Big Data, the fuel for Digital Banks

Olivia Brookhouse    4 November, 2019

In 1981, Bill Gates said “640KB will be enough for anybody”. Surpisingly, it was hard even then, to imagine where we would be today; in a sea of data. Big data is fuelling the world of business, driving human decision making and building machine learning systems which have become essential components to success in the growing sector of digital banking, particularly in Monzo and Revolut. Big Data, as the name suggests, provides 1000’s of metrics which inform many real decisions, so how has Data ensured the continuing success at these innovative companies?

Monzo

Monzo, founded in 2015 by 5 young men who had previously worked for Starling Bank provided a truly unique banking experience than any on the market at the time. Monzo is valued at $2.5 billion, thanks to its effortless user experience which customers can access through the app and recently developed web. The service facilitates many processes such as bill splitting, expense tracking by activity, mobile to mobile repayments, direct debits and many more functions. Big Data and Artificial Intelligence play 2 crucial roles in the daily success of the bank, improving the customer experience and informing internal processes which inturn help shape the direction of the company.

Neal Mathia, Monzo Data Scientist

Because 3,000 people join Monzo every day, it is vital the app can provide accurate and timely responses to all queries. Therefore, Big Data and AI are particularly important to ensure automated help content is accessible, comprehensive and timely. With the use of word embedding and document similarity, algorithms can compare word content and phrase patterns to detect queries of a similar nature and help future customers find answers. Big Data facilitates this self-serve data analytics as machine learning depends on diverse data to improve. Monzo uses Big Data to analyse card usage, demographics and many more data points to provide insights to “enable better decisions faster”, improving its operational efficiency.

Revolut

Revolut, Monzo’s fintech twin, also relies on Big Data to fuel its decision-making processes. Launched by Nik Storonsky and Vlad Yatsenko in July 2015, Revolut had a clear goal: to transform the financial sector. Users can open a current account through the app in under a minute, helping customers avoid long lines in banks. They can pay overseas in 150 currencies without charges and hold and exchange 24 currencies. Even more, its free to send domestic and international money transfers with real exchange rates, a feature which Monzo lacks. Revolut, like Monzo mirrors many unique qualities, easy and functional banking in the palm of your hand.

Revolut is extremely data-driven, and we needed a universal database that could keep up. Moreover, reports that previously took hours to generate can be loaded in seconds. We have a much better grasp of our company KPIs and industry trends.

Abhi Thanendran, lead data scientist at Revolut.

Like Monzo, this has only been possible due to data storage capabilities. Revolut uses Exasol’s in-memory database as its central data repository. An Exasol cluster is now incorporated within the Google Cloud Platform, providing a central repository for all data requiring analytics throughout the business.

LUCA

At LUCA, we work with companies in the financial sector throughout their transformation process towards becoming data-oriented organizations with specific solutions for each business area and issue. In a highly competitive environment, differential data, Big Data, Artificial Intelligence and IoT have become essential allies for companies in the financial sector. Check out our industry page to find out more.

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