which creates a self-service search engine for all the company’s cataloged data, allowing employees to remove the need for assistance of data experts.
Mastercard is a multinational financial services corporation connecting consumers, financial institutions, merchants, governments and businesses around the world. It provides services in over 210 countries and processes 125 billion transactions annually. It partners with banks and merchants to provide a secure exchange of goods and services.
JoAnn Stonier is the Chief Data Officer of Mastercard. She has over two decades of experience in data and analytics and has worked at Mastercard since 2017. With her expertise and Mastercard’s commitment to innovation, she has helped modernise the company’s data collection, storage and analysis processes. Her goal has been to ensure that data strategy and business strategy go hand in hand and that the data used is veracious and appropriate for the task. She has also led Mastercard in developing its very own Security Operating Centre which monitors the company’s services 24/7 to maintain security and protect against bad actors.
