Identify, prevent and predict: Using data to stop global trafficking

In anticipation of our 16 March seminar on how charities can use data to increase their effectiveness, this guest blog explains how data is a crucial pillar in global trafficking prevention strategies. Ana-Sofia Baillet and Robyn Phillips, from STOP THE TRAFFIK, will be speaking at our event.

Automated technologies frequently give rise to concerns about privacy and, at our organisation, the human rights implications of using advanced tools in anti-trafficking efforts. STOP THE TRAFFIK (STT) has been working to prevent human trafficking around the world and in the UK since 2005, and has recently adopted technology as a key component of successful counter-trafficking initiatives. While ethical risks are a reality that need to be addressed, the emergence of ‘tech’ as a disruptor of trafficking can enable proactive prevention.

Shaping prevention efforts through tech

STT’s intelligence-led model relies on innovative tech solutions and follows three main steps: identification, prevention and prediction. Over the past decade, STT has focused on identifying granular trafficking hotspots and trends to prevent future incidents and is developing digital tools to predict conditions under which human trafficking has the potential to occur. One of the key objectives is to amass a dataset of enough variety, volume and reliability to start predicting where trafficking will occur and to build resilience in that community before it has the chance to take hold. These steps aim to change the environment surrounding trafficking by influencing attitudes amongst vulnerable communities, the general public, NGOs, businesses, financial institutions and government agencies. Technology by itself is not the disruptor of crime; however, new tech can enable partnership-based strategies.

How does our model work?

To build an understanding of global patterns and trends, analysts collect non-sensitive data, including source, destination and transit locations; recruitment methods; control methods; transport methods; exploitation types; exploitation subtypes; and the demographics of offenders and victims.

STT analysts then use analytical tools to transform raw data into useful insights, patterns, hotspots and routes. This includes visual intelligence technology that allows analysts to quickly collate, analyse and disseminate large amounts of data from disparate sources to prevent and disrupt human trafficking. Finally, STT shares these findings with global multi-sector partners, in the most appropriate format for them to act upon. The data analysed so far has uncovered human trafficking activity in over 125 different countries, from which approximately 600 trafficking routes have been identified.

Tech-driven innovation and analysis

In an effort to link trafficking prevention strategies to advanced technologies, we have incorporated the following solutions:

• The STOP APP (Identify): The STOP APP is a smartphone app that provides communities with an anonymous, reliable and trustworthy reporting platform. Where appropriate, intelligence is shared with the authorities and other organisations. The data is also ingested into the STT dataset.
• Online campaigns (Prevent): In collaboration with partner organisations, STT delivers customised, geo-targeted social media campaigns that directly reach people in communities identified as vulnerable to human trafficking, enabling them to recognise local indicators, avoid high-risk scenarios, and seek local support.
• STT analysis (Predict): STT uses an intelligence and evidence-led approach. We collect and extract human trafficking data from multiple sources. With adequate data, we can conduct analysis to  identify conditions under which modern slavery has the potential to occur and engage in proactive prevention.

The system at work

In 2018, STT ran a highly effective geo-located, demographically targeted campaign in the Fenlands area in the UK. The awareness campaign focused on communities identified as hotspots for labour exploitation and reached over 250,000 people. Activities included training Barclays Bank frontline staff based on a ‘red flags’ toolkit co-created by STT, an on-the-ground community awareness day and a social media campaign published in both English and Lithuanian. STT worked with over 14 key partners ranging from the Home Office, the Lithuanian Embassy, law enforcement, local authorities, bank branches, local NGOs and community organisations.

This project, through advanced tech tools, changed a community by giving it the information, procedures and awareness required to reduce the risk of human trafficking. 45% of the target population stated that they would act differently in future potential human trafficking situations. To prevent and disrupt trafficking, technology is not optional. There is a need for organisations to become proactive and predictive, rather than solely reactive.