With this, data as a topic has always been connected to such topics, even after what happened last year with the infamous Cambridge Analytica scandal. Let's analyse what's going on with data within fintech, with predictions and speculations on why it will become even bigger than what it is now.
Data And Finance: A Definition
Data is an extremely complex topic to cover but its applications to finance are (still) relatively limited to risk management and user targeting: companies like Monzo, for example, are using big data to ensure that users' experience flows well with the app's updates and, most importantly, by analysing their credit score (mostly for premium versions) with such data, they're able to assess on whether if any form of overdraft/loan should be granted to that hypothetical user. Data, within finance, has a more "executive" level than other sectors like marketing, where it's normally used to target specific, niche audiences and such.
The Power Of Computing Data Within Fintech
Gathering data and understanding it isn't a "manual" job anymore. There are, in fact, dozens of Python-based libraries which could be used to both process and interact with data, thoroughly. For example, NumPy, a renowned library used to process and interact with big data, is being used within risk management tools to speed up mortgages applications, by cross-referencing different credit scores gathered via static data from credit cards and banks. Python is the single most required development skill within data science and finance, and its computing power is being used by Barclays, Santander and, recently, Paypal. Computing data has become quite a common practice within software development as well, a very worth-mentioning signal of the fact that, in the future, data-ready software will be used in finance without requiring dedicated development routes.
The Market Value of Data Within Fintech
As briefly mentioned above, the Cambridge Analytica scandal has been the bridge between the usage of data and the mainstream: the usage of data for marketing purposes, specifically Facebook, in that case, wasn't a renowned form of integration within the mainstream, but, infamously, the scandal opened up to a precise, 100% correct way of targeting paid ads, effectively helping thousands of businesses worldwide. With this, a lot of Fintech companies grown massively: Monzo data applications after the C.A. document was released took over 25% of their development, especially when applied to mobile. In 2020, we can safely say that the market value for data-related strategies will peak at around $2 billion within the sole fintech market.
Paul Matthews is a Manchester-based business and tech writer who writes in order to better inform business owners on how to run a successful business. He’s currently consulting a team of app developers in Manchester. You can usually find him at the local library or browsing Forbes' latest pieces.