At Intrinio, we’ve helped thousands of fintech companies get access to quality data at affordable prices. Along the way, we’ve noticed 5 common mistakes that fintech founders and engineers make when buying data for their apps and software.
We’ve seen companies that make these mistakes get banned for life from accessing critical data feeds, be investigated by the SEC, or even have their company shut its doors due to complications. Financial data is tricky, but this blog will make it easy for you to get things right so that this doesn’t happen to you.
Fintech is a broad industry. It ranges from insurance, to lending, payments, capital markets, personal finance, AML, KYC, and more. The “Capital Markets” category includes any companies that are focused on solutions for investing - stocks, bonds, options, ETFs, mutual funds, crypto and more. Startups in this space are building brokerage solutions, trading software, research terminals, hedge funds, robo advisory services, AI investing bots, investment education platforms, social investing websites, crypto exchange & more.
For startups in this space, data is absolutely critical. It forms the lifeblood of their apps, software and tools. It populates their charts and graphs. It informs their investment decisions. It educates their users. It predicts the market. In fact, data is the largest expense item for fintech companies outside of human capital. Most founders and fintech engineers are not prepared for this, and if not planned for or executed correctly, data feed costs can drown an early-stage startup or project.
Let’s face it. When you are in the early stages of building your company, you are looking for the cheapest resources you can find. This will often lead fintech companies to questionable data providers in search of the lowest price. However, when it comes to financial data, you get what you pay for. This is not the area where you want to cut corners. Building data sets takes years of time, effort, energy, technology, and talent. There are no easy ways around this. If a data vendor is touting prices that seem too good to be true - they are.
These types of providers are often screen scraping data from other companies and websites, violating terms of service, and breaking the law. In many cases, that’s the only way to make a profitable business out of selling cheap data.
Before you sign up for a data feed, make sure you research the provider. Check to see if there are any lawsuits pending against them, and read reviews and threads online. If the data vendor can’t tell you exactly where they source their data from, this is a red flag. Keep in mind that if you start with a sketchy provider and decide to upgrade later, it’s quite a bit of work to unwind the data integration and start over. This can cost you time, money, and maybe even your company. Building on top of stolen data is not a strong foundation, so choose wisely.
Fintech founders and engineers are often eager to get building and can be under pressure to scale quickly. The irony is that if you build too quickly, you’ll make mistakes that prevent you from scaling effectively. When it comes to data, planning ahead for growth is critical. Data needs within fintech startups change drastically as they grow. A cheap, quick data feed may work for a few months, but when things change and you need new, different, or more data - you could be left spinning your wheels.
The first thing to think about is volume, many data providers will rate-limit your API calls or the frequency at which you are receiving data. As you grow, your users or use cases may call for a higher volume of data. For example, you could start by only needing to chart daily stock prices to your users inside your app, but after you raise a Series A round your new feature set could call for streaming real-time data.
The next thing to consider is history. For data sets like financial statements or fundamentals, it may be okay to start with 1 year of history. But if your investment models grow in their sophistication and start calling for more historical research, you may need 10+ years of history.
Lastly, whatever you are building could bridge into new asset classes. You could add a crypto feature, starting covering ETFs, or get user demand for options trading- businesses make money by adding these features so their platform becomes more engaging, sticky, or allows them to increase prices.
Fintech startups and engineers that don’t plan for growth and choose a flexible provider can end up switching data providers, adding multiple data providers, and wasting valuable time on integrations. Be sure to talk with your provider about your roadmap and future plans for volume, history, and asset classes. Your profitability depends on it.
For any startup or entrepreneurial project, speed is paramount. It’s critical for founders, CEOs, CTOs, and heads of product to delegate and automate in areas outside of the company’s core competency. For fintech companies - this means data has to flow easily.
Unfortunately, many legacy and large vendors are not set up for efficiency. If you don’t speak up early in the process, you may find that the time to integrate eats up your engineering resources. If the data isn’t easy to use, your developers will be wasting time trying to figure out how to access it. If dev tools like SDKs and good documentation aren’t present, it could triple the amount of time it takes to integrate data- remember that your top cost is people, and developers are expensive resources. If timely customer support and other resources are not readily available, data delays could threaten your launch, lose you customers, increase human capital costs, or worse. Speed is survival when you are building a disruptive or innovative fintech solution, so make sure to speak up about speed when you are buying data.
Purchasing and accessing data feeds is complicated. For new founders and engineers, the contracts can read like a foreign language. It’s important to read them thoroughly, however, because you could be signing your company up for a trip it can’t afford.
One mistake we see data buyers make is confusing monthly vs annual pricing. You can often save money by paying annually, but the commitment can be tough to stomach. Be sure to check whether the pricing you are looking at is annual or monthly and ask if you can switch to annual after a few months. Payments can also be listed in contracts as monthly, quarterly, or annually. Paying upfront can be completely out of the question, but you may be able to get an annual pricing discount and negotiate monthly or quarterly payments with an annual commitment. Lastly, contracts can be laid out with a bit of trickery to make your price look low, but then include other fees later in the document. In particular, some data companies try to hide stock exchange fees, per user fees, or other service fees within the contract.
Financial data feeds are often connected to entities like stock exchanges that are heavily regulated by the SEC. If you are buying market data that originates from a stock exchange, there are lots of rules involved, and it’s critical that you follow them - for example, paying exchange fees or per user fees. Our 3-part video series “Market Data 101” breaks this down in more detail, so head there to dive in.
Even if you aren’t getting data from an exchange, many providers strictly regulate how you are using the data. There’s a big difference between internal and external use. If you are showing the data to anyone outside of your company, it triggers extra costs like “display fees” or “redistribution fees”. Some data providers don’t even allow this at all. Most data providers do not allow for “resale” of the data under any circumstances. There’s a chance that if you try to break any of these rules, the data vendor - or worse - the SEC - could audit you. You risk being blacklisted from the data space and unable to access the data, paying steep fines, or even being sued. It can literally take your company down. Be sure to ask a lot of questions about usage of the data when you are working with a new provider, and be open and honest about your plans for integrating it.
Making any of these mistakes can cost you big money or create regulatory problems, but at Intrinio, we help investors and fintech companies navigate this complex landscape and match their use case to the right financial data feed. To learn more chat with our team today, and if this content was helpful, please make sure to subscribe to our blog and YouTube channel for more fintech and financial data content.