Connecting the dots with network analytics? Why your next investigation needs White Box data

Between 715 billion and 1.87 trillion Euros is laundered around the world each year, according to estimates from the United Nations Office on Drugs and Crime. That’s the equivalent of between 2 and 5 percent of global GDP.

A key challenge in uncovering illicit financial flows is the incomplete picture analysts have, caused by poor quality data that sits in siloes – amongst other reasons.

In response, financial institutions and law enforcement agencies are increasingly relying on innovative technology solutions to join the dots – in order to prevent dark money from entering the financial system and to identify bad actors already taking advantage of it.

Network analytics is an emerging technology being utilised in this area, and OpenCorporates’ White Box data has been at the forefront of powering it. Read on to find out how.

Network analytics: what is it?

Network analytics, or link analysis, can be defined as technology that ‘examines the connections between related entities to better illuminate relationships’.

In the context of anti-financial crime efforts, this means combining various kinds of data to look for connections or anomalies that could indicate financial crime risk – such as corporate records, watchlists or internal customer and transaction data.

With financial institutions looking to proactively monitor their clients for risk, such as through continuous due diligence and transaction monitoring systems, network analytics can act as a complementary layer helping to inform these efforts.

Building a network with company data

As company data is foundational to understanding the universe of legal entities, which are frequently abused by bad actors for nefarious purposes, it’s important you are able to access the right data when building a network analytics solution.

Company data helps to illuminate connections between legal entities, people (ie company officers) and addresses across borders that simply would not have been possible otherwise.

Regulatory technology (RegTech) companies are on the leading edge of innovation in network analytics, as well as financial institutions themselves. Many of these solutions don’t just conduct the analysis, but also generate visual networks illustrating who is linked to what over time – so they can be easily understood by an investigator.

Case study: How FNA use network analytics to enable proactive financial crime investigations

FNA’s network analytics platform uses OpenCorporates’ bulk data to help financial crime investigators take a proactive approach to identifying risk.

By combining our company data with a range of other sources, and applying machine learning, their technology identifies anomalous activity patterns that could be early warning signs of risk.

“Put simply: OpenCorporates’ data helps us complete the record about a company or transaction” explains Brandon Smith, Director, National Security & Financial Crimes Solutions at FNA.

“If you’re investigating suspicious payments but only have transaction data to work with, then you’ve got an incomplete picture. OpenCorporates’ data allows our users to understand transactions, and other activities, in the context of a business”.

“Our solution provides insights in two ways: by conducting statistical analysis to identify if a known financial crime typology is occurring, or if activity patterns over time indicate compliance with how people or businesses say they will act”.

An example network visualisation from FNA’s technology, utilising OpenCorporates’ data, is below.

A time-event based network investigation into an investment network containing alleged fraud – visualised by FNA’s technology. Red, purple, and pink links visualize OpenCorporates connections that were otherwise unavailable when only considering financial transactions and news reporting denoted by other colors. OpenCorporates data helps identify additional companies for investigation with time based relationships that are not captured on current company websites or were not identified in financial transaction data.

Why your network analytics solution needs White Box company data

If you’re building or procuring a network analytics tool to enhance your investigations, be sure to ask the following questions when you’re looking for a company data source to integrate into it:

  • Provenance: where does the data come from? How can you be sure?
    For data to be used effectively in any risk-related decision, you need to be sure where it came from and if you can trust it. OpenCorporates’ data is collected only from official public sources, and we provide clear provenance for all company datapoints – so you can deploy it with confidence.
  • Connecting data: how easy is it to combine the data with other data sources?
    Investigative leads often arise when you are able to combine one dataset with another, but inconsistent schemas or proprietary identifiers can make this difficult. OpenCorporates makes combining data easier by aligning all the data we collect into a single global schema, and assigning each company record an open identifier – based on the one in the official company register it was collected from. These open identifiers mean you aren’t locked into only using our data, unlike Black Box data providers.
  • Coverage: what jurisdictions and types of data are included?
    The more high quality data your solution can analyse, the greater your chance of finding a connection that could be a red flag. OpenCorporates provides access to complete official company data (including legal entities, officers and more) from over 139 jurisdictions, providing cross-border insight via a single subscription. Not only that, we have charted branch entity relationships across the US – allowing you to identify links that run across state lines.

You may also be interested in…

  • The White Box Data Revolution
    Our white paper shows how the inherent problems of Black Box data have been exacerbated with recent trends like KYC regulation, globalisation and the connectedness of data. It offers a solution to the problem: White Box data.
    Read white paper >
  • 6 Degree Intelligence cuts investigation time down to a fraction using OpenCorporates data
    6 Degree Intelligence combined OpenCorporates’ data with other datasets to reduce investigation time, and to provide cross-jurisdictional insight in financial crime and modern slavery investigations.
    Read case study >

  • Our data
    400+ organisations rely on our data at scale, via our API or our bulk data offering.
    Find out more >

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