Functional opacity in company data: What it is & why it matters

What does true transparency mean in today’s complex, connected and data-driven world? 

To us, it means the ability to:

  1. Access the resource you need
  2. Find the records you need
  3. Understand the records
  4. Compare the records to each other
  5. Join the records to other records – to make sense of them

This is true transparency, and it’s the transparency that open data provides. But even now, after multiple governments, including the European Union, have signed up to provide open data, it’s rare that critical government data is available as open data – data addressing questions such as: who our elected representatives are, what financial interests they have, who is government doing business with, what companies exist and who ultimately controls them. 

But there’s a nuance here, and it’s one that hasn’t had enough attention.

To frustrate transparency you don’t need to prevent all or even any of these things – you just need to make each of them a bit more difficult, and hey presto you have what we call functional opacity – opacity brought about through multiple barriers of friction such as time, process, cost, format and licence. 

Imagine looking through 5 panes of glass, each super clear – that’s true transparency. Make each pane 20% dirtier, however, and, overall, you have a view that is almost entirely unintelligible. And this is where we are with most critical government data, although each step is not 20% harder, it’s often 90% harder or more.

Functional opacity in company data

In the context of company data, functional opacity exists when, in theory, you have a legal right to access data, but when you try to do so, there are so many obstacles that you might as well not have any right at all.

Let’s imagine you’re an investigator (maybe a journalist, a law enforcement official, asset recovery lawyer or due diligence professional) trying to learn more about a company that is listed as the owner of a superyacht. In theory, you could find the fundamental information about that company by accessing the registry where it was incorporated.

But in practice, it’s often not as simple as that…

  • First of all, you have to sign up to an online portal to get access to the company registry – likely in a language you don’t speak.

  • Okay, you’ve signed up through perseverance and Google Translate. But wait, it turns out you must enter your credit card details even before you can do a search.

  • Assuming you can afford to pay and your finance team gives you the go-ahead, you realise that the registry only lets you search for info by the exact company name. The only problem is that there are no search results for that name. You spend quite a bit of time searching variations of the name, and finally get some hits.

  • To find out which is the likely correct company, you have to pay for and download filings about each company. The only problem is that each is an image-based PDF… in the same foreign language that you don’t understand. Cue a frustrating few hours retyping the information into Google Translate, and trying to make sense of it.

  • After all this, you think you’ve found the right company, but unfortunately it’s owned by another company, in another jurisdiction, in a different foreign language (although there are directors listed for the company, the register doesn’t allow you to search by director to see what other companies they may be associated with).

  • You have to go back to step one with this new company, and as every company registry has its own way of structuring the data and confusing anomalies – you’ll have to spend time trying to get to grips with each.

Of course, even after all this, it may turn out that the information in the register is out of date, and that ultimate ownership of the yacht has been transferred to another company, or even an opaque trust.

Many company registers actually do make the underlying data available as a complete dataset, but the cost is often prohibitive for most organisations, particularly in Europe where complete datasets can cost millions. 

Why functional opacity harms us all

Functional opacity drastically limits what we can find out about companies. 

This is seriously problematic for myriad reasons, including:

  • Knowing who you’re in business with is difficult
    As the hypothetical example above shows, journalists, investigators or simply everyday companies trying to understand who they’re in business with can hit dead ends in functionally opaque registries.
  • Innovation is held back
    When you can’t access company data at scale, it limits the ability of business to leverage data and technology to drive business-critical insights. After all, you can’t automate a workflow or conduct meaningful data analytics with such high barriers in place. And if you’re a startup with limited funds, you may not be able to afford the high price tag associated with acquiring the full dataset – if the registries you’re interested in even make them available at all.
  • An imbalance of power in society
    When data on companies is difficult for people without the money to access it, they can become disenfranchised. A lack of transparency means companies cannot have confidence in who they are doing business with, allows financial crime to flourish and ultimately damages democracy and society.

Openness and transparency are the answer

The only way to overcome functional opacity is to make the data held in company registries available to all as open data without restrictions. We regularly advocate for this, and whilst much of the EU runs the risk of backsliding on the promises of their Open Data Directive, we’re happy to see Illinois recently commit to making their company data openly accessible. 

At OpenCorporates, we live by example too – as we reduce this friction by bringing together data on the world’s companies that’s fresh, unified, traceable and accessible in one place – and all available as open data on our website.

Everybody can access our data at scale, helping them up a picture of companies and their officers in 140+ jurisdictions. Our users don’t need to overcome the functional hurdles of visiting each company registry in turn and manually piecing together snippets of information.

Our approach saves companies time and helps them to find insights that would not otherwise have been possible. For example, investigators from the Anti-Corruption Data Collective (ACDC) and The Miami Herald used OpenCorporates’ data to discover that companies had allegedly been set up to fraudulently claim US Covid relief funds in 2020. 

David Szakonyi, co-founder of the ACDC, described how OpenCorporates data helped by saying: “It would have been an unimaginable amount of work to visit 50 websites of company registries in different states, extract the data and then manipulate it, clean it and apply our filters. By accessing OpenCorporates’ API, we achieved in less than a day what would have taken two people between four and six months to do”.

Many product managers in the business world also tell us that during the build phase of their product, they tried to aggregate data from company registers themselves in a usable way, realised how difficult it was in today’s environment, gave up – and chose to rely on OpenCorporates instead. 

That’s why in our recent webinar, James Phare, CEO of Neural Alpha (who used our data to help build Trase Finance), ​​said: “Most users just want all of this complexity simplified into one nice and easy-to-use data package”.

You may also be interested in…

  • Case studies
    Hundreds of organisations around the world seek to overcome functional opacity by relying on OpenCorporates’ data at scale.
    Read our latest case studies >
  • How OpenCorporates’ data helped expose exploitation of the US Paycheck Protection Programme
    Investigators accessed OpenCorporates’ data to shed light on companies that had been newly set up to (allegedly) fraudulently claim US government Covid relief funds.
    Read more >

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