100+ datasets found
  1. c

    Housing Landlord-Tenant Disputes

    • s.cnmilf.com
    • data.montgomerycountymd.gov
    • +1more
    Updated Oct 4, 2025
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    data.montgomerycountymd.gov (2025). Housing Landlord-Tenant Disputes [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/housing-landlord-tenant-disputes
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    Dataset updated
    Oct 4, 2025
    Dataset provided by
    data.montgomerycountymd.gov
    Description

    The Housing Landlord-Tenant Case Tracking dataset includes tracking information, complaints and individual case dispositions. The data is updated monthly.

  2. O

    Landlord Permits

    • data.cityofgainesville.org
    • data.wu.ac.at
    Updated May 20, 2021
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    (2021). Landlord Permits [Dataset]. https://data.cityofgainesville.org/Business-Economy/Landlord-Permits/x3sz-gqmp
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    csv, xlsx, application/geo+json, kml, xml, kmzAvailable download formats
    Dataset updated
    May 20, 2021
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Permits paid by and issued to single family residential property owners who do not have homestead exemption.

  3. d

    Landlord/Tenant Monthly Caseload CY 2023-2025

    • catalog.data.gov
    • data.texas.gov
    • +1more
    Updated Oct 25, 2025
    + more versions
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    data.austintexas.gov (2025). Landlord/Tenant Monthly Caseload CY 2023-2025 [Dataset]. https://catalog.data.gov/dataset/landlord-tenant-monthly-caseload-cy-2023
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    Dataset updated
    Oct 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    The dataset contains monthly Landlord/Tenant caseload information by court from January 2023- Present. Landlord/Tenant cases include: 1) Eviction- All suits for eviction (recovery of possession of premises) brought to recover possession of real property under Chapter 24 of the Texas Property Code, often by a landlord against a tenant. A claim for rent may be joined with an eviction case if the amount of rent due and unpaid is not more than $20,000, excluding statutory interest and court costs but including attorney fees, if any. Eviction cases filed on or after September 1, 2023, are governed by Rules 500-507 and 510 for Part V of the Rules of Civil Procedure. 2) Repair and Remedy- A case by a residential tenant under Chapter 92, Subchapter B, of the Texas Property Code to enforce the landlord’s duty to repair or remedy a condition materially affecting the physical health or safety of an ordinary tenant. Repair and remedy cases filed on or after September 1, 2013, are governed by Rules 500-507 and 509 of Part V of the Rules of Civil Procedure. Because of the submission deadlines for reports, the most recent monthly data will be two months behind.

  4. d

    Replication Data for \"Do Wall Street Landlords Undermine Renters'...

    • dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Umit Gurun; Jiabin Wu; Steven Xiao; Serena Xiao (2023). Replication Data for \"Do Wall Street Landlords Undermine Renters' Welfare?\" [Dataset]. http://doi.org/10.7910/DVN/HCWJRW
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Umit Gurun; Jiabin Wu; Steven Xiao; Serena Xiao
    Description

    This packet provides the data and code that replicate the empirical results in Gurun, Wu, Xiao, and Xiao (2022). - All data are original except for the job post data which require a data use license for Burning Glass. In the file merger_securityguard.dta, data on the number of job posts for security guards (gr1) are replaced with pseudo data. - Simply running execute.do in Stata (except changing the local directories) will generate all the tables and figures in the paper. - table_program_list.xlsx shows the names of input dataset, do file, and output file for each table and figure in the paper;

  5. Private Landlord Survey - Dataset - data.gov.uk

    • ckan.publishing.service.gov.uk
    Updated Dec 11, 2011
    + more versions
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    ckan.publishing.service.gov.uk (2011). Private Landlord Survey - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/private_landlord_survey
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    Dataset updated
    Dec 11, 2011
    Dataset provided by
    CKANhttps://ckan.org/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    The 2010 Private Landlord Survey is a national survey of landlords and managing agents who own and/or manage privately rented properties in England. The aim of the survey is to provide a snap-shot of the composition and experience of landlords and how they (together with any agent) acquire, let, manage and maintain privately rented accommodation. Source agency: Communities and Local Government Designation: Official Statistics not designated as National Statistics Language: English Alternative title: English Housing Survey Private Landlord Survey

  6. Registered Social Landlords Average Rents - Dataset - data.gov.uk

    • ckan.publishing.service.gov.uk
    Updated Jun 9, 2025
    + more versions
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    ckan.publishing.service.gov.uk (2025). Registered Social Landlords Average Rents - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/registered-social-landlords-average-rents
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    Dataset updated
    Jun 9, 2025
    Dataset provided by
    CKANhttps://ckan.org/
    Description

    Amount charged by Registered Social Landlord (Private Registered Provider (PRP)) Average Weekly Rents for social housing. Data is collected by the Housing Corporation via the annual Regulatory and Statistical Return (RSR) based on general needs stock only. Figures are based on only the larger Registered Social Landlords (RSLs) completing the long form. Upto 2006 the threshold for completing the long form was that the RSL owned/ managed at least 250 units/bedspaces. From 2007 this increased to 1,000 units/bedspaces. The districts, unitary authorities and counties listed above are based on 1 April 1998 boundaries. Figures for any 'new' re-organised areas have been estimated retrospectively applying the new boundaries back to 1997 and making appropriate assumptions. Note that the average RSL rents within a local authority area can move down from one year to the next. This is especially true if, during the latest year, most of the LA stock has been transferred through a large-scale voluntary transfer to the RSL sector. Larger housing associations report the rent they charge in the HCA’s Statistical Data Return. Data in spreadsheet includes average weekly rents for housing association general needs properties by number of bedrooms, in London by borough (stock owned by larger associations only).

  7. D

    Rental Payment Data Reporting Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 30, 2025
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    Dataintelo (2025). Rental Payment Data Reporting Market Research Report 2033 [Dataset]. https://dataintelo.com/report/rental-payment-data-reporting-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Rental Payment Data Reporting Market Outlook



    According to our latest research, the global rental payment data reporting market size stood at USD 1.46 billion in 2024, with a robust compound annual growth rate (CAGR) of 13.2% projected through the forecast period. This sustained growth trajectory is expected to propel the market to reach USD 4.04 billion by 2033. The market's expansion is primarily driven by the rising demand for enhanced tenant transparency, increased adoption of digital payment solutions, and the growing importance of rental data in credit scoring models. As the global rental ecosystem becomes increasingly digitized and regulated, the integration of payment data reporting solutions is becoming indispensable for property managers, landlords, financial institutions, and tenants alike.




    A key growth factor for the rental payment data reporting market is the rising emphasis on financial inclusion and credit accessibility for renters. Traditionally, rental payments have not been systematically reported to credit bureaus, thereby excluding a significant segment of the population from building a positive credit history. However, the emergence of sophisticated rental payment data reporting platforms is transforming this scenario by enabling tenants to leverage timely rent payments to boost their credit scores. This shift is not only empowering tenants but is also attracting the attention of financial institutions seeking more comprehensive risk assessment tools. As a result, the integration of rental data into mainstream credit reporting is rapidly gaining momentum, further fueling market growth.




    Technological advancements are playing a pivotal role in shaping the rental payment data reporting market. The proliferation of cloud-based solutions, artificial intelligence, and machine learning is enabling the automation and accuracy of data collection, reporting, and analysis. These technologies facilitate seamless integration with property management systems, enhance data security, and provide actionable insights for both landlords and tenants. Additionally, regulatory changes in several countries are mandating greater transparency in rental transactions, which is compelling property managers and landlords to adopt compliant data reporting solutions. The convergence of regulatory requirements and technological innovation is thus accelerating the adoption of rental payment data reporting platforms across diverse end-user segments.




    Another significant driver is the increasing professionalization of the property management sector. As institutional investors and large-scale property managers expand their portfolios, there is a growing need for standardized, scalable, and compliant rental payment data reporting tools. These solutions are critical for streamlining rent collection, conducting tenant screening, and maintaining regulatory compliance across multiple jurisdictions. Furthermore, the competitive landscape is witnessing the entry of fintech startups and established software vendors, both of whom are introducing innovative features such as real-time payment tracking, automated reminders, and advanced analytics. This competitive dynamism is fostering continuous product innovation, ultimately benefiting end-users and propelling market growth.




    From a regional perspective, North America continues to lead the rental payment data reporting market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The dominance of North America can be attributed to the high penetration of digital payment platforms, favorable regulatory frameworks, and a mature property management industry. Meanwhile, Asia Pacific is witnessing the fastest growth, driven by rapid urbanization, increasing rental housing demand, and the proliferation of digital financial services. Europe is also experiencing steady growth, supported by regulatory harmonization and rising awareness among property owners and tenants. Other regions such as Latin America and the Middle East & Africa are gradually catching up, owing to increasing investments in real estate technology and financial inclusion initiatives.



    Component Analysis



    The rental payment data reporting market is segmented by component into software and services, each playing a distinct role in the ecosystem. Software solutions are at the heart of this market, providing the digital infrastructure necessary for the automated collection, pr

  8. c

    Global Landlord Insurance Market Report 2025 Edition, Market Size, Share,...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Jul 26, 2025
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    Cognitive Market Research (2025). Global Landlord Insurance Market Report 2025 Edition, Market Size, Share, CAGR, Forecast, Revenue [Dataset]. https://www.cognitivemarketresearch.com/landlord-insurance-market-report
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    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jul 26, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    As per Cognitive Market Research's latest published report,The Europe Landlord Insurance market size will be $27,770.62 Million by 2028.The Europe Landlord Insurance Industry's Compound Annual Growth Rate will be 7.94% from 2023 to 2030. What is Driving Landlord Insurance Industry Growth?

    Rising demand of rental properties
    

    It is said that the best investment is a land investment. Population across the globe follows these proverbs and invest their saving in buying homes. The housing process in European countries were observed at its peak which were derived by the large investors. The institutional investors including private equity and pension funds has raise the houses prices in the European countries. The volume of purchases in Europe hit €64bn (£53bn) in 2020, with about €150bn value of housing stock conservatively estimated to be in the hands of such large investors. According to Preqin private database of investors, Berlin, with €40bn worth of housing assets in institutional portfolios is at top followed by London, Amsterdam, Paris and Vienna.

    The data from Berlin’s Free University states that the Europe’s housing has become increasingly attractive asset class for investors owing to near-zero interest rates and cheering regulatory outlines. The data from European central bank shows that the real estate funds in the Eurozone reached €1tn in 2021 in which residential assets are consider as progressively central part. The institutional investors’ residential transactions between 2012 and 2021 was increased in Germany, Denmark followed by Netherlands.

    Significant occupancy of residential and commercial properties by institutional investors led to the undersupply of housing across the continent and results in the increasing rental rates. Owing to the chronic undersupply of housing in several European countries, the population of the tenants increases which simultaneously increases the demand of rental properties in Europe. Moreover, the capability of population to purchase house is also decreasing with the increasing annual house prices. The data shows a surge in rents by 16.0 % and house prices by 38.7 % from 2010 to third quarter of 2021 in Europe. The rent and houses price in Europe has increased by 1.2 % and 9.2 % respectively from third quarter of 2021 to third quarter of 2020.

    Landlord insurance is applicable to rental properties only. Hence, with the increasing demand of rental properties in Europe is driving the growth of landlord insurance market.

    Increase in natural disasters is propelling market growth
    

    Restraint of the Europe Landlord Insurance Market

    Inadequate information related to landlord insurance policies.(Access Detailed Analysis in the Full Report Version)
    

    Opportunities of the Europe Landlord Insurance Market

    Introduction of new technologies in insurance industry.(Access Detailed Analysis in the Full Report Version)
    

    What is Landlord Insurance?

    Landlord Insurance is a sort of homeowner's insurance that protects homeowners against financial losses associated with rental properties. This insurance includes coverage for fire and other dangers, as well as theft and intentional damage.

    Several European nations are quickly implementing landlord insurance for their buildings. Property and liability protection are two forms of coverage that are commonly included in insurance policies. Both insurance policies are designed to protect both the landlord and the renters from financial losses.

    Damage to property, income replacement, liability insurance, and add-on coverage are all covered by landlord insurance. It assists clients in protecting themselves from financial losses caused by natural catastrophes, injuries, accidents, and other liability concerns.

    It also provides payment for lost rent, repairs, and property replacement that are covered by landlord insurance.

    Landlord liability insurance, landlord buildings insurance, landlord contents insurance, loss of rent insurance, tenant default insurance, accidental damage insurance, alternative accommodation insurance, unoccupied property insurance, and legal expenses insurance are among the various types of landlord insurance.

    In Europe, several online and offline landlord insurance businesses offer solutions for both residential and commercial properties. This landlord insurance migh...

  9. T

    United States - Rental income of persons with capital consumption...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Aug 1, 2019
    + more versions
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    TRADING ECONOMICS (2019). United States - Rental income of persons with capital consumption adjustment: Private business: Tenant-occupied housing: Farm tenant-occupied housing owned by farm operator landlords [Dataset]. https://tradingeconomics.com/united-states/rental-income-of-persons-with-capital-consumption-adjustment-private-business-tenant-occupied-housing-farm-tenant-occupied-housing-owned-by-farm-operator-landlords-fed-data.html
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Aug 1, 2019
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Rental income of persons with capital consumption adjustment: Private business: Tenant-occupied housing: Farm tenant-occupied housing owned by farm operator landlords was -0.97100 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Rental income of persons with capital consumption adjustment: Private business: Tenant-occupied housing: Farm tenant-occupied housing owned by farm operator landlords reached a record high of 5.70500 in January of 1997 and a record low of -1.30900 in January of 2018. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Rental income of persons with capital consumption adjustment: Private business: Tenant-occupied housing: Farm tenant-occupied housing owned by farm operator landlords - last updated from the United States Federal Reserve on October of 2025.

  10. Real rent increase dwellings; social and other landlords

    • cbs.nl
    • ckan.mobidatalab.eu
    • +2more
    xml
    Updated Sep 5, 2025
    + more versions
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    Centraal Bureau voor de Statistiek (2025). Real rent increase dwellings; social and other landlords [Dataset]. https://www.cbs.nl/en-gb/figures/detail/84822ENG
    Explore at:
    xmlAvailable download formats
    Dataset updated
    Sep 5, 2025
    Dataset provided by
    Statistics Netherlands
    Authors
    Centraal Bureau voor de Statistiek
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2015 - 2025
    Area covered
    The Netherlands
    Description

    This table includes figures on the average increase of rent paid for regulated dwellings broken down by type of landlord. The figures have been adjusted for inflation, using the average inflation for the period December to November of the previous year.

    Data available from: 2015.

    Status of the figures: The figures in this table are definitive.

    Changes as of 5 September 2025: The figures of 2025 have been published.

    When will new figures be published? New figures will become available in September 2026.

  11. Global Tenant Screening Services Market Size By Service Type, By Deployment...

    • verifiedmarketresearch.com
    Updated Oct 21, 2024
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    VERIFIED MARKET RESEARCH (2024). Global Tenant Screening Services Market Size By Service Type, By Deployment Type, By End-user, By Geographic Scope And Forecast [Dataset]. https://www.verifiedmarketresearch.com/product/tenant-screening-services-market/
    Explore at:
    Dataset updated
    Oct 21, 2024
    Dataset provided by
    Verified Market Researchhttps://www.verifiedmarketresearch.com/
    Authors
    VERIFIED MARKET RESEARCH
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Time period covered
    2024 - 2031
    Area covered
    Global
    Description

    Tenant Screening Services Market size was valued at USD 1.5 Billion in 2023 and is projected to reach USD 2.7 Billion by 2031, growing at a CAGR of 9.3% during the forecasted period 2024 to 2031.

    Global Tenant Screening Services Market Drivers

    The market drivers for the Tenant Screening Services Market can be influenced by various factors. These may include:

    Increasing Rental Demand: As more people choose to rent rather than buy homes, the demand for tenant screening services has risen, helping landlords find reliable tenants.

    Regulatory Compliance: Landlords are required to adhere to fair housing laws and regulations. Tenant screening services help ensure compliance, reducing legal risks.

    Technological Advancements: Innovations in data analytics, artificial intelligence, and online platforms have made tenant screening faster and more efficient, attracting more landlords to utilize these services.

  12. w

    Problem Landlord List

    • data.wu.ac.at
    application/excel +5
    Updated Jul 17, 2018
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    cocadmin (2018). Problem Landlord List [Dataset]. https://data.wu.ac.at/odso/data_cityofchicago_org/bjV6ai1yNDR1
    Explore at:
    xml, json, application/xml+rdf, xlsx, application/excel, csvAvailable download formats
    Dataset updated
    Jul 17, 2018
    Dataset provided by
    cocadmin
    Description

    This list describes landlords and property owners who are designated "problem landlords". Landlords on this list have had two or more administrative hearing causes brought against them and were found liable or defaulted to one or more serious building violations.

  13. D

    Rental History Verification Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Oct 1, 2025
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    Dataintelo (2025). Rental History Verification Market Research Report 2033 [Dataset]. https://dataintelo.com/report/rental-history-verification-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Rental History Verification Market Outlook



    According to our latest research, the global rental history verification market size in 2024 stands at USD 2.16 billion, with an observed compound annual growth rate (CAGR) of 8.5% from 2025 to 2033. The market is projected to reach USD 4.42 billion by 2033, driven by the growing demand for efficient tenant screening solutions and the increasing digitization of property management processes. This robust expansion is underpinned by technological advancements in verification software and heightened regulatory compliance requirements across various regions, highlighting the market’s critical role in the evolving real estate ecosystem.




    One of the primary growth factors for the rental history verification market is the rising incidence of rental fraud and the escalating need for reliable tenant screening mechanisms. As urbanization accelerates and the rental housing sector expands, property owners and managers face mounting challenges in verifying prospective tenants’ backgrounds. The proliferation of digital platforms for property rentals has made it easier for individuals to falsify information, increasing the risk of financial and reputational losses for landlords and property managers. Consequently, there is a surging demand for comprehensive, automated rental history verification solutions that provide accurate, real-time insights into tenant backgrounds, creditworthiness, and rental payment histories. This trend is further reinforced by heightened awareness among landlords and real estate agencies regarding the importance of minimizing risk and ensuring compliance with fair housing regulations.




    Another significant driver is the integration of advanced technologies such as artificial intelligence, machine learning, and big data analytics into rental history verification platforms. These innovations enable the automation of complex verification processes, reducing manual intervention, and enhancing the accuracy and speed of background checks. AI-powered solutions can quickly analyze vast datasets, identify patterns, and flag potential risks, thereby streamlining the tenant screening process for property managers and landlords. Moreover, the adoption of cloud-based verification services allows for seamless data sharing, scalability, and remote access, which is particularly beneficial in the post-pandemic era where digital transformation and remote property management have become the norm. The convergence of these technological advancements is expected to sustain the market’s growth momentum over the forecast period.




    Additionally, regulatory developments and the increasing emphasis on data privacy and security are shaping the rental history verification landscape. Governments across North America, Europe, and Asia Pacific are enacting stringent regulations to protect tenant rights and ensure the ethical use of personal data during the verification process. Compliance with these regulations necessitates the implementation of secure, transparent, and auditable verification systems, which is driving investments in state-of-the-art software and services. Furthermore, the growing trend of institutional investment in rental properties and the professionalization of property management are fostering the adoption of standardized verification practices, thereby fueling the market’s expansion. As the rental market continues to globalize, cross-border verification solutions are also gaining traction, further broadening the market’s scope.




    From a regional perspective, North America remains the largest market for rental history verification, accounting for over 38% of the global revenue in 2024. This dominance is attributed to the region’s mature real estate sector, high adoption of digital property management solutions, and stringent regulatory frameworks governing tenant screening. Europe follows closely, driven by a burgeoning rental market and increasing regulatory harmonization across member states. The Asia Pacific region is witnessing the fastest growth, with a CAGR of 10.2%, fueled by rapid urbanization, a growing middle-class population, and the digital transformation of real estate services. Latin America and the Middle East & Africa are also emerging as promising markets, supported by rising investments in smart property management infrastructure and the growing need for secure tenant verification solutions.



    Component Analysis

    &l

  14. c

    LANDLORD RONALD Price Prediction Data

    • coinbase.com
    Updated Oct 12, 2025
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    (2025). LANDLORD RONALD Price Prediction Data [Dataset]. https://www.coinbase.com/price-prediction/base-landlord-ronald
    Explore at:
    Dataset updated
    Oct 12, 2025
    Variables measured
    Growth Rate, Predicted Price
    Measurement technique
    User-defined projections based on compound growth. This is not a formal financial forecast.
    Description

    This dataset contains the predicted prices of the asset LANDLORD RONALD over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

  15. e

    Landlord's Electricity Data

    • data.europa.eu
    • data.wu.ac.at
    Updated Sep 27, 2021
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    Environment Agency (2021). Landlord's Electricity Data [Dataset]. https://data.europa.eu/data/datasets/landlords-electricity-data
    Explore at:
    Dataset updated
    Sep 27, 2021
    Dataset authored and provided by
    Environment Agency
    Description

    Legal & Resources - Corporate assets, safety, health and the environment

    Landlord's Electricity Data contains data on electricity meter readings and billings.

  16. G

    Rental History Verification Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 22, 2025
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    Growth Market Reports (2025). Rental History Verification Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/rental-history-verification-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Aug 22, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Rental History Verification Market Outlook




    According to our latest research, the global rental history verification market size in 2024 is valued at USD 2.3 billion, with a robust compound annual growth rate (CAGR) of 8.1% projected from 2025 to 2033. By the end of 2033, the market is forecasted to reach USD 4.6 billion, driven by the increasing demand for reliable tenant screening solutions and the digital transformation of property management processes. This growth is underpinned by stringent regulatory requirements, the rising incidence of rental fraud, and the expanding real estate sector worldwide, positioning rental history verification as a critical component in the property rental ecosystem.




    One of the primary growth drivers for the rental history verification market is the escalating need for secure and trustworthy tenant screening mechanisms. With urbanization accelerating and rental housing becoming a preferred option in many regions, property managers and landlords are seeking advanced solutions to mitigate risks associated with unreliable tenants. The proliferation of fraudulent rental applications and identity theft has heightened the importance of comprehensive background checks, including rental history verification. As a result, both residential and commercial property owners are increasingly adopting automated and integrated verification platforms to ensure tenant reliability, reduce financial losses, and maintain the integrity of their rental portfolios.




    Another significant factor fueling market expansion is the ongoing digitalization of the real estate industry. The integration of advanced technologies such as artificial intelligence, machine learning, and big data analytics into tenant screening solutions has revolutionized the rental history verification process. These innovations enable faster, more accurate, and scalable background checks, thereby streamlining property management operations. Cloud-based deployment models are particularly gaining traction, offering flexibility, cost-effectiveness, and real-time access to verification data. This technological evolution not only enhances operational efficiency for property managers and real estate agencies but also improves the overall rental experience for tenants by accelerating application approvals and minimizing administrative delays.




    The regulatory landscape is also playing a pivotal role in shaping the rental history verification market. Governments and regulatory bodies across regions are implementing stricter tenant screening guidelines to protect both landlords and renters. Compliance with fair housing laws, data privacy regulations, and anti-discrimination statutes necessitates the adoption of standardized and transparent verification processes. This regulatory push is compelling property management firms and real estate agencies to invest in robust verification solutions that ensure legal compliance, reduce liability, and foster trust within the rental ecosystem. Consequently, the market is witnessing increased demand for both software and service-based offerings that cater to diverse regulatory requirements across different geographies.




    From a regional perspective, North America continues to dominate the rental history verification market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The high adoption rate of digital tenant screening solutions, coupled with a mature real estate sector and stringent regulatory frameworks, underpins North America's market leadership. Europe is witnessing steady growth due to rising urbanization and the increasing prevalence of rental housing, while the Asia Pacific region is poised for the fastest CAGR during the forecast period, driven by rapid urban expansion, a burgeoning middle class, and the digitization of property management practices. Latin America and the Middle East & Africa are also emerging as promising markets, supported by growing investments in real estate infrastructure and the gradual shift towards formalized rental processes.





  17. R

    Rental Property Management Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jun 30, 2025
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    Data Insights Market (2025). Rental Property Management Software Report [Dataset]. https://www.datainsightsmarket.com/reports/rental-property-management-software-1448263
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The rental property management software market is experiencing robust growth, driven by the increasing number of rental properties, the need for efficient property management, and the rising adoption of technology in the real estate sector. The market's expansion is fueled by several key trends, including the growing preference for cloud-based solutions offering scalability and accessibility, the integration of advanced features like automated rent collection, tenant communication portals, and maintenance request management, and the increasing demand for data analytics to optimize operational efficiency and profitability. Competition is intensifying among established players like Xotelia, Quicken, and 123Landlord.com, alongside emerging companies such as Rentberry and ADDA.IO, leading to innovative product development and competitive pricing. While the market faces restraints such as the initial investment costs for software adoption and the need for ongoing training and support, the long-term benefits in terms of cost savings, improved operational efficiency, and enhanced tenant satisfaction are driving widespread adoption. Considering a conservative CAGR of 15% (assuming a missing CAGR), and a 2025 market size of $2 billion (estimated based on industry reports and player valuations), the market is projected to significantly expand throughout the forecast period (2025-2033). Regional variations in growth will likely be influenced by factors like market maturity, technological adoption rates, and regulatory frameworks. North America and Europe are expected to hold significant market shares due to high property ownership and technological advancements. The success of rental property management software companies hinges on their ability to offer comprehensive and user-friendly platforms that address the specific needs of property managers and landlords. This includes features such as integrated accounting functionalities, robust reporting tools, and seamless integration with other real estate platforms. The increasing focus on data security and compliance with privacy regulations is also shaping the market landscape. Companies are investing heavily in cybersecurity measures and data encryption technologies to build trust and protect sensitive tenant and property data. Further innovation can be expected in areas such as artificial intelligence (AI)-powered features for predictive maintenance and tenant screening, enhancing the efficiency and profitability of property management operations. The market's growth trajectory is positive, with continued opportunities for expansion and innovation across different segments and geographical regions.

  18. G

    Landlord Insurance Tech Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 23, 2025
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    Growth Market Reports (2025). Landlord Insurance Tech Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/landlord-insurance-tech-market
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    pdf, csv, pptxAvailable download formats
    Dataset updated
    Aug 23, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Landlord Insurance Tech Market Outlook



    According to our latest research, the global Landlord Insurance Tech market size reached USD 2.48 billion in 2024, demonstrating a robust expansion driven by digital transformation in the insurance sector. The market is projected to grow at a CAGR of 12.4% from 2025 to 2033, reaching an estimated USD 7.13 billion by 2033. This impressive growth is primarily fueled by increasing adoption of digital platforms, rising demand for streamlined insurance processes, and heightened awareness among landlords regarding risk management and property protection.




    The primary growth factor for the Landlord Insurance Tech market is the rapid digitalization of the insurance industry. The integration of advanced technologies such as artificial intelligence, machine learning, and data analytics has enabled insurers to offer more personalized products, automate claims processing, and enhance risk assessment capabilities. This technological evolution not only reduces operational costs but also improves customer experience, making it easier for landlords to access, purchase, and manage insurance policies online. The shift towards digital insurance platforms is further accelerated by the proliferation of smart devices and growing internet penetration globally, allowing seamless connectivity between landlords and insurance providers.




    Another critical driver is the increasing complexity and diversity of rental property portfolios, especially in urban areas. As landlords manage multiple properties or units, the need for comprehensive insurance solutions that can be tailored to specific property types and risk profiles becomes paramount. Landlord Insurance Tech platforms are addressing this need by offering modular insurance products, real-time risk monitoring, and automated policy adjustments. These innovations not only mitigate financial losses from unforeseen events such as property damage or tenant default but also provide landlords with data-driven insights to optimize their property management strategies. The convergence of property management and insurance technology is creating new value propositions for both individual landlords and large property management companies.




    Additionally, regulatory changes and evolving legal requirements regarding landlord responsibilities and tenant protection are contributing to market growth. Governments in various regions are implementing stricter guidelines for property insurance, compelling landlords to seek advanced solutions that ensure compliance and reduce legal liabilities. Landlord Insurance Tech providers are responding by integrating regulatory compliance tools, automated documentation, and transparent claims processes into their platforms. This not only simplifies compliance for landlords but also enhances trust and transparency between landlords, tenants, and insurers, fostering further adoption of tech-driven insurance solutions.




    From a regional perspective, North America dominates the Landlord Insurance Tech market due to the high concentration of rental properties, well-established insurance infrastructure, and early adoption of digital technologies. Europe follows closely, driven by increasing investments in property technology (PropTech) and a strong regulatory framework supporting digital insurance solutions. The Asia Pacific region is emerging as a lucrative market, propelled by rapid urbanization, growing middle-class populations, and rising awareness about property risk management. Latin America and the Middle East & Africa are also witnessing steady growth, albeit at a slower pace, as digital transformation initiatives gain traction in these regions. The global landscape is characterized by diverse market dynamics, but the overarching trend is a clear shift towards technology-driven landlord insurance solutions.





    Component Analysis



    The Component segment of the Landlord Insurance Tech market is divided into software, hardware, and services, each playing a pivotal role in the digital tra

  19. T

    United States - Farm output: Rent paid to nonoperator landlords

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 10, 2020
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    TRADING ECONOMICS (2020). United States - Farm output: Rent paid to nonoperator landlords [Dataset]. https://tradingeconomics.com/united-states/farm-output-rent-paid-to-nonoperator-landlords-fed-data.html
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    xml, excel, json, csvAvailable download formats
    Dataset updated
    Mar 10, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Farm output: Rent paid to nonoperator landlords was 18.34000 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Farm output: Rent paid to nonoperator landlords reached a record high of 24.66500 in January of 2014 and a record low of 0.22000 in January of 1932. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Farm output: Rent paid to nonoperator landlords - last updated from the United States Federal Reserve on October of 2025.

  20. A

    Australia Percentage of Households: Tenure & Landlord: Owner with a Mortgage...

    • ceicdata.com
    Updated May 27, 2017
    + more versions
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    CEICdata.com (2017). Australia Percentage of Households: Tenure & Landlord: Owner with a Mortgage [Dataset]. https://www.ceicdata.com/en/australia/survey-of-income-and-housing-percentage-of-households-by-tenure--landlord/percentage-of-households-tenure--landlord-owner-with-a-mortgage
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    Dataset updated
    May 27, 2017
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2000 - Jun 1, 2020
    Area covered
    Australia
    Variables measured
    Household Income and Expenditure Survey
    Description

    Australia Percentage of Households: Tenure & Landlord: Owner with a Mortgage data was reported at 36.800 % in 2020. This records an increase from the previous number of 36.700 % for 2018. Australia Percentage of Households: Tenure & Landlord: Owner with a Mortgage data is updated yearly, averaging 35.050 % from Jun 1995 (Median) to 2020, with 16 observations. The data reached an all-time high of 37.100 % in 2016 and a record low of 28.100 % in 1996. Australia Percentage of Households: Tenure & Landlord: Owner with a Mortgage data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H042: Survey of Income and Housing: Percentage of Households: by Tenure & Landlord.

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data.montgomerycountymd.gov (2025). Housing Landlord-Tenant Disputes [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/housing-landlord-tenant-disputes

Housing Landlord-Tenant Disputes

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8 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 4, 2025
Dataset provided by
data.montgomerycountymd.gov
Description

The Housing Landlord-Tenant Case Tracking dataset includes tracking information, complaints and individual case dispositions. The data is updated monthly.

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