Analyzing Auto Theft And Theft From Autos In Parking Lots .
THEFT OF AND FROM AUTOSIN PARKING FACILITIES INCHULA VISTA, CALIFORNIAA Final Report to the U.S. Department of Justice,Office of Community Oriented Policing Serviceson the Field Applications of the ProblemOriented Guides for Police ProjectRANA SAMPSON, AUGUST 2004This project was supported by cooperative agreement #2001CKWXK051 by the Office ofCommunity Oriented Policing Services, U.S. Department of Justice. The opinions containedherein are those of the author(s) and do not necessarily represent the official position of the U.S.Department of Justice. References to specific companies, products, or services should not beconsidered an endorsement of the product by the author or the U.S. Department ofJustice. Rather, the references are illustrations to supplement discussion of the issues.SummaryIn Chula Vista, CA, a city 10 minutes fromthe Mexican border, auto theft and theftfrom auto account for 44 percent of thecity’s total crime index 1 . Using RonClarke’s problem-oriented policing guidesummarizing the research and effectivecountermeasures to auto theft and theft fromauto in parking facilities as a framework 2 ,the Chula Vista Police Departmentconducted a detailed review of its vehiclecrime problem, finding that ten parking lotsin Chula Vista, and the adjacent parking lotsto them, accounted for 22 percent of allvehicle crime in the city. The reviewincluded analysis of vehicle theft andvehicle break-ins by vehicle type, model,and year; recovery rates of stolen vehicles inthe target parking lots, for all of Chula Vista,and other cities in San Diego county; ratesof theft in Chula Vista’s high volume autotheft parking lots; an analysis of time parkedbefore the theft was noticed; revictimization;trend data for auto theft; monetary value ofproperty loss; vehicle theft rates by SanDiego county cities; offender interviews; lotmanager interviews and environmentalassessments of the lots; and an analysis ofborder point interventions versus parking lotinterventions. The results of the analysisrevealed offenders making highly rationalchoices in target selection and masking theircrimes with the legitimate routine activity inthese lots. The project results also suggestfor Chula Vista (and potentially other U.S.border cities to Mexico) that border pointinterventions are less effective than parkinglot interventions in reducing auto theft. Thisproject also confirms the value of thisparticular POP guide and its step-by-stepapplication to reducing theft of and fromautos in parking facilities. 3
IntroductionThe purpose of this Field Applications POPProject, funded by the U.S. Department ofJustice, Office of Community OrientedPolicing Services, was fourfold: 1) assist theChula Vista Police Department in findingmore effective responses to auto theft andtheft from auto in parking lots; 2) reducevehicle crime in those lots; 3) assess theutility of the problem-oriented policingguide entitled Thefts of and from Autos inParking Facilities (the Guide); and lastly, 4)improve the police department’s capacity toroutinely problem solve. 4 This paper reportsfindings from Chula Vista’s examination ofauto thefts and theft from autos in parkinglots.Chula Vista, a 50-square mile suburbancommunity bordering the Pacific Ocean, isapproximately seven miles north of theMexican border. With a 2000 censuspopulation of approximately 173,000residents, Chula Vista is a fast-growing,diverse community. To the south, one slip ofthe city of San Diego borders the southboundary of Chula Vista, resting betweenChula Vista and the border to Mexico. TheSan Diego Police Department’s SouthernDivision polices this part of San Diego. Thecity directly north of Chula Vista is NationalCity, a small, generally high crime city witha 2000 census population of under 60,000.The vast majority of the city of San Diegosits on the northern border of National Citywith a 2000 census population of 1,200,000making it the seventh largest city in theUnited States. Chula Vista, National City,San Diego, along with a number of othercities and unincorporated areas, compriseSan Diego County, whose population in2000 slightly exceeded 2,800,000. Thecounty’s northern border is Camp Pendleton,a Marine Corps base. North of this base isOrange County.Chula Vista is a city of residential andcommercial streets bisected by two mainNorth-South freeways. These freeways,Interstate 5 and 805, traverse Chula Vistaconverging at the Mexican border. (SeeAppendix 1, Figure 1)Initial site selectionThe COPS Office selected the Chula VistaPolice Department (CVPD) for participationin the project. In November 2001, the CVPDdecided upon the problem of auto theft/theftfrom auto in parking facilities forexamination (among the 19 guidebookproblems available at that time) for severalreasons. The CVPD surveyed its employees(both civilian and sworn) seeking input onthe most important crime or safety problemsin Chula Vista. The five problems receivingthe most nominations included burglary ofsingle-family homes, thefts of and from carsin parking facilities, drug dealing inprivately owned apartment complexes, falseburglar alarms, and speeding in residentialareas. Mid-managers and command staffconvened to discuss the importance of eachof these problems, reviewing availableinformation on trends and harms, and theutility of a POP guide to Chula Vista’sspecific problems. Ultimately, this groupselected thefts of and from cars in parkingfacilities for the following reasons: The auto theft problem in ChulaVista appeared disproportionatelyhigh for a city of its population. Asfor theft from vehicles, the groupbelieved that this too wasdisproportionately high, particularlysince this crime is generallyunderreported. Auto theft rates rose 15 percent in2000 through much of 2001, (whileresidential burglary rates declinedeight percent since 1999). Because residential burglary rateshave declined significantly since the2
mid-1990s, only an estimated 240single-family burglaries (the focus ofthe residential burglary problemsolving guide) were expected tooccur in 2001; in comparison, anestimated 1280 incidents of theftof/from auto in public lots wereexpected to occur in 2001. Data gathered for the meetingshowed that during a 3-month periodin the spring of 2001, approximatelynine percent of all auto thefts in theCity of Chula Vista occurred in justfour public lots (Wal-Mart; Target;Home Depot; and the Swap Meet lot)suggesting a good fit between thisPOP guide and the problem. The group believed that vehiclecrime in lots could be reduced sincelots had borders and they belonged toa person who or an entity that couldexercise greater control over them. Previous efforts to address public lotauto theft at one lot had been verysuccessful. Auto thefts at ChulaVista Mall were reduced nearly 40percent between 1998 and 2001 as aresult of problem-solving efforts atthat location.Chula Vista’s Uniform Crime Report(UCR) Index crimes are dominatedby motor vehicle thefts and larcenies(many of the larcenies are actuallythefts from vehicles). In fact, there isa perception in the County that ChulaVista is high crime because of itsrelatively high number of crimes. Ifvehicle crime could be reduced (anestimated 17 percent of the totalUCR Index crimes were theftsof/from autos in public lots) thenperhaps the perception that ChulaVista is high crime could be turnedaround.Once the problem type was selected, wepresented specific information from theGuide to higher-ranking members of theDepartment. Next, we began to gather andanalyze information related to vehicle crimefrom the CVPD’s files. We reviewed 2000 and 2001 data forlocations that had the highest volumeof auto theft and the locations thathad the highest volume of vehicleburglaries. 5 We decided to use 2001data for all further analysis, eventhough there were some slightdifferences between years 2000 and2001, since the frequency of thethefts were great enough in a oneyear time frame to discernmeaningful, more recent patterns. For 2001, there were 1,714 autothefts, and 1,656 vehicle burglariesin Chula Vista representing 44percent of all Part I crimes in ChulaVista. These vehicle crimes occurredin public lots and streets and privatelots and areasFinding Meaningful ParametersWe began a search to identify the locationsin Chula Vista where vehicle crimesclustered. We found that six of the ninehighest volume auto theft locations in theCity coincided with the highest volume autoburglary locations. We used aerial (ortho)photos of these top nine locations to allowus to visually distinguish parking lots fromother types of locations. Using ArcView, thecrime analyst layered parcel addresses ontothe aerial photos. All of the top nine highvolume locations were parking lots,however, two were apartment complexprivate parking lots, not public lots (thefocus of the guidebook is on public lots).We skipped these two apartment complexlots and chose the next two high volumelocations.3
We then chose a tenth location, whichrequires an additional explanation. Werealized that Chula Vista’s five high schoolshad a fair amount of vehicle crime.Although no individual high school made itonto our top ten list, when grouped, theirvolume of vehicle crimes elevated them tonumber nine on our list. Because the issuesat these high schools are similar, and they allhave the same lot owner, the SweetwaterUnion High School District, we believe thatgrouping these as one target site providesthe benefit that CVPD would be able topresent a more robust data set to the SchoolDistrict when offering strategies to reducetheir vehicle crime problem. With the highschools as one target, we now had tentargets.While using ArcView, we were able to seethe types of properties adjacent to our targetlots. Unfortunately, we found that many ofour target lots were adjacent to other parkinglots. We decided to add in these adjacentlots to lessen displacement opportunities.We viewed adjacent lots as probabledisplacement sites. By paying close attentionto these lots upfront and ultimatelyrecommending countermeasures for vehiclecrime in these adjacent lots we believed wewould minimize any displacement. 6We designated each of the groupings – ourten volume lots with their adjacent lots asone of ten target areas. We determined thatif we grouped in these adjacent lots, wecaptured 22 percent of all vehicle crime inChula Vista. Some of the adjacent lots weresmall, however, they added over 40additional lots to our analysis. The analystdrew polygons around each of the targetareas exporting the vehicle crime data fromthese into a database file to begin furtheranalysis of the vehicle crimes contained inthose target areas.These ten targets accounted for 387 autothefts and 293 vehicle burglaries – 25percent of the city’s auto thefts and 20percent of the city’s auto burglaries. Whilesome of the target areas had only one ownerand one lot address (Southwestern College),others had many owners, as well as adjacentlots with different addresses and lot owners(Broadway and Palomar).We discovered that our target lots also hadhigh levels of calls for service to police, aswell as police initiated calls. Six out of theten target areas were also among ChulaVista’s top ten police call for servicelocations, indicating that these lots were notjust vulnerable to vehicle crime but weregenerally crime and disorder magnets. Callsfor service ranged from minor disputes anddisturbances to violent crimes. We believeapplying effective responses to vehiclecrimes in our lots will also reduce many ofthese other police calls, as enhancedguardianship of these lots by lot owners andmanagers will produce a diffusion ofbenefits 7 over a wider array of public safetyproblems there. (See Appendix 1, Table 1)Geographic distribution of targetsInitially, we could have chosen all our targetlots from a more specific part of ChulaVista, such as the downtown area on thewest side, as vehicle crimes are likely toconcentrate in lots there. 8 However, ChulaVista’s fast-growing suburban areas on theeast side of town contained some of our autotheft hot spots, so we decided to use theentire city in analyzing the volume ofvehicle crime.We found that seven of the 10 target areas,and three of the five high schools in TargetArea 9 were on the west side of Chula Vista.The west side of Chula Vista has an olderdowntown area with many businesses,although it is still predominantly residential.Calls for service and crime rates are higherin this area of the city than in the Easternsection. The largest shopping mall in ChulaVista, Target 3, is among the target areas on4
the west side. The dividing line between Chula Vista’s eastand west side is Interstate 805. The east sideof the city contains three target areas,Southwestern Community College (Target8), the East H Street Shopping Center(Target 1), and two of the five high schoolscontained in Target 9. The east side of ChulaVista is predominantly residential, dottedwith recent or new housing developmentsand shopping areas. It is a middle- to upperincome community, with substantiallyhigher income levels than the west side. We determined that the highest risk lots(risk rates of lots will be discussed in detaillater in this paper) were generally locatedwithin one-tenth of a mile of a freeway.Medium risk lots averaged three-quarters ofa mile to a freeway. The lowest risk lots ofthe ten targets averaged 2.5 miles to thefreeway. (See Appendix 1, Figure 2)Analysis SubcommitteesOnce we developed some preliminaryparameters for the project, we outlined ananalysis plan, in part fashioned from theanalysis questions in the problem-orientedpolicing guide, and in part designed tocapture some of the unique qualities ofborder communities. We divided theanalysis work into to seven groupings. Fromthese groupings, we formed sevensubcommittees and tasked each withinformation gathering. The subcommitteeswere as follows: Theft of vehicle problem in ChulaVista’s target lotsTheft from vehicle problem in ChulaVista’s target lotsOffendersRisk rates in Chula Vista’s targetslotsEnvironmental design andmanagement practices in ChulaVista’s target area lotsAuto theft prosecution and auto theftinsurance fraud in Chula VistaNational comparisons for vehiclecrime (other cities, including bordercities)Based on the earlier survey we administeredwithin the CVPD, we found that more than50 employees expressed interest in assistingon this project. 9 We shared with theseemployees the information gathering taskswe expected from each of thesubcommittees and asked interestedemployees to select a subcommittee. Alieutenant, sergeant, agent or civilianmanager in the CVPD chaired thesubcommittees. As a first step, thesubcommittee members were asked to readthe POP guide, and in some cases specificresearch articles pertaining to theirsubcommittee topic. In addition, we askedthat subcommittee members provide us withfeedback on the POP guide and itsapplication to Chula Vista’s vehicle crimeproblem (project goal number 3). We alsoasked that subcommittee membersdetermine, based on their reading and theirpolicing experiences, if it would be valuableto collect any additional information beyondthe tasks we initially outlined and thoseoutlined in the Guide.We found there was value in engaging somany Department employees in the project.Since vehicle crime represented 44 percentof all Part I crimes in Chula Vista, webelieved participating employees woulddevelop a greater understanding of ChulaVista’s vehicle crime problem and becomeexposed to research-based approaches toreduce it (project goal number 1). We alsobelieved involvement in a high levelproblem-solving project was a good methodof introducing problem-solving toemployees less familiar with it while itcould also enhance the problem-solvingskills of those employees already familiarwith it (project goal number). In addition,these employees allowed us to:5
Share time-consuming informationgathering tasks among a wider groupof people, minimizing the burden ona single individual, for instancecarrying out surveys (environmental,management practices, and offenderinterviews)Provide us with a diversity of inputon tasks and response strategiesLimit the average amount of timespent by each subcommittee memberto approximately one hour perweek. 10Hold ourselves publicly accountablewith their interest in the projectFacilitate employee problem-solvingon other crime problems (projectgoal number 4)Data GapsIt is worth noting that during the vehicletheft analysis, we encountered a series ofdata gaps, each needing resolution. Policedepartments in San Diego County (ninemunicipal, one county, and several collegeand secondary school police agencies) sharea countywide computer database system.These police agencies share the same crimereporting form so that agencies can compareinformation across cities and the county.Each police department can access theirdata, as well as countywide data. A policedepartment can look at another city’s databut not export it for analysis. The gaps fellinto two different categories:1. Report writing/data entry gaps2. Countywide data system gapsReport writing/data entry gapsIn Chula Vista, reports of auto theft can betaken in person by an officer or acommunity service officer, or over thephone to a community service officer orcadet. 11 Many times, these report-takersneglected to fill out a number of the crimereport boxes, particularly the time of theftdiscovery, and make and model information,particularly for trucks. This is not surprising,as the form is somewhat confusing in thisregard. Many times, these report writersplaced information about the timeframe forthe auto theft in their report narratives,however, data entry operators only enterinformation from the cover sheet boxes notfrom the narrative description of the crimecaptured on the form’s second page.In addition, many of these officers used astreet’s one-hundred block address for anauto theft occurring in a lot, not realizing theimportance of specifying the exact addressfor the lot. Each lot has a distinct address,however, officers were generally unaware ofthem. The reporting form also requires thatofficers determine and check off whether thevehicle was stolen from a) the street b) agarage c) a parking lot d) a driveway or e)other. For the most part, officers left theseboxes blank, unaware of their importance inauto theft analysis. Even in those caseswhere one of the boxes was checked, thecountywide data entry system does not havea data-field to collect this information (eventhough these boxes exist on the countywideform) so we could not compare the extent ofChula Vista’s lot theft to other cities withoutlooking through individual reports submittedto the county system from these other cities.Remedy: We pulled by hand everyChula Vista report for 2001 that wasmissing data or solely contained onehundred block data (as opposed toexact address). Often the narrativecontained the needed information, ifnot, we found some other way todetermine this information. Wefiltered out all reports that werestreet thefts allowing us to focus onthe lots.Among the theft from auto reports, we foundthat officers often incorrectly reported theftof vehicle parts, such as theft of an in-dash6
car stereo, license plate, vehicle wheels orafter-market body kits. Report-takersfrequently reported these incorrectly as theftfrom vehicles.Cure: Once again we hand pulled reportsto determine accuracy. As it turned out,accurate labeling helped us uncover atheft of parts problem in a movie theatrelot. The amount of time moviegoersspend in the theatre guaranteed thatoffenders had sufficient time (once themoviegoer parked) to dismantle parts ofthe car unnoticed. To correct this andother reporting problems, we providedtraining to every Chula Vista policeofficer and CSO on accurately reportingvehicle crimes. 12 Cure: As a result, for much of ourdata we used the separate databasekept by CVPD. For those countyreports with missing information wehand pulled reports
clustered. We found that six of the nine highest volume auto theft locations in the City coincided with the highest volume auto burglary locations. We used aerial (ortho) photos of these top nine locations to allow us to visually distinguish parking lots from other types of locations. Using ArcView, the crime analyst layered parcel addresses onto
between auto theft/vehicle crime and general violent crime. Despite data collection challenges, a study facilitated by the Colorado Auto Theft Prevention Authority and the Colorado Auto Theft IntelligenceCoordination Center found a strong connection between auto theft and a wide range of other crimes:
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IDENTITY THEFT If you are a victim of identity theft, or you suspect that someone is using your name . and your notarized ID Theft Affidavit (located at the back of this kit). Identity theft is a Class D Felony under KRS 514.160. Theft related to credit or debit cards is a Class A Misdemeanor or Class D Felony under KRS 434.550 - 434.730. 2 .
Lookout's Phone Theft in America report, a survey of smartphone theft victims conducted by IDG Research, examines the smartphone theft epidemic in the U.S. The report found that 1 in 10 U.S. smartphone owners are victims of phone theft and 68 percent of victims were unable to recover their device after the theft occurred.
Identity Theft Unit in response to increased identity theft incidents reported by Indiana citi-zens and to enhance existing efforts to educate Hoosiers about protecting their identities. The Identity Theft Unit assists ID theft victims and provides investigative services to help promote the prosecution of identity thieves.
Scope of the ID Theft Problem In 2014: 17.6 million people were victims of identity theft Up from 8.1 million in 2010 The ID theft fraud amount was 18 billion Down from all time high of 48 billion in 2010 Every 2 seconds there is a new identity fraud victim To correct ID theft and restore credit, victims spent .
Accounting The Accounting programme is written by Niall Lothian, formerly Professor at Edinburgh Business School, Heriot-Watt University, and John Small, Professor Emeritus at Heriot-Watt University. Both have previously occupied chairs in the University’s Department of Accountancy and Finance.
