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We live in an era in which law enforcement agencies are chronically understaffed but are still expected to solve crimes and maintain public safety even with fewer resources. An increasing number of agencies are addressing that dilemma – and finding success – by using advanced data analysis techniques like decision intelligence to solve cases faster, improve clearance rates and use their resources more effectively.
Decision intelligence is the application of AI (Artificial Intelligence) and machine learning technologies, along with data fusion, data visualization and collaboration tools, to augment and improve decision-making.
Decision intelligence can improve operational efficiency in multiple ways:
- By fusing all types of data for analysis.
- By enriching data with AI-powered insights.
- By visualizing data to see patterns, gain insights, conduct timeline analysis and geospatial mapping to analyze events from multiple angles.
- By enabling secure sharing of data.
- By automating manual processes so that investigations move forward faster.
- By enabling better use of resources.
Let’s examine these areas and the results of applying advanced analytic technologies.
Nationally, homicide, violent crime and property crime clearance rates – the percentage of cases in which a suspect or suspects are charged – have declined over the last 40 years, according to research by the Manhattan Institute and criminology professor Anthony Braga. However, that research also found that agencies can improve their clearance rates in gun homicide cases by sustaining their investigative efforts for longer periods, increasing the amount of forensic evidence collected and analyzed, sharing information more widely and involving more investigators and leaders in the investigative process.
Based on a deep analysis of gun homicide cases handled by the Boston Police Department, Braga found that these changes led to a 23% increase in homicide clearance for cases investigated.
MORE DATA CAN BRING BETTER RESULTS
Having more information can help investigators solve more crimes and solve them faster – if they have the right kind of data and the right tools. Oftentimes today, the volume of data needing analysis is a major problem. The variety – from smartphones, video, social media, other open-source intelligence, audio recordings, record management systems, and more – is also a major challenge. Combining all that data into a form that enables fast and easy analysis can be extremely time-consuming and technically challenging without the right tools.
Decision intelligence tools, like NEXYTE, can reduce analysts’ and investigators’ time by automating and accelerating the data fusion process.
ENRICHING DATA SAVES TIME AND ENABLES INSIGHTS
In addition to bringing diverse data types together into one platform for a comprehensive view, decision intelligence tools can automatically enrich the data in ways that make it more valuable, and that can lead to breakthrough insights. For example, if there are audio files of a suspect with a known identity, that “voice print” can be automatically compared to other audio and video files and linkages revealed with other suspects as well as events, locations, phone numbers, devices, etc. Similarly, decision intelligence tools can convert audio files to transcript form, enabling valuable analysis methods. These kinds of automated analysis can be done in seconds or minutes compared to hundreds or thousands of hours of human effort.
VISUALIZATION HELPS INVESTIGATORS SEE THINGS THEY WOULD NOT OTHERWISE SEE
It has long been recognized that visualizing data by displaying information in the form of maps, graphs, visual timelines, network graphs, heat maps and other types of images has many benefits. Visualization makes recognizing patterns, trends, and relationships between people, places, events and other entities easier. As a result, investigators, analysts and others can make more informed decisions faster.
Network graphs – a standard feature of decision intelligence technology like NEXYTE – are particularly useful in criminal investigations by analyzing customer data to identify individuals most highly connected with other known entities, such as prior crimes, other suspects, gunfire incidents, etc. For example, the New York Police Department analyses of 2020 gun violence revealed that exactly 100 people were connected to three or more gunfire incidents as offenders, witnesses or victims. They also found that ninety street blocks in the city had three or more gunfire incidents in 2020 (some blocks experienced as many as eight incidents). Based on that information, the department concentrated its neighborhood policing efforts on key hot spots and focused its deterrence efforts to prevent gun violence by high-risk groups and individuals.
More and more law enforcement agencies use visualization tools to improve decision-making in their real-time crime centers. They provide views of locations layered with crime, traffic, geospatial, weather and other data. As a result, they can make better decisions based on solid, robust data and allocate resources more effectively for intervention and crime prevention.
SHARING DATA IMPROVES PERFORMANCE
A key finding of the research that evaluated the Boston Police Department’s operations was that involving more stakeholders and leaders in investigations improved results. The Boston police did that by sharing the details of investigative work within the agency and inviting collaboration, suggestions and questions, inviting a range of viewpoints and ideas. Having a single platform that enables a comprehensive view of all the data in a case makes it easy to examine that data from multiple angles and easily run queries. Similarly, sharing data between law enforcement agencies is also key in many cases across municipal lines, state lines and internationally. Visualization also comes into play here by making sharing data in visual and graphic form easy.
AUTOMATING MANUAL PROCESSES MOVES INVESTIGATIONS FORWARD FASTER
One of the biggest changes in law enforcement in the last decade has been the explosion of video – from body-worn cameras, dash cams, smartphones, social media, security monitoring systems, license plate readers and other sources. In many cases, video evidence is key to successful prosecutions. But video also presents a huge challenge in processing, analyzing, storing and managing the volume of data.
Decision Intelligence tools like NEXYTE use AI and machine learning to analyze video and audio data to search for relevant information, including recognizing individuals, vehicles, weapons, locations, voices and other factors. Consider the efficiency and time-saving advantages of that automated analysis compared to conducting a manual review of hundreds or thousands of hours of video.
Decision intelligence offers similar efficiency gains by automatically using voice recognition to translate video, audio and text messages.
One of the major benefits of decision intelligence is that it simplifies the process of running queries. You don’t have to be a data scientist or technician. For example, any investigator or analyst can quickly query the data to find all individuals in a particular geography “who have previously been associated with a gun crime since 2017 and who drive a red SUV” and run similar queries. In addition, decision intelligence tools use AI to suggest other search and query criteria that may yield positive results.
DECISION INTELLIGENCE ENABLES THE BETTER USE OF RESOURCES
Leaders in law enforcement, intelligence and public safety face a wide range of challenges, but one common challenge for all of them is the pressure to improve efficiency and achieve better results with fewer resources – especially with smaller units. The struggle to recruit and hire qualified police officers is almost universal. Almost 80 percent of law enforcement agencies reported having difficulty recruiting qualified candidates and 75 percent said recruiting was getting harder year over year, according to a recent survey by the International Association of Chiefs of Police (IACP).
Decision intelligence technology can enable agencies to improve operational efficiency by making investigators and analysts more productive and enabling leaders to make better decisions about when, where and how to deploy their resources. Those efficiency gains come from bringing more data together faster than ever before, fusing more diverse types of data and from the automated enrichment of data so that it is more valuable. Visualization and easy-to-use queries can help investigations move forward faster and reveal key insights that would otherwise be missed. The ability to easily share data between teams, up and down the chain of command, between different agencies and across borders improves performance. Dramatic efficiency gains can also come from automating formerly manual processes and using AI and machine learning in analysis and predictive modeling.
The pressures to improve operational results – better clearance rates, less crime, improved public safety and community confidence – will only increase. Achieving improvement will require innovation and embracing the opportunities data analytic tools offer to improve efficiency and effectiveness.
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