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TwitterNumber, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.
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TwitterGapMaps provides Crime Risk data sourced from Applied Geographic Solutions (AGS) which has been used by thousands of companies for over 20 years, providing valuable comparative information on the spatial patterns of crime.
Crime Risk Data includes crime risk indexes and projections on detailed crime types like murder and motor vehicle theft, and summary indexes of crimes against persons, crimes against property and overall crime risk. Crime Risk Data is available at the highly detailed census block level to capture the different risk levels across business and residential places. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide.
The crimes included in the Crime Risk Data database are the “Part 1” crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative “overall” crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. In 2020, 5-Year Projections were added to the database.
Use cases: 1. Insurance underwriting and risk mitigation. 2. Evaluating the security measures needed to protect employees and customers at retail facilities. 3. The study of the effects of neighborhood crime on wellness and health care outcomes.
Methodology: Crime is tracked for multiple years using both FBI aggregate crime reports and for many parts of the country at the individual incident level. A complex set of statistical models are used to estimate and forecast risk of each individual crime type by using land use data in conjunction with demographic and business characteristics.
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TwitterGapMaps offers an advanced and reliable Crime Risk dataset sourced from Applied Geographic Solutions (AGS), a trusted provider of premium demographic insights with over 20 years of experience. Leveraged by thousands of businesses, AGS use advanced statistical methodologies and a rolling seven-year database of FBI and local agency statistics to provide a highly accurate view of the relative risk of specific crime types for any geographic area empowering organizations to make informed decisions in areas such as insurance, urban planning, and real estate.
The AGS Crime Risk dataset includes: - Standardised indexes for a range of serious crimes against both persons and property such as murder, rape, robbery, assault, burglary, theft, and motor vehicle theft - Aggregate measures of crime risk, including crimes against persons, crimes against property, and overall crime risk, offering a comprehensive overview of an area’s safety. - 5-Year Projections: Added in 2020, these projections enhance the dataset by forecasting future crime risks, providing valuable insights for long-term planning. - High-Resolution Data: Crime risk indexes are available at the block group level, allowing insurers to identify variations in crime risk across specific land uses such as motor vehicle theft from parking structures.
Use cases for Crime Risk data in Insurance include: 1) Help determine the likelihood of policyholders filing claims. This information allows them to price policies appropriately. Higher crime risk areas typically result in higher premiums to account for the increased likelihood of claims. 2) Provide recommendations for loss prevention measures based on crime risk assessments. This could include installing security systems, using better lighting, or employing security personnel. Effective loss prevention can reduce the frequency and severity of claims. 3) Insurance underwriters can establish sufficient premiums to cover potential claims. Misjudging crime risk could lead to financial losses if claims exceed the collected premiums. This stability is essential for the insurer's long-term viability. 4) Offer competitive premiums while maintaining profitability. This can attract more customers and increase market share.
Methodology: The primary source of CrimeRisk is a careful compilation and analysis of the FBI Uniform Crime Report databases. On an annual basis, the FBI collects data from each of about 16,000 separate law enforcement jurisdictions at the city, county, and state levels and compiles these into its annual Uniform Crime Report (UCR). While useful, the UCR provides detailed data only for the largest cities, counties, and metropolitan areas. A complex set of statistical models are used to estimate and forecast risk of each individual crime type by using land use data in conjunction with demographic and business characteristics.
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TwitterNumber of homicide victims, by method used to commit the homicide (total methods used; shooting; stabbing; beating; strangulation; fire (burns or suffocation); other methods used; methods used unknown), Canada, 1974 to 2024.
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TwitterVictims of gang-related homicides (total number of homicide victims; number of homicide victims - unknown gang-relation; number of homicide victims - known gang relation; number of gang-related homicide victims; percentage of gang-related homicide victims; rate (per 100,000 population) of gang-related homicide victims), Canada and regions, 1999 to 2024.
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TwitterNumber, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.