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How decision intelligence and data-driven approaches can combat drug smuggling, trafficking networks

Law enforcement can stay ahead of evolving criminal tactics through strategic investments in training and resources

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Smuggling and trafficking networks have evolved.


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By Mark Massop

In recent years, the challenge of combating drug smuggling and trafficking networks has become increasingly complex for law enforcement agencies across the United States.

Offenders continuously evolve their tactics, leverage technology and exploit vulnerabilities in existing enforcement measures. Between 2018 and 2022, the number of fentanyl drug trafficking offenders increased by 460.7%, according to the United States Sentencing Commission.

In July 2023, Mexican marines working customs duty found a shipping container on the Pacific coast, bound for Australia, loaded with 7,200 bottles of a clear liquid labeled “mezcal” that actually contained liquid methamphetamine.

Law enforcement agencies must adopt innovative and data-driven approaches to tackle this crisis effectively. This article explores the concept of decision intelligence and its potential to bolster efforts to combat drug smuggling and trafficking networks at the federal, state and local levels.

The Evolution of Smuggling and Trafficking Networks

Smuggling and trafficking networks have evolved beyond traditional methods to exploit gaps in law enforcement capabilities. They now employ sophisticated technologies, decentralized structures and encrypted communication channels. These networks engage in illicit activities, including drug trafficking, human smuggling, contraband trade and financial fraud. Recognizing these dynamic challenges, law enforcement agencies must adapt and innovate.

Understanding Decision Intelligence

Decision intelligence is an emerging field that combines data fusion, artificial intelligence and machine learning, data analytics and human expertise to make better-informed decisions in complex environments. By leveraging data-driven insights, law enforcement agencies can enhance their ability to anticipate, detect, and counter smuggling and trafficking networks effectively.

Leveraging Data Analytics

Data analytics plays a pivotal role in decision intelligence. Law enforcement agencies can harness the vast amounts of data available to them, such as surveillance records, intelligence reports, financial transactions and open-source data to identify patterns and anomalies. Advanced machine learning analytics can detect trends, predict potential smuggling activities, and pinpoint key nodes within smuggling and trafficking networks.

Collaborative Information Sharing

Effective decision-making in combating smuggling and trafficking networks hinges on seamless information sharing among various state, local and federal law enforcement agencies. Creating centralized platforms for secure and real-time data exchange enables agencies to collaborate efficiently and pool resources. It fosters a comprehensive understanding of the network’s operations and helps identify critical pathways for interdiction.

Implementing Automated Risk-Scoring

Law enforcement agencies can stay one step ahead of smuggling and trafficking networks by applying risk-scoring models to prioritize suspicious individuals and groups. Machine learning algorithms analyze historical data to forecast potential smuggling and trafficking hotspots, preferred routes and modus operandi. With this foresight, agencies can strategically deploy their resources and focus on high-risk areas and suspects.

Utilizing Machine Learning in Surveillance

Smuggling and trafficking networks often adapt their methods to evade law enforcement. Traditional surveillance techniques may not suffice in this rapidly changing landscape. Integrating machine learning into surveillance practices can expedite actionable intelligence through data enrichments for anomaly detection, video analytics, voice recognition and audio transcription. This technology empowers officers to identify suspects, track their movements and preempt criminal activities more effectively.

Embracing Open-Source Intelligence

Open-source intelligence (OSINT) is a valuable resource for law enforcement agencies combating smuggling and trafficking networks. Publicly available and third-party data from social media, online forums and other sources can provide critical insights into the networks’ activities, recruitment efforts and communication channels. Law enforcement officers trained in OSINT analysis can glean valuable information to inform their operations.

Incorporating Human Expertise

While decision intelligence relies on cutting-edge technology, human expertise remains irreplaceable. Law enforcement personnel possess invaluable insights and intuition honed through years of experience. Integrating these qualities with data-driven decision-making ensures a holistic approach to combating smuggling and trafficking networks.

Strengthening Border Security

Effective decision-making must extend beyond traditional border checkpoints. Law enforcement agencies can deploy tactical intelligence capabilities with advanced technology to monitor remote areas susceptible to smuggling and trafficking activities. This enables law enforcement and border security to gain real-time insights and relay them to centralized command centers, enabling quicker responses to emerging threats.

Investing in Training

Law enforcement agencies must invest in comprehensive training for officers and analysts to leverage advanced technological capabilities to gain actionable intelligence. Training programs should cover data analysis, machine learning, cybersecurity and OSINT techniques.

NEXYTE, Cognyte’s decision intelligence platform, transforms how law enforcement agencies utilize data. NEXYTE automatically fuses and analyzes data sources of all types to provide a rich, cohesive view that accelerates data-backed decisions. This extensible, future-proof platform is designed to seamlessly scale out, handle unlimited data volumes, and easily integrate with new and existing data sources and systems.

In doing this, NEXYTE democratizes the power of AI and machine learning to enable users to readily access data and share insights with powerful yet easy-to-use data visualization and exploration tools. Data and insights are seamlessly shared across organizational boundaries while maintaining strict governance and permissions. NEXYTE’s out-of-the-box machine learning algorithms automatically detect suspicious indicators, patterns, hidden connections, and anomalies and embed previously unattainable insights into the user’s work processes to provide contextual operational value. This empowers users to assess risks quickly and accelerates detecting and preventing threats and illicit activities.

Smuggling and trafficking networks pose a significant challenge to law enforcement agencies worldwide. By adopting decision intelligence platforms like NEXYTE, law enforcement can enhance their capabilities in detecting, disrupting and dismantling these illicit networks. Leveraging data analytics, machine learning and human expertise in a collaborative environment will empower agencies to make more informed decisions and safeguard communities from the pervasive threats smuggling and trafficking networks pose. Through strategic investments in training and resources, law enforcement can stay ahead of evolving criminal tactics and ensure a safer and more secure future for all citizens.

About the author
Mark Massop is a retired police officer from Independence, Mo. For the past 19 years, Mark has worked in the private sector, supporting the law enforcement community with mission-critical analytics and investigative solutions.