Fighting Human Trafficking Through Data Sharing and Analytics

Government agencies that deliver social services often encounter troubling situations among the communities they serve. One of the most devastating is human trafficking — the recruitment, transport, harbor, or receipt of people for forced labor or sex. Many of its victims are adolescents.

In the United States, human trafficking has been reported in all 50 states, with 11,500 cases reported in 2019 alone, according to the Human Trafficking Hotline. Global factors such as the Covid-19 pandemic have increased rates of human trafficking, according to the U.S. State Department.

The complex and interrelated issues that allow this crime to persist must be addressed on multiple fronts. But one practical strategy state and local governments can apply to mitigate this societal affliction is to capture, analyze, and act on relevant data. In particular, the creation and management of a data-sharing platform helps agencies reduce and ultimately eradicate human trafficking.

Data-Capture Challenges

Across governments, agencies have recognized the value of a data-driven approach to addressing social challenges and delivering resident services. As with many similar social-welfare issues, the identification, prosecution, and mitigation of human trafficking can benefit from cross-agency capturing, sharing, and analyzing relevant data.

Yet developing targeted counter-trafficking responses and measuring their impact is hindered by the lack of reliable, high-quality information, according to the Counter-Trafficking Data Collaborative, an initiative of the intergovernmental International Organization for Migration.

In the United States, there are several reasons for the lack of trafficking data.

1. Identification of the crime often relies on self-reporting. Often the vulnerable populations that can fall victim to trafficking shy away from self-reporting, for fear of harm to themselves or to loved ones
2. Federal mandates for the collection of trafficking data are not as robust as they need to be. In the majority of states, healthcare and social workers are required by law to report child, elder, or intimate-partner abuse. But while human trafficking can often involve abuse, there’s no nationwide requirement to specifically report suspected cases.
3. Unlike narcotics trafficking, human trafficking “evidence” involves people, not physical objects that can be easily tagged or inventories. With narcotics trafficking, relevant evidence involves physical objects such as drugs or vehicles. With human trafficking, the evidence involves people, who have the right to move about freely and who might actively try to avoid engagement with the justice system, even as a victim.

The result is that law enforcement, social services, and other government entities typically lack up-to-date, reliable data on human trafficking. And this data deficit makes fighting trafficking difficult indeed.

Data-Capture Challenges

Across governments, agencies have recognized the value of a data-driven approach to addressing social challenges and delivering resident services. As with many similar social-welfare issues, the identification, prosecution, and mitigation of human trafficking can benefit from cross-agency capturing, sharing, and analyzing relevant data.

Yet developing targeted counter-trafficking responses and measuring their impact is hindered by the lack of reliable, high-quality information, according to the Counter-Trafficking Data Collaborative, an initiative of the intergovernmental International Organization for Migration.

In the United States, there are several reasons for the lack of trafficking data.

1. Identification of the crime often relies on self-reporting. Often the vulnerable populations that can fall victim to trafficking shy away from self-reporting, for fear of harm to themselves or to loved ones
2. Federal mandates for the collection of trafficking data are not as robust as they need to be. In the majority of states, healthcare and social workers are required by law to report child, elder, or intimate-partner abuse. But while human trafficking can often involve abuse, there’s no nationwide requirement to specifically report suspected cases.
3. Unlike narcotics trafficking, human trafficking “evidence” involves people, not physical objects that can be easily tagged or inventories. With narcotics trafficking, relevant evidence involves physical objects such as drugs or vehicles. With human trafficking, the evidence involves people, who have the right to move about freely and who might actively try to avoid engagement with the justice system, even as a victim.

The result is that law enforcement, social services, and other government entities typically lack up-to-date, reliable data on human trafficking. And this data deficit makes fighting trafficking difficult indeed.

Connecting the Data Dots

Agencies could eliminate this data desert by capturing and correlating “leading indicator” data – information that can signal trafficking risks. Data related to the demographics and living situation of teen mothers, for example, could raise flags for trafficking risks. If the father is significantly older than the mother, or if the baby is born with narcotics in their system, there’s significant cause for concern. Other relevant data could help identify vulnerable populations, including homeless youth, gang members, or refugees.

But data in one region might not be relevant in another. In urban areas, a combination of a teen pregnancy with active drug use can signal a higher likelihood of someone being a victim of sex trafficking. In rural areas, high concentrations of undocumented men are at a greater risk of trafficking for forced labor. Gather the wrong data in the wrong region, and risk factors can easily be overlooked.

That’s why data sharing is crucial. Governments need a way to distribute and analyze data across agencies so they can connect the right dots and gain a clear picture of potential problems.

Data-Sharing Platform: A Powerful New Tool

The solution is a data-sharing governance legal framework that enables secure cross-agency sharing of relevant data. This approach has proved a powerful tool in the fight against opioid addiction, and the same principles and approaches can be successfully extended to combat human trafficking.

Qlarion, a Voyatek company, collaborated with the Commonwealth of Virginia to create the Framework for Addiction Analysis and Community Transformation (FAACT), an innovative data-sharing concept and platform. The effort shares data among the Department of Criminal Justice Services (DCJS), state and local police, the department of forensic sciences, private healthcare systems, and other organizations. Based on the initiative’s success, the Commonwealth worked with Qlarion to extend the tool to help battle Covid-19.

Now, DCJS has asked our analytics team to repurpose the data-governance model to address human trafficking in the Commonwealth. While it is a crime that is hard to measure because of the heavy reliance on self-reporting, limited third-party reporting requirements, and victim hesitance to interact with the justice system, the government is committed to eradicating the crime.

The data-sharing platform will unite previously siloed data from a variety of organizations to help authorized users identify, prosecute, and prevent trafficking. Crucially, it will enable the creation of easy-to-consume visualizations. These visualizations transform raw data into actionable insights that will enable nontechnical users – including law enforcement, social workers, school counselors and other relevant stakeholders – to quickly and easily identify risk factors, track trends, and drive positive outcomes.

Human trafficking isn’t an issue that can be solved quickly and simply. But efforts like Virginia’s data-sharing platform are a positive development. Because the approach is community-based, it can uncover factors that might otherwise remain hidden. Because it’s scalable, the capabilities can be extended to states across the nation. Because the platform is integrated, it can break down data silos and unlock insights. It’s an excellent example of how data sharing and analytics can have a tangible, positive impact and help deliver services to the residents who need them most.