The best thing about S-branch is our customers. Without exception, all our customers are using data to disrupt or prevent Crime or Fraud. TRAFFIC is one example, working to counter trade in wild animals and plants in the context of both biodiversity conservation and sustainable development.

In 2021 TRAFFIC initiated a project to identify potential instances of corruption in the timber sector, specifically at the point where politically exposed persons (PEPs) allocate companies the rights to harvest wood. The end goal is to use this data to provide credible evidence to financial institutions, encouraging them to investigate further and take action where needed. TRAFFIC’s project was funded under a larger project: Targeting Natural Resource Corruption (TNRC).

The Method

TRAFFIC has access to several different analytical tools and databases. They also have a talented team from a variety of different backgrounds. S-branch was involved early in the process, initially to review TRAFFIC’s method and how they planned to utilise technology. There was an appetite to use technology that TRAFFIC had previously invested in, although a few new tools were added to the arsenal!

Data Collection

Once the country of interest had been selected, the data collection itself was managed by TRAFFIC. There is a wealth of online published information around forestry concessions usually published by the government themselves. Likewise, there is a good amount of information around Politically Exposed Persons (PEPs), sometimes including their family members.

In some cases, TRAFFIC could download the information directly. In other cases, TRAFFIC used ParseHub to scrape data that couldn’t easily be downloaded.

Data Processing

The data collected was varied in its format. While not huge in size it was no small task to coerce this data into a standard format for analysis. This is usually the difficult, time consuming and less glamorous side of analysing data.

There were several challenges with standardising the data, including inconsistencies with the use of accents on names. There was also the need to identify similar people or company names. TRAFFIC managed these tasks in house with data management and occasionally some code. Although the initial analysis was done Excel, TRAFFIC and S-branch eventually moved the data to an analysis database (i2 iBase) to allow patterns in the data to be explored.

Identifying Persons of Interest (i2)

The initial stage was to identify forestry owners and PEPs with similar names that lived in the same region.TRAFFIC has been using i2 Analyst’s Notebook and i2 iBase for several years. S-branch decided to utilise these tools to identify Persons of Interest for further analysis. i2’s ability to display network visualisations alongside geospatial data made it the perfect tool for this.

People with very similar names in the same town were marked in red, while those in a similar region were marked in orange.

Data Enrichment (Videris)

The People of Interest were then investigated further using basic OSINT (Open-Source Intelligence) techniques. TRAFFIC and S-branch also utilised Videris, an OSINT tool that assists in collecting, analysing and visualising open-source data.

On more than one occasion Videris identified social media accounts or news articles that had not been found on the manual OSINT searches. For this reason, we found Videris invaluable for the enrichment stage.

Briefing (i2)

The results of the data enrichment were collected to brief the internal teams. These briefing charts could eventually be passed to financial institutions, to encourage them to investigate further.

Here i2 Analyst’s Notebook was the obvious choice for producing clear and concise briefing content. i2 is widely regarded as the standard for charting which means anything TRAFFIC has made can easily be passed to law enforcement or financial institutions who more than likely already use i2.

High-Level Analysis (Power BI)

There was an appetite to look at the data from ‘the top down’. This analysis would identify patterns and statistical trends. This data would be useful to both the TRAFFIC analysis team and their managers and stakeholders. It would also need to be in a format that is easy to consume, easy to share and didn’t require any specific analysis tools to view.

TRAFFIC are already users of Power BI. This meant that using just a browser, the TRAFFIC team could access interactive dashboards exploring data about PEPs and forestry concession owners. The visualisation below explores the information known about PEPs.

Summary

The TNRC project proves that it is not one person or piece of technology that makes a project successful. It’s a collaboration of talented people and technology that used well can yield good results.

TRAFFIC already had access to several different analytical tools and databases. They also have a talented team from a variety of different backgrounds. TRAFFIC’s talent was combined with S-branch’s experience in analysing fraud and crime data, using a variety of different tools and technology.

To find out more about the TNRC project, please see TRAFFIC’s blog here. If you are looking at running a similar project and are looking at analysis tools to assist you, please contact S-branch for more information.

For more information on TRAFFIC visit their website. If you’d like to find out more about the products mentioned in this blog, please contact S-branch