September 16, 2016 – (Leander, TX) Crime Tech Solutions, a fast-growing provider of low cost / high performance crime fighting software and analytics is delighted to announce the addition of Jamie May as senior analyst and strategic advisor to the company.
“To me, Crime Tech Solutions represents a truly innovative company that understands how to develop and market very good technology at prices that most agencies can actually afford”, said Ms. May. “I’m looking forward to being part of the continued growth here.”
In her role with the company, Ms. May will interact with customers and prospects to help align the company’s solution strategy with market and user requirements.
Law enforcement agencies everywhere are tasked with reducing and investigating crime with fewer and fewer resources at their disposal. “To protect and serve” is the highest responsibilities one can sign up for, particularly in light of recent well-publicized criticisms of police by activists in every city.
That responsibility weighs even heavier in a world with no shortage of criminals and terrorists. There’s never enough money in the budget to adequately deal with all of the issues that face an individual agency on a daily basis. Never enough feet on the street, as they say.
New Tools for Age-Old Problems
Perhaps that’s why agencies everywhere are moving to fight crime with an evolving 21st century weapon – law enforcement software including investigative case management, link and social network analysis, and, importantly, crime analytics with geospatial and temporal mapping.
Crime analytics and investigation software have proven themselves to be valuable tools in thwarting criminal activity by helping to better define resource allocation, target investigations more accurately, and enhancing public safety,
According to some reports, law enforcement budgets have been reduced by over 80% since the early 2000s. Still, agencies are asked to do more and more, with less and less.
Analytics in Policing
Analytics in law enforcement play a key role in helping law enforcement agencies better forecast what types of crimes are most likely to occur in a certain area within a certain window of time. While no predictive analytics solution offers the clarity of a crystal ball, they can be effective in affecting crime reduction and public safety.
Predictive analysis, in essence, is taking data from disparate sources, analyzing them and then using the results to anticipate, prevent and respond more effectively to future crime. Those disparate data sources typically include historical crime data from records management systems, calls for service/dispatch information, tip lines, confidential informant information, and specialized criminal intelligence data.
The Five W’s of Predictive Analytics
Within this disparate data lie the 5 W’s of information that can be used by crime analysis software to build predictions. Those key pieces include:
Arrest records – who committed crimes
Geospatial data – where crimes have occurred
Temporal data – when crimes have occurred
Statistical data – what crimes have occurred
Investigation data – why (and how) the crimes occurred
Using the 5 W’s, agencies are able to gain insight and make predictions about likely future criminal behavior. For example, if a certain type of crime (what) tends to occur in ‘this’ area (where) at ‘this’ time (when), and by ‘this’ type of individual (who) for ‘this’ reason (why)… it would be wise to deploy resources in that area at that time in order to prevent the incidents from ever occurring. This, of course, is a dramatic over-simplification of the types of analytics that make up predictive policing, but illustrates the general concept well.
Although criminals will always try to be one step ahead of the law, agencies deploying predictive analytics are able to maximize the effectiveness of its staff and other resources, increasing public safety, and keeping bad guys off the street.
A recent report questions how some police departments are using data to forecast future crimes.
The report examined how departments are utilizing predictive policing, a computer software that uses data to forecast where crime may happen, who may commit it and who could be potential victims.
Logan Koepke, an analyst who coauthored the report, said the handful of departments that use the software don’t appear to give patrol officers much guidance on what to do with the information provided.
“One problem we’ve seen is there is not a lot of direction from police departments or from vendors about what officers in the field should do once they look at a prediction,” Koepke said.
Upturn, an analysis organization out of Washington, D.C., that works with a variety of groups, published the report “Stuck in a Pattern” last month. “Predictive policing,” the report states, is a marketing term popularized by vendors who sell the software.
The group’s research showed areas that use the software often don’t engage the public in discussion about predictive policing and questioned whether or not departments who use it are measuring the impact the data-driven tool has on policing and crime rates.
How police departments nationwide utilize crime statistics and the software available to patrol officers monitoring incidents has evolved a lot in the past couple decades, Sgt. Tracy Barton with the St. Joseph Police Department said. Barton started as a patrol officer 20 years ago. He said having software like police have today would have been useful.
“I was in District 7, which is the Midtown area. It would have been really cool to know where crime is occurring in District 7 and that I could look that up on a computer and have it at my fingertips where I could see it on an up-to-date basis,” Barton said.
In the past, crime analysts used physical maps and mathematical algorithms to do what software does instantly today. Barton, the St. Joseph Police Department’s crime analyst, uses software that takes into account crimes reported to police to show crime hot spots in the city. A map of those hot spots is available online. Officers, he said, have access to a more in-depth version of that hot spots map, which includes extra details about the area and the crimes occurring.
The hot spots approach St. Joseph police use is most helpful in preventing crime when a series of crimes occur or when there is a crime pattern in a given area, he said. St. Joseph’s small size, Barton added, poses an extra challenge.
The St. Joseph Police Department has had its current software for just a few years. It doesn’t fit the definition of the predictive policing software Upturn outlines in the recent report. The software used locally depends on crime reports police receive. Predictive policing also looks at what types of business are located in an area, if repeat offenders live nearby and other information to predict where crimes may occur. Typically, according to the recent report, predictive policing takes one of two approaches, focusing either on place-based data or person-based data to make predictions.
Kevin Bryant, sociology and criminology professor at Benedictine College, said when people hear predictive policing described, they often think of the movie “Minority Report.” The software, he said, is nothing like in the movies.
“Predictive policing now has kind of morphed into better proactive methods that are based on prediction to some extent in forecasting risk,” Bryant said of how data-driven policing has changed over time. “But what we’ve learned through evaluation studies is that it’s really more important what the police do when they’re in a crime hot spot.”
Bryant worked with the Shawnee, Kansas, Police Department on research that looked at what he calls “smart policing.” In his research and in other work he has read, Bryant said it’s important for police to have a high visibility in crime hot spots, for officers to make connections with the public and for them to avoid staying in crime hot spots for extended periods of time.
When police are in a hot spot for too long, public surveys show area residents feel like they are being picked on rather than protected, he said. Predictive policing takes into account businesses in a given area. Bryant said some types of facilities are at a higher risk of victimization and others can attract crime to an area.
“Knowing where bars, taverns, restaurants, gas stations, convenience stores are, we can actually use their locations as a means of forecasting where crime might emerge at a later date,” Bryant said. “Part of predictive policing is predicting who the risky offenders are and that can be controversial.”
Upturn’s report also explored an ongoing debate among criminologists on the impact of using crime reports when determining patrol.
“Criminologists have long emphasized that crime reports and other statistics gathered by the police are not an accurate record of the crime that happens in a community,” the report states.
Police statistics, Koepke said, reflect officer enforcement efforts, not just crime.
The notion of predictive policing is hotly debated. Some suggest that the technology removes the elements of racial bias in policing. Others claim that it does little to improve public safety. In fact, the predictive policing world took a hit recently when Milpita Police Department in California canceled a contract with software provider PredPol, suggesting that the tool offered little in way of ROI.
Predictive policing refers to the usage of mathematical, predictive and analytical techniques in law enforcement to identify potential criminal activity. Pulling in data from a variety of sources such as arrest records, calls for service, and geospatial (location) data, the promise of predictive policing offers law enforcement a statistical probability that a crime may occur in a particular location within a particular period of time.
Advocates say ‘Great, let’s prevent the crime from happening’. Opponents say ‘The output is only as good as the input’. In other words, there are claims that a reliance upon historical data unduly influences the prediction. The position suggests that if police have tended to make arrests in Location A, then of course predictive policing will suggest patrolling Location A.
That argument has some holes, however; not the least of which is the very simple fact that historical data is the only kind of data that can ever exist. It has to happen before it’s data. The best indicator of future behavior is past behavior, says the pro-predictive policing side.
Predictive policing methods are not a crystal ball: they cannot foretell the future. They can only identify people and locations at increased risk of crime … the most effective predictive policing approaches are elements of larger proactive strategies that build strong relationships between police departments and their communities to solve crime problems.
This same RAND statement was printed today by Dan Verton at MeriTalk. In an article entitled “Policing Data Sees Beyond Black and White“, Mr. Verton does an excellent job of discussing predictive policing in the context of current racial tensions in many US cities. The backdrop for the MeriTalk story is a new book by Manhattan Institute fellow Heather Mac Donald who, in her book “The War on Cops: How the New Attack on Law and Order Makes Everyone Less Safe“, uses data and data analytics to counter the argument that America’s police departments are engaged in a campaign of racial bias.
Our take is that predictive policing has merit. It is an important part of the law enforcement arsenal. Unfortunately, the term ‘Predictive Policing’ has also become a buzzword used by software vendors who aim to stake their claim in the law enforcement data analytics game. As a result of the gross overuse of the term, the predictive policing waters have become muddied.
Disagree? We entered the term into Google today and found about 350,000 unique pages.
We also think that the lack of ROI cited in Milpitra PD’s cancellation with PredPol is largely a result of costs. The promise of predictive policing, coupled with the over-hyped flame fanning of advocates (mostly vendors) has made the software relatively expensive.
Nevertheless, it’s hard for law enforcement to deliver a strong predictive policing ROI if they were over sold on its’ merits to begin with. The good news is that the hype is on the downswing and reality is setting in: Predictive policing is not the next greatest thing. Instead, as we suggest, it is an important tool that law enforcement can use to combat and prevent crime.
One of the many functions crime analysis performs is the identification of “hot spots”, or geographical areas that seem to be hubs for criminal activity. Identifying these hot spots through best practices in geospatial crime mapping allows law enforcement to focus their efforts in areas that need them most. The trouble that law enforcement and crime analysts have encountered is displacement – the fact that once a hot spot is “cleared”, crime seems to pop up again in a different location. The good news is that the displacement is never 100%, so policing hot spots is important – it’s just not a magic bullet.
To solve this problem, a team at Rutgers University’s School of Criminal Justice set out to develop new methodologies that would result in peaceful outcomes that are built to last instead of merely temporary.
The difference between the old approach and the new approach is stark. Where police and analysts used to focus solely on geographical concentration of crimes, Risk Terrain Modeling examines the factors that contribute to such dense concentrations to begin with. Rutgers team have identified several characteristics of any given geographical location which may attract or generate crime. Their technology takes these characteristics, which include socioeconomic data, physical layout, types of local businesses, etc… and uses them to calculate the likelihood crime occurring in the area. This allows law enforcement to be proactive in the prevention of crime in these areas.
The technique seems to be highly effective. After a trial run in New Haven, CT, police were able to identify sixteen “statistically significant risk factors that underlie violent crime occurrences.” A high percentage of violent crime in New Haven during the test period occurred in locations already identified by the concept of risk terrain modeling. Though the technology is still new, it is clearly showing impressive results already.
Shutting down hot spots is important policing, and risk terrain modeling technology allows analysts and law enforcement officers to be even more proactive in their prevention of crime.
June 1, 2016 (Austin, TX) Crime Tech Solutions, LLC, a leading provider of analytics and investigation software for law enforcement and commercial markets, today announced that it has acquired Cleveland, TN based Case Closed Software in a cash transaction. The terms of the deal were not released, but according to Crime Tech Solutions’ founder and president Douglas Wood, the acquisition brings together two dynamic and fast-growing software companies with an unparalleled complement of technologies.
“For Crime Tech Solutions, the opportunity to add Case Closed Software into the fold was too good to pass up” said Mr. Wood. “We think that the technology offered by Case Closed helps to further differentiate us in the market as the price performance leader for this type of investigative solution.”
Crime Tech Solutions, based in the city of Leander, TX, delivers advanced analytics and investigation software to commercial investigators and law enforcement agencies across the globe. Their solution suite includes criminal intelligence software, sophisticated crime analytics with geospatial mapping, and powerful link analysis and visualization software. The company says that the addition of Case Closed Software expands those offerings even further.
Case Closed Software develops and markets investigative case management software specifically designed for law enforcement agencies. The suite is built around four primary software products including best-in-class investigative case management software, property and evidence tracking, a gang database tool, and an integrated link analysis and data visualization tool. The company also plans to release the solution as Case Closed Cloud for cloud-based access.
“Case Closed couldn’t be happier than to be joining Crime Tech Solutions,” said Keith Weigand, the company’s founder. “The blending of our technologies creates a suite that will add tremendous value to our mutual customers, and will be hard for others to duplicate.”
According to both Mr. Weigand and Mr. Wood, the name Case Closed will continue on as the product brand, given its widespread popularity and loyal customer base. Crime Tech Solutions is expected to retain all Case Closed employees, with Mr. Weigand joining as the company’s chief technical officer.
Crime Tech Solutions says it expects continued growth via ongoing software sales and strategic acquisitions.