Expanding Forensics Through Forensic Intelligence

By Michael Greenwood, M.Sc.Reviewed by Danielle Ellis, B.Sc.

Forensic intelligence relates to collecting and using forensic data in a broader policing context, allowing crimes to be connected, solved, and even predicted through data analysis. Forensic intelligence, then, is the examination of criminological information to recognize patterns in crime and can assist policing organizations in choosing where and when to deploy resources. This article will discuss the principles of forensic intelligence and how they can be applied to produce more effective policing.

What is the Added Benefit of Forensic Intelligence?

Typical forensic techniques such as fingerprint and DNA analysis have become routine during criminal investigations, and evidence leading to convictions is regularly provided. Just as the large quantity of crime data collected during everyday policing can inform ongoing and future policing efforts, for example, where geographic and temporal data of specific crimes is used to inform deployment, routinely collected forensic data can infer criminal behavior patterns.

Personal identifying forensic data such as fingerprints and DNA can implicate an individual in multiple crimes and, on a broad scale, help to build a demographic profile of perpetrators. Forensic intelligence aims to make the practice of policing fundamentally more ‘scientific,’ in the sense that aggregate forensic data should inform policing practice and support fair and transparent policymaking.

Forensic science has typically been considered a tool for criminal investigation, leading to increasing specialization and compartmentalization of forensic data collection and forensic data. Indeed, 80 to 90% of forensic materials recovered at a crime scene never reach the laboratory, as economic incentives drive the examination of only the most promising forensic evidence, such as DNA and fingerprints, which can be utilized in combination with traditional policing efforts to corroborate an individuals presence at the scene.

However, as the 20^th-century French criminalist Edmond Locard stated: “Fingerprints are wonderful (..) but [for example] dust analysis is an infinite, unlimited resource. One can exactly know what the man did”. In other words, focusing policing efforts on only a few forms of evidence can leave investigators blind to other possibilities and inform criminals which evidence they should be most careful about leaving.

A Holistic Approach to Crime Analysis

The increasing specialization of forensic science has led to the separation between forensic scientists and criminal investigators and the separation of scientists from the criminal investigation itself. Third-party laboratories often perform forensic testing and are generally in service to the court rather than the police. To paraphrase the opinion of De Forest (1999), non-scientifically educated detectives are in the position of directing actual criminalists, relegating forensic scientists to the role of technicians, and leaving no problem-solving scientists on the “front end” of the investigation.

In some countries, such as Switzerland, a more integrated approach has been attempted between forensic and investigative units and has shown promising results. Similarly, in France, the role of crime scene coordinator was established within the police, with the remit of making the best use of forensic data gathered during specific investigations.

While the focus of forensic data collection is generally around what would be useful in court, a more holistic approach would evaluate and use forensic case data at each stage of the investigative process. This is the fundamental principle of forensic intelligence and would allow stronger information processing and evaluative models to be developed, reducing errors in decision-making throughout the course of the investigation. Further, when properly collected and interpreted, high-volume forensic case data can be useful in generating proactive policing models with predictive capability.

Proactive Models of Policing

Proactive policing is the ability to undertake policing actions that will reduce, disrupt, or prevent crime, usually achieved by strategic management and effective enforcement strategies. Such strategies are informed by rigorous criminal and forensic data accumulation and may influence law and policymaking on a national or international level.

For example, the ubiquity of cell phones provides an enormous quantity of tracking and communication data relating to individual criminals or criminal demographics, and police are legally able to examine and interpret this data when identifying individuals planning and executing criminal activity.

More indirectly, effective educational and societal programs at the community level can be recognized and implemented on a broader scale, and the effect of political decisions on crime and policing can be interpreted.

While forensic case data is stored on databases and can often allow multiple crimes to be assigned to a single person, DNA evidence in particular, such linking is often incidental rather than the result of rigorous data collection and management. Forensic intelligence aims to change this and implement forensic data interpretation broadly.

For example, in the early 21^st century, the ability to assign expended bullets to specific firearms was developing. Besides being useful in identifying specific criminals, it was used in areas rife with gang crime to identify gang activity, establish territorial boundaries, and detect spikes in newly emerging activity. Rapid intervention could then be deployed where it would prove most effective, and valuable insight relating to gang activity and relationships was established.

Mindset Change and Moving Forward

Taking a more structured and rational approach to decision-making can help overcome the obstacles that arise when integrating forensic intelligence into crime intelligence. Rather than just feeding the judicial system, decision-making should be based on the analysis of a collection of more comprehensive factors. However, there is much dissent relating to big information and the society of information, and all data collection must be fair and transparent.

Future research could focus on the development of more efficient algorithms for the analysis of forensic data; forensic data patterns and trends that would be difficult for humans to identify can be picked out with the assistance of artificial intelligence and machine learning. The deepening integration of forensic science with criminal investigation could likewise give a more complete image of a crime or series of crimes, placing forensic intelligence at the front end of policing.