1 Presentation to the Greater Albuquerque Chamber of Commerce Board of Directors October 26, 2017
2 Research & Strategic Crime Analysis New Collaborative Crime-Fighting Initiatives Places Crime Concentration in ABQ ALeRT Analysis Led Recidivism Team People Arrestee Characteristics, Behavior CSU Crime Strategies Unit Perceptions Resident Insights SCAN Security Camera Analytical Network
Crime Context 3
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 4 Context: A Crime Spike in Albuquerque Overall Crime Rate Per 100,000 Inhabitants 12,000 10,000 Unprecedented spike in crime 8,000 6,000 4,000 2,000 Historically-low crime rate years 0
5 Context: A Crime Spike in Albuquerque 2013 2014 Change ( 13-14) 2015 Change ( 14-15) 2016 Change ( 15-16) Change ( 13-16) Violent Crime Incidents Murder 37 30 (-19%) 46 (+53%) 61 (+33%) (+65%) Rape 439 402 (-8%) 404 (+0.5%) 381 (-6%) (-13%) +26% Violent Crime Rate (2014-2016) Robbery 1,046 1,381 (+32%) 1,686 (+22%) 1,957 (+16%) (+87%) Agg. Assault 2,803 3,121 (+11%) 3,273 (+5%) 3,846 (+18%) (+37%) Property Crime Incidents +26% Property Crime Rate (2014-2016) Burglary 7,297 6,123 (-16%) 5,996 (-2%) 6,236 (+4%) (-15%) Larceny 20,229 20,756 (+3%) 22,818 (+10%) 24,582 (+8%) (+22%) Auto Theft 3,005 3,558 (+18%) 5,179 (+46%) 7,710 (+49%) (+157%) Source: Uniform Crime Report Data, Provided by APD
Crime Concentration in ABQ 6
7 Example: Residential Burglary vs. Robbery Property Residential Burglary Violent Robbery of Individual
8 Example: Residential Burglary vs. Robbery Property Residential Burglary Violent Robbery of Individual AUG
9 Five Key Areas: Violent Crime Concentration Cluster Area (sq. mi.) Percentage of City Area Population Percentage of City Pop. Area 1: SE/Primary 5.54 2.93% 37,631 6.73% Area 2: Downtown 0.69 0.37% 2,597 0.46% Area 3: Far Southeast 0.75 0.39% 4,945 0.88% Area 4: San Mateo 1.74 0.92% 6,419 1.15% Area 5: Southwest 0.69 0.37% 5,700 1.02% Total 9.41 4.98% 57,292 10.23% Courtesy of Albuquerque Journal
10 Violent Crime Concentration 49.0% of Non-Fatal Shootings with Injury 43.6% of Murders 36.2% of Robberies/Individuals 34.5% of Aggravated Assaults 5 Crime Clusters 5% of ABQ Area 10% of ABQ Population 29.4% of Non-Fatal Shootings without Injury 27.0% of Carjackings 26.3% of Home Invasions 19.7% of Robberies/Commercial
11 Property Crime Concentration 23.7% of Commercial Burglaries 22.3% of Auto Thefts 17.5% of Larcenies 16.6% of Residential Burglaries 5 Crime Clusters 5% of ABQ Area 10% of ABQ Population 14.3% of Auto Burglaries
12 Arrestee Address Concentration 42.3% of Carjackings 39.1% of Robberies of Individuals 34.0% of General Robberies 31.4% of Aggravated Assaults 26.1% of Murders 5 Crime Clusters 5% of ABQ Area 10% of ABQ Population 23.5% of Commercial Robberies 33.1% of Residential Burglaries 31.3% of Commercial Burglaries 28.5% of Larcenies 26.0% of Auto Burglaries 23.4% of Auto Thefts
13 Example: Arrestee Addresses vs. Incidents Arrestee Addresses - Residential Burglary Incidents Residential Burglary
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Central Avenue Crime 15 Concentration
Arrestee Characteristics, Behavior 16
17 Breaking the Crime Cycle: A Study on the Characteristics and Criminal Activity of Arrestees in Bernalillo County Research Goal Provide a comprehensive understanding to the justice system and broader community of the size, composition, and criminal behavior of arrestees in Bernalillo County Research Purposes Strategic Crime Analysis Make discoveries that are operationally useful to justice system agencies in the short-term and capable of supporting greater collaboration and long-term decision making Data Integration Lay a successful foundation for future efforts to integrate data across the justice system and with other types of agencies, and establish standards and practices for this work Note: This research project uses law enforcement and jail data to study those who have been arrested for crimes in Bernalillo County. Currently, the master data set does not contain any data relating to the disposition of these arrests/cases.
18 Breaking the Crime Cycle: Data Sources APD BCSD DPS MDC Arrests, Citations, and Summons Arrests, Citations, and Summons Statewide Fingerprint Cards County Jail Bookings VA Tech ABQ i-team UNM Master Arrestee Data Set Period of Study: January 1, 2010 December 31, 2016 (7 Years) 557,828 Total Charges 311,939 Total Arrests/Bookings 127,519 Total Individuals
19 Today s Key Insights 1. A small number of people are responsible for a large share of total arrests and felony arrests. 2. Those who have a felony arrest in their criminal history are more likely to have longer arrest records. 3. As a person s arrest record lengthens, they are highly likely to pick up a violent crime arrest and a felony-level arrest at some point; however, a large share of their arrests continue to be for lower-level offenses and most are for drug, property, or public order crimes. 4. Arrestees tend to be generalists in nature; they are not likely to specialize in committing one particular type of crime.
Distribution of All Arrestees: 20 1-Time vs. Repeat Arrestees Among All Arrestees 2.5 mean number of arrests 1-Time Arrestees 58% Repeat Arrestees 42% Among All Repeat Arrestees 4.5 mean number of arrests Number of Total Arrests Number of Arrestees Percent of Total Just 1 74,577 58.5% More Than 1 52,942 41.5% Total 127,519 100.0%
Distribution of All Arrestees: 21 Total Arrest Count 2 Arrests 16% 3 Arrests 8% 4 Arrests 5% 5 Arrests 3% 6 Arrests 2% 5+ Arrests 13% 7 Arrests 2% 8 Arrests 1% 9 Arrests 1% 10+ Arrests 4% 1 Arrest 58% NOTE: The maximum number of arrests for any one person was 78 (arrests largely occurred outside of Bernalillo County), with the next closest being 64. 1 Arrest 2 Arrests 3 Arrests 4 Arrests 5 Arrests 6 Arrests 7 Arrests 8 Arrests 9 Arrests 10+ Arrests Total Arrestees 74,577 19,944 9,781 6,035 4,283 2,963 2,168 1,784 1,315 4,669 127,519
22 Disproportionate Impact of Certain Arrestees 4,669 People with 10+ Arrests 0.8% of City Pop. 3.7% of Arrestees 20.4% of all arrests (63,515 Arrests) 5,626 People with 4+ Felony Arrests 36.3% of all felony Arrests (29,867 Felony Arrests) 1% of City Pop. 4.4% of Arrestees
23 Today s Key Insights 1. A small number of people are responsible for a large share of total arrests and felony arrests. 2. Those who have a felony arrest in their criminal history are more likely to have longer arrest records. 3. As a person s arrest record lengthens, they are highly likely to pick up a violent crime arrest and a felony-level arrest at some point; however, a large share of their arrests continue to be for lower-level offenses and most are for drug, property, or public order crimes. 4. Arrestees tend to be generalists in nature; they are not likely to specialize in committing one particular type of crime.
Distribution of Arrestees with 1+ Felonies: 24 1-Time vs. Repeat Arrestees Among Arrestees with 1+ Felonies 4.3 mean number of arrests 1-Time Arrestees 28% Repeat Arrestees 72% Repeat Arrestees with 1+ Felonies 5.6 mean number of arrests Number of Total Arrests Number of Arrestees with 1+ Felony Arrests Percent of Total Just 1 11,632 27.6% More Than 1 30,521 72.4% Total 42,153 100.0%
Distribution of Arrestees with 1+ Felonies: 25 Total Arrest Count 3 Arrests 12% 4 Arrests 9% 5 Arrests 8% 2 Arrests 16% 6 Arrests 6% 5+ Arrests 35% 7 Arrests 4% 8 Arrests 4% 9 Arrests 3% 10+ Arrests 10% 1 Arrest 28% 1 Arrest 2 Arrests 3 Arrests 4 Arrests 5 Arrests 6 Arrests 7 Arrests 8 Arrests 9 Arrests 10+ Arrests Total Arrestees 11,632 6,813 5,082 3,962 3,199 2,401 1,893 1,578 1,218 4,375 42,153
26 Today s Key Insights 1. A small number of people are responsible for a large share of total arrests and felony arrests. 2. Those who have a felony arrest in their criminal history are more likely to have longer arrest records. 3. As a person s arrest record lengthens, they are highly likely to pick up a violent crime arrest and a felony-level arrest at some point; however, a large share of their arrests continue to be for lower-level offenses and most are for drug, property, or public order crimes. 4. Arrestees tend to be generalists in nature; they are not likely to specialize in committing one particular type of crime.
Distribution of Arrestees by Crime Category 27 of Most Serious Arrest 1-Time Arrestees 4-Time+ Arrestees 8-Time+ Arrestees 8.81% 30.38% 23.28% 13.60% 18.23% 17.73% 19.36% 6.87% 18.28% 62.38% 71.90% Note: Data distributed represent highest arrest category of 98.2% of the 1-time arrestee population, with 1,331 records unknown. Data distributed represent highest arrest category of 99.98% of the 4-time+ arrestee population, with 4 records unknown. Data distributed represent highest arrest category of 100% of the 8-time+ arrestee population.
Distribution of Arrestees by Charge Class 28 of Most Serious Arrest 1-Time Arrestees 4-Time+ Arrestees 8-Time+ Arrestees 4.32% 4.71% 6.86% 5.57% 10.30% 16.88% 13.62% 17.84% 31.53% 25.52% 36.43% 42.91% 36.25% 32.38% Misd/Petty Misd: 74% All Felony Categories: 17% Misd/Petty Misd: 19% All Felony Categories: 80% Misd/Petty Misd: 8% All Felony Categories: 92% Notes: Data distributed represent highest charge class of 91.1% of the 1-time arrestee population, with 6,635 records unknown. Data distributed represent highest charge class of 99.97% of the 4-time+ arrestee population, with 8 records unknown. Data distributed represent highest charge class of 100% of the 8-time+ arrestee population.
29 Distribution of Arrests by Crime Category 1-Time Arrestees 4-Time+ Arrestees 8-Time+ Arrestees 30.38% 23.28% 6.87% 29.84% 20.48% 10.73% 30.33% 18.51% 10.85% 17.73% 19.36% 24.06% 27.31% Notes: Data distributed represent 98.2% of total arrests for 1-time arrestees, with 1,331 records unknown. Data distributed represent 98.1% of total arrests for 4-time+ arrestees, with 3,215 records unknown. Data distributed represent 98.5% of total arrests for 8-time+ arrestees, with 1,381 records unknown.
30 Distribution of Arrests by Charge Class 1-Time Arrestees 4-Time+ Arrestees 8-Time+ Arrestees 10.30% 6.57% 7.72% 7.09% 8.46% 4.13% 6.41% 6.61% 31.53% 23.24% 24.54% 20.40% 22.37% 42.91% 26.12% 23.40% Misd/Petty Misd: 74% All Felony Categories: 17% Misd/Petty Misd: 47% All Felony Categories: 34% Misd/Petty Misd: 46% All Felony Categories: 34% Notes: Data distributed represent 91.1% of total arrests for 1-time arrestees, with 6,635 records unknown. Data distributed represent 94.5% of total arrests for 4-time+ arrestees, with 9,209 records unknown. Data distributed represent 95.2% of total arrests for 8-time+ arrestees, with 4,292 records unknown.
31 Today s Key Insights 1. A small number of people are responsible for a large share of total arrests and felony arrests. 2. Those who have a felony arrest in their criminal history are more likely to have longer arrest records. 3. As a person s arrest record lengthens, they are highly likely to pick up a violent crime arrest and a felony-level arrest at some point; however, a large share of their arrests continue to be for lower-level offenses and most are for drug, property, or public order crimes. 4. Arrestees tend to be generalists in nature; they are not likely to specialize in committing one particular type of crime.
32 Cross-Crime Category Behavior: 4-Time+ Arrestees Approximately 23,000 Arrestees Of those arrested for a (COLUMN) crime, how many were also arrested for a (ROW) crime? Crime Category (Arrestee Count) Violent (14,481) Drug (9,425) Property (14,730) DWI (5,209) Public Order (18,657) Violent 5,181 55.0% 8,713 59.2% 3,175 61.0% 11,472 61.5% Drug 5,181 35.8% 6,292 42.7% 1,436 27.6% 7,645 41.0% Property 8,713 60.2% 6,292 66.8% 2,439 46.8% 11,974 64.2% DWI 3,175 21.9% 1,436 15.2% 2,439 16.6% 3,963 21.2% Public Order 11,472 79.2% 7,645 81.1% 11,974 81.3% 3,963 76.1% Parole/Probation 3,803 26.3% 2,962 31.4% 3,974 27.0% 1,044 20.0% 4,765 25.5%
33 Research & Strategic Crime Analysis New Collaborative Crime-Fighting Initiatives Places Crime Concentration in ABQ ALeRT Analysis Led Recidivism Team People Arrestee Characteristics, Behavior CSU Crime Strategies Unit Perceptions Resident Insights SCAN Security Camera Analytical Network
34 ALeRT Analysis Led Recidivism Team
35 Analysis Led Recidivism Team (ALeRT) 147 serious repeat felony offenders identified since launch Collective felony conviction rate of 17.7% on the arrests of these offenders over the past 3 years APD BCSD FBI D.A. 50 ALeRT offenders arrested since launch APD BCSO FBI 21 ALeRT offenders sentenced since launch More information being provided to judges about offender history D.A. pushing for strict conditions of release or pre-trial detention, when appropriate D.A. DETAINED: Ruben Gamboa (Pinon), 8 felony arrests 2014- present (auto theft, agg assault on a peace officer, shooting from a vehicle) DETAINED: Michael Lozano, 5 felony arrests 2014-present (kidnapping, auto theft, agg battery against a household member) 1. Identify Repeat Offenders 2. Track through Justice System 3. Notify D.A. upon Arrest 4. Apprehend when Necessary 5. Aggressively Prosecute
36 Sentenced ALeRT Offenders 4.5 Years Tyler Shumake 3 Felony Arrests 3 Years Alfonso Rodriguez 3 Felony Arrests 1.5 Years Alan Shendo 11 Felony Arrests 3.5 Years Jacob Anthony Chavez 10 Felony Arrests 11 Years Dominic Pack 7 Felony Arrests 4 Years Simon Gonzales 10 Felony Arrests 7.5 Years Joseph Hirschfeild 11 Felony Arrests 2.5 Years Monica Garcia 5 Felony Arrests 364 Days Robert Springer 6 Felony Arrests 11.5 Years Ruben Gamboa (Pinon) 8 Felony Arrests 5 Years James Dotts 4 Felony Arrests 152 Days Sabrina Allsup 8 Felony Arrests 90 Days Aaron Brown 3 Felony Arrests 12 Years Jake Loughborough 5 Felony Arrests 2 Years William Shimer 8 Felony Arrests 3 Years April Trujillo 11 Felony Arrests 3 Years Andrew Lucero 9 Felony Arrests 13.5 Years Adrian Pacheco 5 Felony Arrests 7 Years Morris Mora 9 Felony Arrests 957 Days Lucky Crowder 4 Felony Arrests 4 Years Miranda Gilbert 6 Felony Arrests Source: APD Real Time Crime Center
37 CSU Crime Strategies Unit
38 Crime Strategies Unit (CSU) San Francisco Delegation Visit: In July, a 25-person delegation of law enforcement, government, and business leaders traveled to San Francisco for a series of meetings with the San Francisco District Attorney s Office to explore various data practices, analytical tools, and new technologies to more intelligently and efficiently fight crime Crime Strategies Unit (CSU): A division of the San Francisco District Attorney s Office where analysts, investigators, and prosecutors work together to identify crime drivers, better connect crimes and criminals to one another, and deploy high-tech tools to more efficiently investigate and build the types of cases necessary to bring down crime rates In my 30 years in law enforcement and prosecution, I have never seen a delegation as broad as this come together, get on a plane and fly to another city, to learn and improve. It s impressive. -- San Francisco D.A. George Gascón
39 How a CSU Can Improve Criminal Justice TODAY Arrested for Commercial Burglary Arrested for Residential Burglary 2 Previous Misdemeanor Convictions A B 2 Previous Misdemeanor Convictions No Prior Felony Arrests or Convictions 1 Prior Felony Arrest, No Convictions PROSECUTED SIMILARLY Line Prosecutor, Work w/ Facts of Case as Presented, Work Toward Plea SIMILAR OUTCOME/SENTENCE Guilty Plea, 1-Year Probation
40 How a CSU Can Improve Criminal Justice Part of Crime Ring of Commercial Burglars TOMORROW Solo Operator Personally Connected to 10 Other Unsolved Crimes A B No Apparent Connection to Other Unsolved Crimes Items Stolen in Burglaries Sold to Kingpin who Ships Stolen Goods Steals to Buy Drugs PROSECUTED DIFFERENTLY CSU Assignment, Team of Prosecutors/Staff (Person A) Vs. Candidate for Diversion? (Person B) DIFFERENT OUTCOME/SENTENCE Numerous Convictions, Multiple Counts, Significant Jail Time (Person A) Vs. Diversion Program w/ Conditions (Person B)
41 SCAN Security Camera Analytical Network
42 Security Camera Analytical Network (SCAN) Sign up at: www.cabq.gov/scan Business Enrollment: Collaboration between: City of ABQ, D.A. s Office, APD, and BCSD (developed by the Real Time Crime Center and the ABQ i-team) Online mapping APD tool for law enforcement FBI that plots the location and details of residential and business security cameras Makes video evidence of crimes more accessible, will reduce the time it takes law enforcement to locate cameras and determine whether video footage is helpful to an investigation D.A. Businesses BCSO can also sign up to allow camera feeds to be remotely accessed by the Real Time Crime Center Participation is voluntary; success depends upon residents and businesses choosing to be a partner in fighting crime New marketing partnership with Greater Albuquerque Chamber of Commerce to drive recruitment
43 Thank You www.abqi-team.com