So You Want To Develop A Fintech App: A Review of Data Sets
In the 1500s and 1600s, a drastic movement occurred in the world known today as the Scientific Revolution. After centuries – even millennia – of human progress staying relatively even, suddenly an explosion of discoveries and achievements were made across various fields. One of the emerging principles of this period was something we now call the Scientific Method. Formally credited to a philosopher named Francis Bacon, who lived from 1561 to 1626, the Scientific Method listed out a logical progression of steps necessary for new conclusions to be made, with more certainty than ever before. Bacon’s Scientific Method, published in his 1620 work, Novum Organum, included these steps:
- Observe and come up with a question
- Hypothesize an answer to the question
- Come up with an experiment to test your hypothesize
- Analyze the data
- Revise initial hypothesize
- Repeat testing/analysis as necessary
Although the general public rarely considers how the scientific method applies to modern-day situations, the steps Bacon formulated to test and make conclusions are still widely used in the modern world. In fact, we could even argue that today’s innovations are largely driven by applying this basic method across various fields and situations – and fintech is no exception. Most fintech exists today in order to help solve problems that previous technologies couldn’t address, or to make financial processes more efficient. But the products and services that are continually emerging within the fintech sector are, in the end, the result of the scientific method being applied to financial needs people have.
Through the rest of this article, the final post in our “So You Want To Build a Fintech App,” we’ll review how you can best approach the testing and analysis steps of building your app in order to ensure its relevance and validity before it’s launched. (For an overview on the process of building a fintech app, you can read the first post of this series here.)
Like we argued in our last post, testing is one of the most important parts of building your fintech app. Why? Because testing helps you know if your app is actually going to work or not, depending on specific criteria. Through testing, you can evaluate what’s working and what’s not, and then make changes necessary for your app to be successful.
There are many different types of testing you should conduct at this point, but an especially relevant series of tests that should be done with specifically fintech apps is data testing. Data testing involves checking all of the APIs that connect consumers’ banks to your app to see if they are working properly after you’ve gone through the process of integrating financial APIs into your app (for more on this, check out the second article in this series here). This is not an easy task, however, because every API for every bank or financial institution has a different interface, which means, hypothetically, thousands of different scenarios should be run through your app before launch to make sure that it will work for any user, no matter what bank they use.
Data Sets for Testing Data
In the past, it’s been difficult to obtain financial data sets to conduct the kind of testing necessary for a fintech app, and developers were limited to purchasing sets of synthetic, or manufactured, data sets from websites like Kaggle or data.world. Now, these sources aren’t bad in and of themselves, but the fact that their data sets are fabricated, generic, or, at the least, modified from the original data, means that they simply won’t be able to give you a very accurate representation of what your app will be like when real data is running through it. Not only are these data sets not a particularly precise subset of real financial data; they also aren’t very diverse and are, more often than not, old and out of date. These realities are all significant details to consider in the testing process.
What you want when conducting data testing for your app is data that is 1) as close to real data as possible, 2) recent, and 3) from a diverse range of sources. The good news is, there is a place where you can actually find financial data like that, as long as you know the right place to look for it.
Finding Better Data Sets
Instead of synthetic ones, you should be looking for data sets that are compiled of real data from real people. This data should be live and permissioned by the consumers to be used in testing processes like yours. That means the consumers, who own the data in effect, grant permissions to use their data for this reason. Does that sound too good to be possible? It’s not, we promise! These kinds of data sets are actually available to developers through some API platforms – potentially the very same platform you used for your API integration in the first place! These platforms can be a great source to ask about data sets to conduct testing on your app, because they already have ongoing access to live data from a huge set of consumers. Working with an API platform to also conduct your data testing allows you to test your app with the best kind of data – ongoing live data from diverse financial institutions – which means that the tests you run yield results that are as accurate to your intended consumer audience as possible. However, be sure that your partner provides access to datasets that have been granted to your company explicitly! That’s the only way to fully respect consumers’ privacy and data rights.
In the last 500 years, our world has experienced more progress and innovation than Francis Bacon could have imagined. By applying the principles of his scientific method – observing, asking questions, developing theories and products, testing, analyzing, and revising – countless new inventions have been created that make our lives easier and more connected.
Fintech that lasts depends on these same principles to create better financial experiences and products for consumers. So don’t leave the success of your app or its services up to chance when you launch! Instead, choose to perform the most robust testing you possibly can through integrating diverse APIs and then testing those APIs as thoroughly as possible by using live, consumer-permissioned data. It’s as simple as that.
If you’re in the process of developing a fintech app and want to talk more about API integration or obtaining financial data sets for testing, we can help! You can contact us with specifics or learn more here.