Introduction

Shoplifting Statistics: The year 2024 has remained crucial for all retail businesses, and shoplifting poses one of the major challenges for retailers all over the world. Entrepreneurs grip the handles of economic pressure to retard or restrict retail trade, and organized retail crime has just added insult to injury with vandalism and theft in various techniques.

This legal exploration will present recent shoplifting statistics in various key markets around the world.

There were approximately 530,640 shoplifting offences recorded by the police in England and Wales in 2024/25, the highest in this provided time period. Although the annual number of shoplifting offences remained quite stable before the COVID-19 pandemic, there was a slight trend of rising offences that reached a pre-pandemic peak of around 382,660 in 2017/18. The 2020/21 and 2021/20 reporting years are not directly comparable to the other reporting years due to COVID-19 lockdowns that occurred at that time. Areas with the highest shoplifting rate As of 2023/24, the shoplifting rate for England and Wales as a whole was 7.4 shoplifting offences per 1,000 population. Looking at individual police force areas, the area covered by Nottinghamshire Police Force, in the English East Midlands, had the highest shoplifting rate of 13.2, followed by Cleveland, in North East England, at 13.1. By contrast, the Dyfed-Powys Police Force Area, in Wales had the lowest shoplifting rate of just 3.9 offences per 1,000 population. Although Cleveland also had the highest overall crime rate in England and Wales, and Dyfed-Powys had one of the lowest, Nottinghamshire's crime rate was slightly below the overall average, despite having such a high shoplifting rate. Comparisons with other theft offences Shoplifting is one of the major sub-categories of theft in the jurisdiction of England and Wales. Although shoplifting offences have increased significantly recently, the number of theft offences overall has generally been falling. In 2002/03 for example, there were approximately 3.41 million incidences of theft, compared with just 1.78 million in 2023/24. This trend has been driven by declines in other types of theft, such as burglary, which fell from over 890,000 offences in 2002/03, to around 266,500 in 2023/24.

The number of shoplifting cases registered by the German police has fluctuated in the last decade, though the figures displayed in this graph show a decrease since 2015. In 2023, around 426,096 cases of shoplifting were recorded by police in Germany, a rather large increase compared to the previous year. Mind the shop Shoplifting is damaging to any business. There are measures that can be taken in order to minimize shoplifting, such as video surveillance, tagging items, as well as hiring security personnel that are visibly present to customers in some shops. The reality is, however, that among theft crimes, shoplifting is the most common, so even with security measures implemented, it is difficult for stores to completely avoid being targeted. Falling crime rate Recent statistics show that the crime rate in Germany (estimated per 100,000 people) was falling considerably. However, since the pandemic the rate of crime in Germany has risen. Police have also recorded more crime offences since 2021.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

***Starting on March 7th, 2024, the Los Angeles Police Department (LAPD) will adopt a new Records Management System for reporting crimes and arrests. This new system is being implemented to comply with the FBI's mandate to collect NIBRS-only data (NIBRS — FBI - https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs). During this transition, users will temporarily see only incidents reported in the retiring system. However, the LAPD is actively working on generating new NIBRS datasets to ensure a smoother and more efficient reporting system. ***

******Update 1/18/2024 - LAPD is facing issues with posting the Crime data, but we are taking immediate action to resolve the problem. We understand the importance of providing reliable and up-to-date information and are committed to delivering it.

As we work through the issues, we have temporarily reduced our updates from weekly to bi-weekly to ensure that we provide accurate information. Our team is actively working to identify and resolve these issues promptly.

We apologize for any inconvenience this may cause and appreciate your understanding. Rest assured, we are doing everything we can to fix the problem and get back to providing weekly updates as soon as possible. ******

This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.

Suburb-based crime statistics for crimes against the person and crimes against property. The Crime statistics datasets contain all offences against the person and property that were reported to police in that respective financial year. The Family and Domestic Abuse-related offences datasets are a subset of this, in that a separate file is presented for these offences that were flagged as being of a family and domestic abuse nature for that financial year. Consequently the two files for the same financial year must not be added together.

In 2022, retailers in California lost over ************************ U.S. dollars' worth of revenue to retail theft, making it the state most impacted by the crime. This is, however, more of a reflection of the population: the states with the highest resident population generally recorded the largest retail theft losses.

In 2023/24, the shoplifting rate in England and Wales was 7.4 shoplifting offences per 1,000 population. Among Police Force areas, Nottinghamshire, located in the English East Midlands, had the highest shoplifting rate of 13.2, followed by Cleveland in North East England, at 13.1.

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).

This collection contains electronic versions of the Uniform Crime Reports publications for the early years of the Uniform Crime Reporting Program in the United States. The reports, which were published monthly from 1930 to 1931, quarterly from 1932 to 1940, and annually from 1941 to 1959, consist of tables showing the number of offenses known to the police as reported to the Federal Bureau of Investigation by contributing police departments. The term "offenses known to the police" includes those crimes designated as Part I classes of the Uniform Classification code occurring within the police jurisdiction, whether they became known to the police through reports of police officers, citizens, prosecuting or court officials, or otherwise. They were confined to the following group of seven classes of grave offenses, historically those offenses most often and most completely reported to the police: felonious homicide, including murder and nonnegligent manslaughter, and manslaughter by negligence, rape, robbery, aggravated assault, burglary -- breaking and entering, and larceny -- theft (including thefts $50 and over, and thefts under $50, and auto theft). The figures also included the number of attempted crimes in the designated classes excepting attempted murders classed as aggravated assaults. In other words, an attempted burglary or robbery, for example, was reported in the same manner as if the crimes had been completed. "Offenses known to the police" included, therefore, all of the above offenses, including attempts, which were reported by the police departments and not merely arrests or cleared cases.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) for all complete quarters so far this year (2017). For additional details, please see the attached data dictionary in the ‘About’ section.

Statistical breakdown by citywide, borough, and precinct.

Introduction

Crime Statistics: Crime affects how we live, where we go, and how safe we feel every day. The latest numbers from 2025 reveal significant shifts in the types of crimes occurring and their geographical distribution. As towns and cities grow and new technologies are introduced, it's essential for everyone—from parents and students to business owners and local leaders—to understand what is happening.

This Crime Statistics will break down the newest US crime data, including violent crimes, property crimes, where crime is rising or falling, how police are responding, and which groups are most at risk. These facts and figures aren't just stats—they show what's happening in real communities and help us make better choices for a safer future.

A CSV file which is updated daily by 11am and includes crime incidents from November 1st, 2015 forward through 7 days prior to today's posting date. Homicides, rapes, robberies, aggravated assaults, burglaries, thefts, motor vehicle thefts, arsons, and drug offenses are included (based on the primary offense listed for each incident).

Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. 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 database are the "Part I" 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. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. 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. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

Crime isn't a topic most people want to use mental energy to think about. We want to avoid harm, protect our loved ones, and hold on to what we claim is ours. So how do we remain vigilant without digging too deep into the filth that is crime? Data, of course. The focus of our study is to explore possible trends between crime and communities in the city of Calgary. Our purpose is visualize Calgary criminal behaviour in order to help increase awareness for both citizens and law enforcement. Through the use of our visuals, individuals can make more informed decisions to improve the overall safety of their lives. Some of the main concerns of the study include: how crime rates increase with population, which areas in Calgary have the most crime, and if crime adheres to time-sensative patterns.

In 2023, about ** percent of surveyed retail brands in the United States said their employees were not authorized to stop or apprehend shoplifters in their stores. Just under ** percent of brands surveyed said they had loss prevention and asset protection personnel for such scenarios.

Provide robbery, snatch, forcible intercourse, car theft, residential theft, drugs, motorcycle theft and 7 other types of cases, weekly statistics on occurrences, clearance, and clearance rate. (This data is a preliminary statistics change file for each week, for reference only, and the correct statistics are still based on the annual criminal statistics of this department.) Case type, number of occurrences, number of clearances, clearance rate

Crime data from years prior to the current one. The data included in this dataset has been reviewed and approved by a Milwaukee Police Department supervisor and the Milwaukee Police Department’s Records Management Division. This approval process can take a few weeks from the reported date of the crime. For preliminary crime data, please visit the Milwaukee Police Department’s Crime Maps and Statistics dashboard at https://city.milwaukee.gov/police/Information-Services/Crime-Maps-and-Statistics.

Wisconsin Incident Based Report (WIBR) Group A Offenses.

The Crime Data represents incident level data defined by Wisconsin Incident Based Reporting System (WIBRS) codes. WIBRS reporting is a crime reporting standard and can not be compared to any previous UCR report. Therefore, the Crime Data may reflect:

• Information not yet verified by further investigation
• Preliminary crime classifications that may be changed at a later date based upon further investigation
• Information that may include mechanical or human error

Neither the City of Milwaukee nor the Milwaukee Police Department guarantee (either express or implied) the accuracy, completeness, timeliness, or correct sequencing of the Crime Data. The City of Milwaukee and the Milwaukee Police Department shall have no liability for any error or omission, or for the use of, or the results obtained from the use of the Crime Data. In addition, the City of Milwaukee and the Milwaukee Police Department caution against using the Crime Data to make decisions/comparisons regarding the safety of or the amount of crime occurring in a particular area. When reviewing the Crime Data, the site user should consider that:

• The information represents only police services where a report was made and does not include other calls for police service
• The information does not reflect or certify "safe" or "unsafe" areas
• The information will sometimes reflect where the crime was reported versus where the crime occurred

The use of the Crime Data indicates the site user's unconditional acceptance of all risks associated with the use of the Crime Data.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page. XY fields in data is in projection Wisconsin State Plane South NAD27 (WKID 32054).