At Tranglo, we process billions of dollars in cross-border transactions every year. Single and mass payouts go through our system rapidly, enabling quick payments around the world. The sheer amount of information that we have garnered over a decade of handling business payments is huge, but not processed and understood in its entirety.
It wasn’t immediately apparent when we first started, but big data is now an important topic of discussion in fintech and, specifically, payments. As more and more businesses use fintech to simplify their payments, third-party processors suddenly find themselves with a lot of data that can be analysed to shape corporate strategies. Suddenly, making sense of big data is a pivotal aspect of these firms.
What is big data?
Imagine the following scenario. You are digitally savvy. Not the kind who can’t live without the Internet or social media platforms, but you have adequate know-how to manoeuvre around Google and Facebook for news, traffic information, or work and leisure. How much data do you think Google and Facebook have on you?
According to this Guardian opinion piece, the amount of data they have is far beyond what you can possibly imagine. This includes every email you have ever sent, deleted and every picture that has ever been uploaded. Everything you’ve searched for and deleted. Your routine. Places you have visited.
Now multiply this with billions of users and we are looking at zettabytes (hyperbole alert) of data. This information, unprocessed, represents big data in the most basic way: overwhelming and, to the layman, mostly useless.
To the trained eye, however, the potential of big data is endless. It allows businesses to observe consumer behaviour and identify trends that can be used to chart strategies and market their products more effectively. And this is just one example in a single sector. Imagine big data being used to aid rescue missions, improve healthcare delivery and technology, accelerate mega construction projects, etc.
How do fintechs seize the potential of big data in B2B payments?
But we digress. In the context of B2B payments, what are payment hubs doing with big data? More importantly, is it all that useful for businesses that engage these fintechs? Here are two examples of what Tranglo is doing.
First, allow us to point you to this article published by McKinsey. The key takeaway: identifying big data resources and gaps is basic to a big data strategy. It goes on to say that a “review of internal and external data will create a realistic view of a company’s capabilities and needs, as well as access to analytical talent and partnerships”.
Tranglo identified the need to process data to its full potential early 2019. In just 3 years, we’ve set up a team and developed a number of cool tools, like our Kafka Connectors Board that makes data streaming a breeze, to solve the problem of underused data. We used to have a lot of payment and technological data that can rarely be shared outside of the company because it was not standardised. Nor was this information shared across the company internally because of siloed efforts: analysis of payment data often neglected marketing aspects/potentials and couldn’t be used to coordinate client engagement efforts effectively.
Our tech has been in overdrive to identify “data gems” and recognise the value of them in our partnerships with clients. Thanks to smarter resource routing recommended by the reports we generate for them, our partners are experiencing shorter payment turnaround time in specific corridors, and have improved their liquidity this way.
Second, read this PYMNTS.com piece on the usefulness of Google Maps to predict the future of payments. Or you can just trust us as we highlight a point that stands out: “A good deal of what’s coming in payments and commerce can be seen via what’s going on with maps. They are not only doing specific, day-to-day jobs for consumers, merchants and others, but pointing the way toward innovations, disruptions and trends that could dominate the 2020s.”
As a global payment processor, Tranglo has access to payment trails. With that information, we have drawn up maps worth “billions in transaction value”. We are using these maps to learn more about how people pay, what changes are in store and push the frontiers of known payment hotspots. This allows us to drive our network expansion optimally, allowing businesses to make payments through us more efficiently. Using these maps, we’ve come up with an all-in-one business payment solution, Tranglo Business, that gives corporates of all sizes the most cost-effective way to send and receive global payments driven by data.
What does the future hold for big data-driven payments?
According to Experian, 85% of organisations see data as the most valuable asset, but low data literacy is a hindrance. We are proud to say we’ve made significant progress in this area. While protecting our bottom line is important, we know that reinventing the ways in which we create value for our customers is key to making cross-border payments accessible to all. After all, it is not just about driving the payment ecosystem towards a sustainable future, but doing so in a seamless and rewarding manner.
One of the ways we are doing that, if you haven’t already figured it out, is by analysing data gathered by our single interface platform and API efficiently, deriving meaningful insights and using them to affect the supply chain positively. We want to help businesses, big and small, observe transactional trends and make better decisions by seizing the potential of big data-driven payments.
Talk to us to know more.