StreetCred Software Uses Big Data to Slap Cuffs on Inefficiency
Founded by two police officers in Texas, StreetCred is looking to help police agencies deal with a backlog of misdemeanor warrants and collect outstanding fines.While tech-savvy police departments may be common staples of television shows such as "Law & Order," the reality of police work can sometimes be quite different. A case in point is the tracking of Class C misdemeanor warrants in the state of Texas, an activity that for many officers includes the arduous task of verifying, organizing and tracking down information about thousands of offenders. Serving such warrants—and collecting the fines owed by the targets—not only makes police agencies money, but also saves the money it costs taxpayers to incarcerate those unable to pay the fines. Enter StreetCred Software, a new company that founders Nick Selby and David Henderson said is working to put the cuffs on an issue they say is costing taxpayers significant amounts of money. "What we're doing is prioritizing the warrants based on locate-ability and collectability," said Selby, a former analyst with The 451 Group and today a sworn police officer in Texas. "And to do that, we tap into a bunch of law-enforcement computer systems, we tap into a bunch of public records databases, we tap into a bunch of open-source information and open-source intelligence. … [We] aggregate and then we correlate." By correlating information, the software is able to determine a ranking for each warrant based on the accuracy of the information the police have about the person and the likelihood the person will be able to pay if caught. The software also tracks the amounts owed by each person and notifies officers if the person has a history of violence. If an officer checks out the home or work address of the target and determines that it is wrong, he or she can mark it down in the program and change the ranking for the warrant.
The information the company factors in comes from a variety of places, ranging from government to law enforcement to commercial sources, to determine the score of a given warrant. Once that information has been pulled together, the software begins to query it.