16 datasets found
  1. Lipper Fund Research Database

    • lseg.com
    Updated Jun 30, 2025
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    LSEG (2025). Lipper Fund Research Database [Dataset]. https://www.lseg.com/en/data-analytics/financial-data/fund-data/lipper-fund-data
    Explore at:
    csv,delimited,gzip,html,json,pdf,python,sql,text,user interface,xml,zip archiveAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset provided by
    London Stock Exchange Grouphttp://www.londonstockexchangegroup.com/
    Authors
    LSEG
    License

    https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer

    Description

    View LSEG's Lipper Fund Research Database, providing independent fund content to benchmark fund performance, manage risk, and more.

  2. Eulerpool Ownership API

    • eulerpool.com
    Updated Jul 30, 2025
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    Eulerpool (2025). Eulerpool Ownership API [Dataset]. https://eulerpool.com/data-analytics/finanzdaten/api/eulerpool-ownership-api
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    Dataset updated
    Jul 30, 2025
    Dataset provided by
    Eulerpool Research Systems
    Authors
    Eulerpool
    Description

    Access data on ownership by institutions, mutual funds, stakeholders, and float for both stocks and bonds on a global scale. Discover comprehensive details about shareholding patterns for equities and fixed-income instruments across the world, including institutional and mutual fund holdings, stakeholder interests, and floating shares. Obtain insights into the distribution of shares held by institutions, mutual funds, stakeholders, and the float for securities worldwide, encompassing both equities and bonds. Explore global share ownership information, covering institutional and mutual fund investments, stakeholder shares, and float-related holdings for both stocks and fixed-income securities.

  3. t

    Financial Data Tables

    • tradesmith.com
    json
    Updated Jun 18, 2025
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    (2025). Financial Data Tables [Dataset]. https://tradesmith.com/AFDG:OTC/owners
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 18, 2025
    Description

    API providing data for top institutional holders, mutual fund holders, and insider transactions.

  4. Fintual Mutual Fonds

    • kaggle.com
    Updated May 18, 2021
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    Diego Olguín (2021). Fintual Mutual Fonds [Dataset]. https://www.kaggle.com/diegoolgun/fintual-mutual-fonds/activity
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 18, 2021
    Dataset provided by
    Kaggle
    Authors
    Diego Olguín
    Description

    Context

    Fintual is a general fund manager that started as a startup that went through the YCombinator accelerator. In recent times, Fintual has become the place where many Chileans have invested to save as an alternative to traditional mutual funds. In parallel to the investment series A, Fintual has an APV series, which is intended as voluntary savings for people's old age, as support for the mandatory savings that exist by law in Chile.

    Fintual impone como novedad 4 nuevos fondos, de menos conservadores o más arriesgados son Conservative Streep, Moderate Pitt, Risky Norris. Los niveles de riesgo que Fintual dispone son 5 y son ponderaciones de estos 3 fondos, de más conservador a más arriesgado son:

    -Muy Conservador: Conservative Streep 100%

    -Conservador: Conservative Streep 57.8% + Moderate Pitt 42.2%

    -Moderado: Conservative Streep 20.5%+Moderate Pitt 79.5%

    -Arriesgado: Moderate Pitt %80.3 + Risky Norris %19.7

    -Muy Arriesgado: Moderate Pitt 38.5% + Risky Norris 61.5%

    Content

    The dataset is obtained from the Fintual API and the present files are 5:

    1. fonds_info: General Information.

    2. fonds_series_A: Features information from the Conservative Streep, Moderate Pitt, and Risky Norris funds for A series.

    3. fonds_series_APV: Same as fond_series_A, but for APV series.

    4. fintual_risk_lvl_A: Presents information on risk levels 'Muy Conservador', 'Conservador', 'Moderado', 'Arriesgado' and 'Muy arriesgado'.

    5. fintual_risk_lvl_APV: Same as fintual_risk_lvl_A, but for A series.

    Acknowledgements

    Thanks to the Fintual team for facilitating the extraction of data from their API as an add-on in Google Sheets. You can find more information about Fintual at www.fintual.com.

    Inspiration

    In Chile, the political, social and economic environment has lived through very volatile times. At the same time, Fintual has become the choice of ordinary people who do not have much information about investing, but at the same time are bored with rigid banking protocols, which is why Fintual has become a very popular option in the last moment. That is why analyzing how Fintual funds vary can be a different window to analyze the social, political and economic changes in Chile and how this is consistent with important national and international events in the future.

  5. U

    United Kingdom NFC: Resources: API: PI: OI: Collective Investment Fund...

    • ceicdata.com
    Updated Feb 15, 2025
    + more versions
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    CEICdata.com (2025). United Kingdom NFC: Resources: API: PI: OI: Collective Investment Fund Shareholders [Dataset]. https://www.ceicdata.com/en/united-kingdom/esa10-resources-and-uses-non-financial-corporations-primary-income/nfc-resources-api-pi-oi-collective-investment-fund-shareholders
    Explore at:
    Dataset updated
    Feb 15, 2025
    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, 2015 - Mar 1, 2018
    Area covered
    United Kingdom
    Variables measured
    Flow of Fund Account
    Description

    United Kingdom NFC: Resources: API: PI: OI: Collective Investment Fund Shareholders data was reported at 3.000 GBP mn in Jun 2018. This stayed constant from the previous number of 3.000 GBP mn for Mar 2018. United Kingdom NFC: Resources: API: PI: OI: Collective Investment Fund Shareholders data is updated quarterly, averaging 3.000 GBP mn from Mar 1987 (Median) to Jun 2018, with 126 observations. The data reached an all-time high of 6.000 GBP mn in Dec 2007 and a record low of 0.000 GBP mn in Dec 1989. United Kingdom NFC: Resources: API: PI: OI: Collective Investment Fund Shareholders data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.AB028: ESA10: Resources and Uses: Non Financial Corporations: Primary Income.

  6. e

    Eximpedia Export Import Trade

    • eximpedia.app
    Updated Jan 25, 2025
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    Seair Exim (2025). Eximpedia Export Import Trade [Dataset]. https://www.eximpedia.app/
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    .bin, .xml, .csv, .xlsAvailable download formats
    Dataset updated
    Jan 25, 2025
    Dataset provided by
    Eximpedia PTE LTD
    Eximpedia Export Import Trade Data
    Authors
    Seair Exim
    Area covered
    Ukraine, United Kingdom
    Description

    Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries

  7. d

    Alternative Data | Social Media-Based Insights on 800M+ Professionals &...

    • datarade.ai
    .json, .csv
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    Xverum, Alternative Data | Social Media-Based Insights on 800M+ Professionals & Companies for VC, Hedge Funds & Investment Analysis [Dataset]. https://datarade.ai/data-products/alternative-data-social-media-based-insights-on-800m-profe-xverum
    Explore at:
    .json, .csvAvailable download formats
    Dataset provided by
    Xverum LLC
    Authors
    Xverum
    Area covered
    Guatemala, Honduras, Macao, Benin, Tuvalu, Vietnam, Papua New Guinea, Spain, Nepal, France
    Description

    Xverum’s Alternative Data delivers a unique lens into the evolving landscape of global businesses - offering non-traditional insights built from social media signals and public web profiles. With over 750M enriched professional profiles and 50M verified companies, this dataset empowers investors, hedge funds, and analysts to identify hidden trends, benchmark headcount dynamics, and make smarter portfolio decisions.

    Our data bridges the gap between surface-level company metrics and internal workforce dynamics - ideal for those seeking high-signal, low-noise intelligence.

    🔍 Key Features: ✅ Social Media–Derived Insights: Profiles collected and enriched from open social platforms and web sources. ✅ Workforce Trend Monitoring: Track hiring surges, downsizing, department shifts, and growth by role or region. ✅ Educational Intelligence: Understand degree types, universities, and certifications across a company’s talent base. ✅ 50M Company Profiles: Enriched with org size, industry, location, and growth signals. ✅ Dynamic Dataset: Monthly refresh with 350M+ updates per month to ensure timeliness. ✅ Fully GDPR/CCPA-Compliant: Ethically sourced and privacy-secure.

    Primary Use Cases: 💠 VC & Hedge Fund Due Diligence Spot early-stage momentum and pre-IPO growth by tracking hiring trends, talent density, and team structure shifts.

    💠 Investment Signal Generation Discover investment opportunities based on headcount expansion, leadership changes, and team expertise indicators.

    💠 Corporate Intelligence & Benchmarking Compare peer companies by workforce size, education level, technical background, and hiring speed.

    💠 Talent Strategy & Workforce Analytics Analyze top roles, degrees, and backgrounds across competitive organizations.

    Why Xverum’s Alternative Data? ✅ 750M Verified Professional Profiles ✅ 50M Company Datasets with rich firmographics ✅ Unique social-driven signals for workforce tracking ✅ Investor-grade alternative intelligence ✅ Bulk delivery in .json or .csv formats ✅ S3 Bucket, Email, Cloud Services - fully flexible delivery

    Request a free sample today and discover how our social media–powered alternative data can enhance your investment strategies, VC scouting, and workforce due diligence.

  8. a

    Neighborhood Investment Fund Areas

    • statedemo-dcdev.hub.arcgis.com
    • ozmarketplace.dc.gov
    • +4more
    Updated Dec 29, 2008
    + more versions
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    City of Washington, DC (2008). Neighborhood Investment Fund Areas [Dataset]. https://statedemo-dcdev.hub.arcgis.com/datasets/DCGIS::neighborhood-investment-fund-areas
    Explore at:
    Dataset updated
    Dec 29, 2008
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    The dataset contains locations and attributes of Neighborhood Investment Fund Areas (NIF).The Neighborhood Investment Fund is an annual, non-lapsing fund to finance economic development and neighborhood revitalization in 12 targeted areas of the District. The fund is capitalized by an annual contribution of 15 percent of the personal property tax, not to exceed $10 million. The Neighborhood Investment Fund supports neighborhood revitalization through the Target Area Grant Program (TAPG) and Predevelopment and Project Grants (PDG).

  9. National Stock Exchange : Time Series

    • kaggle.com
    Updated Dec 4, 2019
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    Atul Anand {Jha} (2019). National Stock Exchange : Time Series [Dataset]. https://www.kaggle.com/atulanandjha/national-stock-exchange-time-series/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 4, 2019
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Atul Anand {Jha}
    License

    http://www.gnu.org/licenses/lgpl-3.0.htmlhttp://www.gnu.org/licenses/lgpl-3.0.html

    Description

    Context

    The National Stock Exchange of India Ltd. (NSE) is an Indian stock exchange located at Mumbai, Maharashtra, India. National Stock Exchange (NSE) was established in 1992 as a demutualized electronic exchange. It was promoted by leading financial institutions on request of the Government of India. It is India’s largest exchange by turnover. In 1994, it launched electronic screen-based trading. Thereafter, it went on to launch index futures and internet trading in 2000, which were the first of its kind in the country.

    With the help of NSE, you can trade in the following segments:

    • Equities

    • Indices

    • Mutual Funds

    • Exchange Traded Funds

    • Initial Public Offerings

    • Security Lending and Borrowing Scheme

    https://cdn6.newsnation.in/images/2019/06/24/Sharemarket-164616041_6.jpg" alt="Stock image">

    Companies on successful IPOs gets their Stocks traded over different Stock Exchnage platforms. NSE is one important platofrm in India. There are thousands of companies trading their stocks in NSE. But, I have chosen two popular and high rated IT service companies of India; TCS and INFOSYS. and the third one is the benchmark for Indian IT companies , i.e. NIFTY_IT_INDEX .

    Content

    The dataset contains three csv files. Each resembling to INFOSYS, NIFTY_IT_INDEX, and TCS, respectively. One can easily identify that by the name of CSV files.

    Timeline of Data recording : 1-1-2015 to 31-12-2015.

    Source of Data : Official NSE website.

    Method : We have used the NSEpy api to fetch the data from NSE site. I have also mentioned my approach in this Kernel - "**WebScraper to download data for NSE**". Please go though that to better understand the nature of this dataset.

    Shape of Dataset:

    INFOSYS - 248 x 15 || NIFTY_IT_INDEX - 248 x 7 || **TCS - 248 x 15

    • Colum Descriptors:

    • Date: date on which data is recorded

    • Symbol: NSE symbol of the stock

    • Series: Series of that stock | EQ - Equity

    OTHER SERIES' ARE:

    EQ: It stands for Equity. In this series intraday trading is possible in addition to delivery.

    BE: It stands for Book Entry. Shares falling in the Trade-to-Trade or T-segment are traded in this series and no intraday is allowed. This means trades can only be settled by accepting or giving the delivery of shares.

    BL: This series is for facilitating block deals. Block deal is a trade, with a minimum quantity of 5 lakh shares or minimum value of Rs. 5 crore, executed through a single transaction, on the special “Block Deal window”. The window is opened for only 35 minutes in the morning from 9:15 to 9:50AM.

    BT: This series provides an exit route to small investors having shares in the physical form with a cap of maximum 500 shares.

    GC: This series allows Government Securities and Treasury Bills to be traded under this category.

    IL: This series allows only FIIs to trade among themselves. Permissible only in those securities where maximum permissible limit for FIIs is not breached.

    • Prev Close: Last day close point

    • Open: current day open point

    • High: current day highest point

    • Low: current day lowest point

    • Last: the final quoted trading price for a particular stock, or stock-market index, during the most recent day of trading.

    • Close: Closing point for the current day

    • VWAP: volume-weighted average price is the ratio of the value traded to total volume traded over a particular time horizon

    • Volume: the amount of a security that was traded during a given period of time. For every buyer, there is a seller, and each transaction contributes to the count of total volume.

    • Turnover: Total Turnover of the stock till that day

    • Trades: Number of buy or Sell of the stock.

    • Deliverable: Volumethe quantity of shares which actually move from one set of people (who had those shares in their demat account before today and are selling today) to another set of people (who have purchased those shares and will get those shares by T+2 days in their demat account).

    • %Deliverble: percentage deliverables of that stock

    Acknowledgements

    I woul dlike to acknowledge all my sincere thanks to the brains behind NSEpy api, and in particular SWAPNIL JARIWALA , who is also maintaining an amazing open source github repo for this api.

    Inspiration

    I have also built a starter kernel for this dataset. You can find that right here .

    I am so excited to see your magical approaches for the same dataset.

    THANKS!

  10. CEO Contact Data | Venture Capital & Private Equity Investors in the USA |...

    • datarade.ai
    Updated Jan 1, 2018
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    Success.ai (2018). CEO Contact Data | Venture Capital & Private Equity Investors in the USA | Verified Global Profiles from 700M+ Dataset | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/ceo-contact-data-venture-capital-private-equity-investors-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 1, 2018
    Dataset provided by
    Area covered
    United States
    Description

    Success.ai presents an exclusive opportunity to connect directly with top-tier decision-makers in the finance sector through our CEO Contact Data, specifically designed for venture capital and private equity investors based in the USA. This tailored database is part of our expansive collection that draws from over 700 million global profiles, meticulously verified to ensure the highest quality and reliability.

    Why Choose Success.ai’s CEO Contact Data?

    Specialized Investor Profiles: Access detailed profiles of CEOs and senior executives from leading venture capital and private equity firms across the United States. Investment Insights: Gain valuable insights into investment trends, fund sizes, and sectors of interest directly from the decision-makers. Verified Contact Details: We provide up-to-date email addresses and phone numbers, ensuring that you reach the right people without the hassle of outdated information. Data Features:

    Targeted Financial Sector Data: Directly target influential figures in the financial sector who have the authority to make investment decisions. Comprehensive Executive Information: Profiles include not just contact information but also professional backgrounds, areas of investment focus, and operational histories. Geographic Precision: Focus your outreach efforts on US-based investors with our geographically segmented data. Flexible Delivery and Integration: Choose from various delivery options including API access for real-time integration or static files for periodic campaign use, allowing for seamless incorporation into your CRM or marketing automation tools.

    Competitive Pricing with Best Price Guarantee: Success.ai is committed to providing competitive pricing without compromising on quality, backed by our Best Price Guarantee.

    Effective Use Cases for CEO Contact Data:

    Fundraising Initiatives: Connect with venture capital and private equity firms for fundraising activities or financial endorsements. Partnership Development: Forge strategic partnerships and collaborations with leading investors in the industry. Event Invitations: Send personalized invites to investment summits, roundtables, and networking events catered to top financial executives. Market Analysis: Utilize executive insights to better understand the investment landscape and refine your market strategies. Quality Assurance and Compliance:

    Rigorous Data Verification: Our data undergoes continuous verification processes to maintain accuracy and completeness. Compliance with Regulations: All data handling practices adhere to GDPR and other relevant data protection laws, ensuring ethical and lawful use. Support and Custom Solutions:

    Client Support: Our team is available to assist with any queries or specific data needs you may have. Tailored Data Solutions: Customize data sets according to specific criteria such as investment size, sector focus, or geographic location. Start Connecting with Venture Leaders: Empower your business strategy and network building by accessing Success.ai’s CEO Contact Data for venture capital and private equity investors. Whether you're looking to initiate funding rounds, explore investment opportunities, or engage with top financial leaders, our reliable data will pave the way for meaningful connections and successful outcomes.

    Contact Success.ai today to discover how our precise and comprehensive data can transform your business approach and help you achieve your strategic goals.

  11. 2017 Climate Investment Funds SREP results data

    • kaggle.com
    Updated Jan 1, 2021
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    World Bank (2021). 2017 Climate Investment Funds SREP results data [Dataset]. https://www.kaggle.com/theworldbank/2017-climate-investment-funds-srep-results-data/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 1, 2021
    Dataset provided by
    Kaggle
    Authors
    World Bank
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    The results data presented below is based on the portfolio of SREP projects and has been compiled on behalf of the following multilateral development banks: ADB, AFDB, IDB, IFC and IBRD. It follows the principles outlined under the Revised SREP Results Framework and includes the indicators that help determine whether and to what extent the SREP interventions achieve the proposed project outcome objectives involving: (a) Annual electricity output; (b) Improved energy access to people, businesses and community services; (c) GHG emissions reduced/avoided (tons of CO2 equivalent); (d) increased public and private investments in targeted subsectors (co-financing) You can learn more and get further analysis at the 2017 SREP Operational and Results Report: https://www.climateinvestmentfunds.org/sites/default/files/meeting-documents/srep_18_3_orr_1.pdf

    Context

    This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore World Bank's Financial Data using Kaggle and all of the data sources available through the World Bank organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

    This dataset is distributed under Creative Commons Attribution 3.0 IGO

  12. Venture Capital Funding Data | Global VC Professionals | Verified Profiles...

    • datarade.ai
    Updated Feb 12, 2018
    + more versions
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    Success.ai (2018). Venture Capital Funding Data | Global VC Professionals | Verified Profiles with Work Emails | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/venture-capital-funding-data-global-vc-professionals-veri-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Feb 12, 2018
    Dataset provided by
    Area covered
    Australia, Western Sahara, Iraq, Indonesia, Barbados, Bahrain, Moldova (Republic of), Saint Pierre and Miquelon, Liechtenstein, Anguilla
    Description

    Success.ai provides unparalleled access to Venture Capital Funding Data, meticulously curated to support organizations in identifying, connecting with, and analyzing global venture capital professionals. Our robust database includes verified profiles of VC analysts, fund managers, investment partners, and other key decision-makers. With AI-driven validation, continuously updated data, and extensive global coverage, our solutions empower businesses to excel in fundraising, partnership development, and strategic investment decisions.

    Key Features of Success.ai's Venture Capital Funding Data:

    Global Reach: Access profiles of venture capital professionals across 250+ countries, representing the world’s leading VC firms and emerging funds.

    Comprehensive Profiles: Gain insights into the professional histories, investment focuses, and contact details of fund managers, analysts, and partners. Each profile includes work emails, phone numbers, and firmographic data.

    Industry-Specific Data: Tailored to industries such as technology, healthcare, renewable energy, e-commerce, and more, ensuring highly relevant data for targeted outreach.

    Real-Time Accuracy: Our AI-driven systems continuously update datasets to ensure a 99% accuracy rate, delivering the most reliable and actionable insights for your needs.

    GDPR-Compliant Data: Fully compliant with global data privacy standards, ensuring ethical and legal usage across all business practices.

    Why Choose Success.ai for Venture Capital Funding Data?

    Best Price Guarantee: Our pricing is the most competitive in the market, ensuring you get maximum value for comprehensive VC funding data.

    AI-Validated Accuracy: Advanced AI technology verifies every data point, reducing errors and improving efficiency in your outreach and analysis.

    Tailored Solutions: Whether you need industry-specific data or a broader view of the VC landscape, our datasets are customized to meet your exact requirements.

    Scalable Access: From startups seeking funding to established firms analyzing VC markets, our platform scales to meet the needs of all users.

    Comprehensive Use Cases for VC Funding Data:

    1. Fundraising Strategies:

    Identify and connect with venture capitalists whose investment priorities align with your business goals. Use verified profiles to build meaningful relationships and secure funding.

    1. Market Research and Analysis:

    Understand the VC landscape, including trends, emerging sectors, and regional investment hotspots. Leverage this data to stay ahead in competitive markets.

    1. Partnership Development:

    Access detailed profiles to identify potential partners for co-investments, joint ventures, or syndications. Build strong networks with the right contacts.

    1. Lead Generation:

    Enhance your lead generation efforts with verified contact details for decision-makers at leading VC firms. Use accurate email and phone data to improve conversion rates.

    1. Event Planning and Outreach:

    Plan targeted events or outreach campaigns by accessing detailed data on VC professionals in your target sectors and regions.

    APIs to Supercharge Your Outreach:

    Enrichment API: Keep your systems up-to-date with real-time data enrichment, ensuring your VC contact lists remain accurate and actionable.

    Lead Generation API: Access verified profiles and key contact details to maximize the efficiency of your lead generation campaigns. Perfect for connecting with top-tier venture capitalists and fund managers.

    Tailored Solutions for Diverse Needs:

    Startup Founders: Identify potential investors aligned with your funding stage and sector.

    Investment Banks: Gain insights into VC funding trends and key players to support advisory services.

    Corporate Development Teams: Discover VCs for partnership opportunities or to fund internal innovation projects.

    Consulting Firms: Provide data-driven recommendations to clients by leveraging detailed VC funding data.

    What Sets Success.ai Apart?

    Extensive Database: Access verified profiles of thousands of venture capital professionals, from analysts to managing partners, across diverse industries and regions.

    Ethical and Legal Compliance: All data is ethically sourced and complies with global standards, including GDPR, giving you confidence in every interaction.

    Customizable Delivery: Receive data tailored to your specifications, whether you need a comprehensive dataset or niche industry insights.

    Expert Support: Our team of experts is always available to help you maximize the value of our data solutions.

    Transform Your Outreach with Success.ai:

    With Venture Capital Funding Data, Success.ai empowers you to connect with the right investors, streamline your fundraising efforts, and gain unparalleled insights into the global VC ecosystem. Whether you’re a startup founder, corporate executive, or investment professional, our data solutions provide the tools you need to succeed.

    Get star...

  13. Artificial Intelligence Market (AI) In Asset Management Analysis, Size, and...

    • technavio.com
    Updated Jun 23, 2024
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    Technavio (2024). Artificial Intelligence Market (AI) In Asset Management Analysis, Size, and Forecast 2025-2029: North America (Mexico), Europe (France, Germany, Italy, Spain, and UK), Middle East and Africa (UAE), APAC (Australia, China, India, Japan, and South Korea), South America (Brazil), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/artificial-intelligence-in-asset-management-market-analysis
    Explore at:
    Dataset updated
    Jun 23, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global
    Description

    Snapshot img

    Artificial Intelligence Market (AI) In Asset Management Size 2025-2029

    The AI in asset management size is forecast to increase by USD 25.17 billion at a CAGR of 44.1% between 2024 and 2029.

    The Artificial Intelligence (AI) market in asset management is experiencing significant growth, driven by the rapid adoption of AI technologies to enhance asset performance tracking and management capabilities. This trend is further fueled by the increasing popularity of cloud-based AI services, which offer greater flexibility and scalability for asset managers. However, the market also faces challenges related to data privacy and cybersecurity concerns, which require careful attention from industry players. Asset managers must ensure the secure handling of sensitive financial data and maintain compliance with regulatory requirements to mitigate risks and protect client information.
    Navigating these challenges while capitalizing on the opportunities presented by AI in asset management requires a strategic approach and a deep understanding of the market landscape. Companies seeking to succeed in this market must prioritize data security, invest in advanced AI technologies, and build robust compliance frameworks to meet the evolving needs of clients and regulators.
    

    What will be the Size of the Artificial Intelligence Market (AI) In Asset Management during the forecast period?

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    The artificial intelligence (AI) market in asset management continues to evolve, with various sectors integrating advanced technologies to enhance operations and improve investment strategies. Regulatory reporting and due diligence processes are streamlined through API integration and decision support systems. Virtual advisors and family offices cater to retail investors, while institutional investors, pension funds, and alternative investment managers leverage machine learning for asset allocation and risk management. AI-driven trading and predictive analytics enable quantitative investment management and high-frequency trading. Additionally, computer vision and natural language processing facilitate financial modeling and investment research.
    The ongoing integration of AI in asset management ensures continuous optimization and adaptation to market dynamics. Cloud computing enables scalable implementation and deployment of these advanced technologies. Overall, the AI market in asset management remains a dynamic and evolving landscape, with ongoing innovation and application across various sectors.
    

    How is this Artificial Intelligence (AI) In Asset Management Industry segmented?

    The artificial intelligence (ai) in asset management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Deployment
    
      On-premises
      Cloud
    
    
    Application
    
      BFSI
      Retail and e-commerce
      Healthcare
      Energy and utilities
      Others
    
    
    Technology
    
      Machine learning
      Natural language processing
      Others
    
    
    Solution Type
    
      Portfolio Optimization
      Risk Management
      Predictive Analytics
      Robo-Advisors
    
    
    Geography
    
      North America
    
        US
        Mexico
    
    
      Europe
    
        France
        Germany
        Italy
        Spain
        UK
    
    
      Middle East and Africa
    
        UAE
    
    
      APAC
    
        Australia
        China
        India
        Japan
        South Korea
    
    
      South America
    
        Brazil
    
    
      Rest of World (ROW)
    

    By Deployment Insights

    The on-premises segment is estimated to witness significant growth during the forecast period.

    The on-premises segment of the artificial intelligence (AI) market in asset management is experiencing notable growth. On-premises AI solutions offer organizations greater control and flexibility over their data, as they are installed locally and customized to meet specific business requirements. Deep learning and machine learning algorithms are integrated into these solutions for advanced data analysis, enabling hedge funds, institutional investors, and family offices to make informed investment decisions. AI-driven risk management and fraud detection systems enhance financial technology, ensuring data security and regulatory compliance. Big data and predictive analytics are harnessed for quantitative investment management and portfolio optimization. Furthermore, AI-powered portfolio management and customer relationship management streamline operations, while natural language processing facilitates efficient investment research.

    AI assistants and virtual advisors cater to retail investors, offering personalized investment strategies and recommendations. Cloud computing enables seamless API integration and real-time data processing, while algorithmic trading and high-frequency trading leverage AI for enhanced market insights. AI-driven research and sentiment analysis provide valuable alternativ

  14. t

    Trust Fund Impact on Budget Results and Investment Holdings

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Trust Fund Impact on Budget Results and Investment Holdings [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This table shows the total receipts and outlays and the resulting surplus or deficit (shown on the table as excess) for the current month and the current fiscal year-to-date for all federal trust funds. The table also shows the totals for securities held as investments by the federal trust funds for the beginning of the fiscal year and the beginning and ending of the current accounting month. A trust fund is a type of account, designated by law, for receipts or offsetting receipts dedicated to specific purposes and the expenditure of these receipts. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  15. 英国 NFC:资源:API:PI:OI:集合投资基金股东

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). 英国 NFC:资源:API:PI:OI:集合投资基金股东 [Dataset]. https://www.ceicdata.com/zh-hans/united-kingdom/esa10-resources-and-uses-non-financial-corporations-primary-income/nfc-resources-api-pi-oi-collective-investment-fund-shareholders
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    Dataset updated
    Feb 15, 2025
    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, 2015 - Mar 1, 2018
    Area covered
    英国
    Variables measured
    Flow of Fund Account
    Description

    NFC:资源:API:PI:OI:集合投资基金股东在06-01-2018达3.000百万英镑,相较于03-01-2018的3.000百万英镑保持不变。NFC:资源:API:PI:OI:集合投资基金股东数据按季更新,03-01-1987至06-01-2018期间平均值为3.000百万英镑,共126份观测结果。该数据的历史最高值出现于12-01-2007,达6.000百万英镑,而历史最低值则出现于12-01-1989,为0.000百万英镑。CEIC提供的NFC:资源:API:PI:OI:集合投资基金股东数据处于定期更新的状态,数据来源于Office for National Statistics,数据归类于全球数据库的英国 – 表 UK.AB028:2010年欧洲账户体系:资源和使用:非金融企业:主要收入。

  16. 英国 NFC:资源:季节性调整后:API:PI:OI:集合投资基金股东

    • ceicdata.com
    Updated Aug 20, 2018
    + more versions
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    CEICdata.com (2018). 英国 NFC:资源:季节性调整后:API:PI:OI:集合投资基金股东 [Dataset]. https://www.ceicdata.com/zh-hans/united-kingdom/esa10-resources-and-uses-non-financial-corporations-primary-income/nfc-resources-sa-api-pi-oi-collective-investment-fund-sharehol
    Explore at:
    Dataset updated
    Aug 20, 2018
    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, 2015 - Mar 1, 2018
    Area covered
    英国
    Variables measured
    Flow of Fund Account
    Description

    NFC:资源:季节性调整后:API:PI:OI:集合投资基金股东在06-01-2018达3.000百万英镑,相较于03-01-2018的3.000百万英镑保持不变。NFC:资源:季节性调整后:API:PI:OI:集合投资基金股东数据按季更新,03-01-1987至06-01-2018期间平均值为3.000百万英镑,共126份观测结果。该数据的历史最高值出现于12-01-2007,达6.000百万英镑,而历史最低值则出现于12-01-1989,为0.000百万英镑。CEIC提供的NFC:资源:季节性调整后:API:PI:OI:集合投资基金股东数据处于定期更新的状态,数据来源于Office for National Statistics,数据归类于全球数据库的英国 – 表 UK.AB028:2010年欧洲账户体系:资源和使用:非金融企业:主要收入。

  17. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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LSEG (2025). Lipper Fund Research Database [Dataset]. https://www.lseg.com/en/data-analytics/financial-data/fund-data/lipper-fund-data
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Lipper Fund Research Database

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10 scholarly articles cite this dataset (View in Google Scholar)
csv,delimited,gzip,html,json,pdf,python,sql,text,user interface,xml,zip archiveAvailable download formats
Dataset updated
Jun 30, 2025
Dataset provided by
London Stock Exchange Grouphttp://www.londonstockexchangegroup.com/
Authors
LSEG
License

https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer

Description

View LSEG's Lipper Fund Research Database, providing independent fund content to benchmark fund performance, manage risk, and more.

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