Produced as part of the Pandora Papers, this collaboration from Finance Uncovered and Premium Times was designed to stand out from past reporting on corrupt Nigerian funds sequestered in Britain. Yes, it too reveals the names of wealthy and connected Nigerians buying UK property. But the audience also gets a chronologically-animated, interactive map — an unprecedentedly data-rich perspective on the wave of suspect money flowing into UK property. Journalists found 233 properties, worth £350m, secretly bought by 137 Nigerians. One in six was owned by an offshore company of interest to law enforcement. Money laundering was suspected in most cases.
After our work was published, some Nigerian politicians and officials were interviewed by the country’s specialist anti-corruption enforcement agency, the Economic and Financial Crimes Commission (EFCC). In addition, Nigeria’s Federal Inland Revenue Service announced an investigation into possible tax evasion and the Code of Conduct Bureau announced investigations into serving and past public officials.
Elsewhere, anti-corruption campaigners praised our Pandora Papers reporting for shining new light on patterns of corruption and money laundering. Delivering the Transparency International UK annual anti-corruption lecture, Ngozi Okonjo-Iweala, director-general of the World Trade Organisation and former Nigerian finance minister, explained how our work revealed a “cottage industry” of enablers — lawyers, accountants, estate agents — in London, who play a vital role in facilitating Nigerian corruption. Meanwhile, Transparency International Nigeria (CSLAC) urged president Muhammadu Buhari to allocate increased funds to the country’s anti-corruption agencies, allowing them to launch comprehensive investigations into findings from the Pandora Papers.
In the U.K., the opposition Labour Party responded to Pandora Papers by setting up an Illicit Finance Taskforce to pressure the government into prioritising the fight against international corruption. However, government ministers said they would not be rushed. They insisted plans were already in train that would eventually outlaw the use of anonymous offshore companies in the UK property market. These measures —contained in the Registration of Overseas Entities Bill — had first been promised in 2016 but are still not included in the government’s current legislative programme. After the Pandora Papers, more than 40 MPs, from all parties, accused the U.K. was showing insufficient urgency. They have written to the prime minister calling on him to prioritise long-promised anti-corruption reforms, without which, they MPs said, the U.K. found itself “at the heart of the world’s dirty money crisis”.
This project started as a slowly expanding list of people who owned companies incorporated in secrecy havens such as the Seychelles and Panama. The ownership data was painstakingly extracted from the Pandora Papers, a leak of 12 million PDF, XLS, Word and other files, all from the offshore company-formation industry. The process took six months. From the resulting Ms Excel dataset, two patterns emerged: many offshore company owners were wealthy Nigerians, and many offshore companies were used to buy UK real estate. The leaked documents didn’t mention specific U.K. property purchases, but we were able to match Pandora Papers companies to the names of anonymous offshore companies found in UK Land Registry records. Finance Uncovered (FU) shared its methodology with the BBC and The Guardian. Together, the three organisations went on to identify more than 1,500 UK properties, worth £4 billion, secretly bought by about 600 wealthy individuals. Techniques used to find matches included Ms Excel functions such as MATCH, VLOOKUP, INDEX(MATCH) and pivot tables. SQL was also used to combine and interrogate Land Registry data. For FU and Premium Times, the main focus was Nigerian owners of U.K. property. So together we assembled profiles on the wealthy Nigerians who had appeared in our research. Later, the same methodology — search, data-matching and profiling — was applied to other leaks, including Panama Papers and FinCEN Files, further expanding our dataset. To highlight the many U.K. properties acquired during the corruption-blighted presidency of Goodluck Jonathan (2010-15), we used Flourish tools to plot our findings on an animated map. Each property was represented as a pin-drop “blob” that appeared in chronological order. We also used Flourish tools to build a slide show highlighting other data trends, such as properties owned by oil tycoons, and properties owned by companies of interest to law
What was the hardest part of this project?
After months of research, FU and Premium Times had amassed an unprecedented amount of intelligence on hundreds of wealthy and powerful Nigerians who secretly invested in UK property. But we faced two challenges. First, we wanted our work to stand out from the steady flow of piecemeal reporting on suspected corruption and money laundering. Second, we had to navigate tough U.K. publishing constraints.
Even though the U.K. government had failed to deliver on a 2016 pledge to introduce a public register of those who anonymously bought U.K. property, FU found it could not simply print those names that ministers had not. Strict local privacy laws still applied.
As a result, FU ultimately named just five wealthy Nigerians (from a total of 137) in published case studies. The rest of the dataset then went through an anonymising process. Names of individuals were replaced by the fields in which they worked: “oil”, “politics”, “banking”, etc.
These industry categorisations, together with other anonymised data points — property ownership dates, purchase prices, current valuation estimates, law enforcement interest — were all assembled in a revised dataset. In addition, the precise locations of properties were very slightly blurred, completing the anonymising process.
While the results were not easy to fashion into a piece of written journalism, they were ideal for data visualisations, using Flourish tools.
In particular, once we saw the chronologically-animated map, we realised that we had landed on a fantastic story-telling medium for our data. The visualisation was both instantly arresting and information-rich. We believe it also sets our project apart from previous reporting on suspected corruption or money laundering.
What can others learn from this project?
We are especially proud of this project because we were forced outside of our comfort zone — follow-the-money investigative reporting — in order to tell an important data story through an animated and interactive visualisation.
Doubtless, Sigma Award judges will receive many entries from journalists highly experienced in data visualisation work. That is not us. We came to this form of story-telling by accident. We hope our efforts will spark ideas for others who tend to think of themselves as traditional reporters, confined to words and a few numbers numbers.
As well as offering an elegant technical solution to the legal limitations on our story-telling, we were surprised and delighted to learn that our visualisation also allowed us to reach new audiences. As one of our Premium Times colleagues told us, people in remote, up-country Nigerian villages were excitedly using their mobile phones to study animated maps of London, with coloured dots showing properties bought by Nigeria’s wealthy elite.
This anecdotal feedback was inspiring for us. FU’s mission is to help make follow-the-money investigative journalism a reality in some of the most challenging parts of the world. We will certainly think harder about how to use data visualisation methods to build new audiences on future projects. We hope our work will inspire others to do so, too.