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Big Data Surveillance: The Case of Policing

Posted by Douglas Wood, CEO of Case Closed Software – a leader in investigation software  and analytics for law enforcement.

Headquartered here in Central Texas, I recently had an opportunity to have coffee with Dr. Sarah Brayne, Assistant Professor, Department of Sociology at The University of Texas at Austin. Ms. Brayne had just published an interesting article in The American Sociological Review. The article is titled Big Data Surveillance: The Case of Policing.

The article examines the intersection of two emerging developments: the increase in surveillance and the massive exploration of “big data.” Drawing on observations and interviews conducted within the Los Angeles Police Department, Sarah offers an empirical account of how the adoption of big data analytics does—and does not—transform police surveillance practices.

She argues that the adoption of big data analytics facilitates may amplify previous surveillance practices, and outlines the following findings:

  1. Discretionary assessments of risk are supplemented and quantified using risk scores.
  2. Data tends to be used for predictive, rather than reactive or explanatory, purposes. (Here, Crime Tech Weekly would want to differentiate between predictive analytics and investigation analytics)
  3. The proliferation of automatic alert systems makes it possible to systematically surveil an unprecedentedly large number of people.
  4. The threshold for inclusion in law enforcement databases (gang databases, criminal intelligence data, etc) is lower, now including individuals who have not had direct police contact. (Here again, Crime Tech Weekly would point out that adherence to criminal intelligence best practices vastly reduces this likelihood)
  5. Previously separate data systems are merged, facilitating the spread of surveillance into a wide range of institutions.

Based on these findings, Sarah develops a theoretical model of big data surveillance that can be applied to institutional domains beyond the criminal justice system. Finally, she highlights the social consequences of big data surveillance for law and social inequality.

The full PDF report can be downloaded via Sage Publishing by clicking here. Or, if you have general comments or questions and do not wish to download the full version, please feel free to contact us through the form below. Crime Tech Weekly will be happy to weigh in.

A Look at Digital Policing

For law enforcement and other police service agencies, the ability to rapidly manage and interpret massive amounts of data is of paramount importance. Front line officers require timely and accurate data that enables intelligence-led decision making, and officers must be deployed proactively in order to deter and prevent criminal behavior.

abmpegasus-intelligence-led-policingAs we have written before, the true lifeblood of effective policing is data. With disparate and poorly integrated systems, however, the intelligence that can be gleaned from that data is mitigated. The information is too often hidden or lost.

In order to better utilize data – coming from sources such as Records Management Systems, Computer Aided Dispatch, Criminal Intelligence Systems, and other such repositories – innovative law enforcement agencies turn to technology-agnostic, scalable analytics platforms which blend historical and real-time data to both solve today’s crimes and predict tomorrow’s. Supported by purpose-built law enforcement analytics, agencies can keep pace with growing volumes of data and stay one step ahead of the criminals via actionable insights.

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For disparate data to be transformed to actionable insights, law enforcement agencies must deal with several challenges:

  • Timeliness – Unlike fine wine, data tends to lose value over time. Crime happens in real time, and what was the case six months ago may not be the case today.
  • Reliability – The data absolutely must be trusted by the officers entrusted with using it.
  • Fragmentation – If the data is overly fragmented or otherwise unavailable, it becomes cumbersome to use and holds little value.
  • Auditability – Without a clear and recognized audit trail, agencies are not able to effectively track the decisions made in the field versus what the analytics pointed to.

5WAn analytics solution helps blend data from disparate sources in order to provide officers with a trusted, single view of the truth. Simply put, the right analytics software will help agencies manage the challenges above.

While there has been a ton of negative news related to predictive policing, recently, using an analytics platform approach allows agencies to consolidate, analyze, and utilize ALL of their data. This analysis can – and does – help agencies become more efficient and more effective.

Crime Hot Spots and Risk Terrain Modeling

abmpegasus-intelligence-led-policing
A typical ‘hot spot’ in crime analytics

By Tyler Wood, Operations Manager at Crime Tech Solutions.

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.

CrimeMapLite
Advanced crime analytics show statistically significant risk factors.

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.

The author, Tyler Wood, is head of operations at Austin, TX based Crime Tech Solutions – an innovator in crime analytics and law enforcement crime-fighting software. The clear price/performance leader for crime fighting software, the company’s offerings include sophisticated Case Closed™ investigative case management and major case management, GangBuster™ gang intelligence software, powerful link analysis software, evidence management, mobile applications for law enforcement, comprehensive crime analytics with mapping and predictive policing, and 28 CFR Part 23 compliant criminal intelligence database management systems.)

Hail! Jail! The Gang’s All Here!

gangPosted by Crime Tech Solutions

Gangs are everywhere, it seems.

They’re known and feared across the world. Their nasty reputations are due to the nature of their crimes: arson, murder, drug-trafficking, armed robbery, etc.. But today’s street gangs are less The Wire and more Wired.

In the digital era, gangs are putting an increased amount of focus on white-collar crimes. In April, members of a California gang were convicted of crimes including identity theft and credit card fraud.

In New York, a gang made $1,500,000 in a year running a money order scam. A New Jersey chapter of the Crips manufactured counterfeit gift cards. Florida gangs are stealing identities to file false fax returns.

Diedre Butler, a unit chief at the National Gang Intelligence Center, says gangs are switching to financial crimes because, “the likelihood of being caught is less, the sentences once you are caught are less, and the actual monetary gain is much higher.” Gangs are also using social media such as facebook as recruitment tools, and to present an image of toughness online. Authorities are learning to closely monitor social media for evidence of gang activity.

The merging of gang crime and financial crime poses a problem for police departments who often have separate units for dealing with each type of crime. Police also warn that gangs are still as violent as ever, despite their foray into white-collar crimes, causing the NYPD to take measures such as introducing a Grand Larceny Division.

The world is becoming increasingly digitized, and criminals will always follow the money. In order for law enforcement to fight this new wave of crime they must be proactive and adapt to the modern world.

Crime Tech Solutions is proud to deliver GangBuster™ the industry’s price performance leading gang intelligence software.