This table shows the aggregate assets and liabilities of hedge funds that file Form PF with the Securities and Exchange Commission. Unlike table B.101.f in the regular Financial Accounts publication, which reports assets and liabilities of domestic hedge funds only, this table presents data on all hedge funds that file Form PF, both domestic and foreign.

The share of systematic hedge fund launches that uses artificial intelligence or machine learning grew overall during the last decade. One percent of fund launches in 2010 used artificial intelligence or machine learning, and the proportion peaked at 24 percent of fund launches in 2018.

The Investment Fund Services market is experiencing robust growth, projected to reach a market size of $150 billion by 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This expansion is driven by several key factors. The increasing complexity of global financial regulations necessitates sophisticated fund administration and management solutions, fueling demand for specialized services. Furthermore, the rise of alternative investment vehicles, such as private equity and hedge funds, is contributing significantly to market growth. Technological advancements, including the adoption of AI and machine learning for portfolio optimization and risk management, are streamlining operations and improving efficiency. The expanding global wealth pool and rising institutional investment in funds further underpin the market's trajectory. Increased regulatory scrutiny is also impacting the market, encouraging players to invest in compliance and risk management solutions. The market is segmented by type (Software, Service) and application (Enterprise, Individual), catering to diverse client needs. Key players like DTCC, Clearstream, and several major global banks are actively competing, driving innovation and service enhancement. Geographic distribution shows a strong concentration in North America and Europe, which currently hold the largest market share. However, the Asia-Pacific region, particularly China and India, demonstrates significant growth potential due to burgeoning domestic wealth and increased foreign investment. While market expansion is robust, potential restraints include cybersecurity threats, data privacy concerns, and the complexity of integrating new technologies into existing infrastructures. Successful players will need to navigate these challenges effectively to maintain their market position and capitalize on the significant opportunities ahead. The forecast period of 2025-2033 indicates a continued strong performance, fueled by technological innovation and growing global demand.

High-Flyer hedge fund boldly redirects its $13.79 billion assets towards AGI, emblematic of its technological foresight and ambition.

In the third quarter of 2020, funding for artificial intelligence (AI)-focused companies reached 4.7 billion U.S. dollars in the United States. This quarter’s funding was the second largest over this four-year time period. Overall, artificial intelligence funding investment in the U.S. has significantly grown over the past few years.

AI investment in the U.S.

The United States leads in private investments in AI when compared with other regions around the world, especially considering that the top three investors for AI investments in the world are U.S. companies, namely Intel Capital, 500 Startups, and Y Combinator. The U.S.’s dominance in AI investment contributes to its increased role in the global AI industry. When compared with other countries, it is deemed as the most AI-ready government, which means that the U.S. is considered the country best situated in the world to implement AI within public services, from healthcare to education to transportation. Moreover, North America currently makes up the region with the most AI patent publications, which may also contribute to the U.S.’s dominant role in AI.

AI adoption in U.S. companies

AI has already been implemented in many organizations within the United States, with many of those who do not currently use AI planning to use it in some capacity in the future. This is not overly surprising given that companies who have fully embraced AI see more of a positive impact on their organizations than those who have not done so. The leading AI and analytic application for U.S. organizations is managing risk, fraud, and cybersecurity threats.

The High-frequency Trading Market is projected to be valued at 5.6 billion USD in 2024, driven by factors such as increasing consumer awareness and the rising prevalence of industry-specific trends. The market is expected to grow at a CAGR of 7.5%, reaching approximately 10.2 billion USD by 2034.

The US hedge fund market, a significant segment of the global alternative investment landscape, is projected to experience robust growth over the forecast period (2025-2033). With a 2025 market size estimated at $2.77 trillion (based on global data and US market dominance), a Compound Annual Growth Rate (CAGR) of 6.52% suggests a substantial expansion. This growth is driven by several factors, including increasing institutional investor participation seeking higher returns beyond traditional asset classes, the ongoing development of sophisticated investment strategies like quantitative and data-driven approaches, and a persistent need for diversification within investment portfolios. While regulatory scrutiny and economic uncertainty pose potential constraints, the adaptability of hedge fund managers and their capacity to navigate market volatility are expected to mitigate these risks. Specific strategies like equity, macro, and event-driven approaches continue to attract significant capital, alongside the rising prominence of more specialized niche strategies catering to unique market opportunities. The concentration of major players like Bridgewater Associates and Renaissance Technologies within the US contributes significantly to the market's strength and dynamism. The competitive landscape within the US hedge fund market remains fiercely contested. Established firms consistently refine their strategies and leverage technological advancements to maintain an edge, while emerging managers seek to differentiate themselves through innovative approaches. Geographic concentration, with a significant portion of the market residing in major financial hubs like New York and Connecticut, suggests opportunities for regional expansion and potential diversification into less saturated areas. The ongoing evolution of technology, particularly within artificial intelligence and machine learning, is expected to significantly impact investment strategies and operational efficiencies across the industry, driving further growth and innovation in the coming years. The overall outlook remains optimistic, with the US hedge fund market poised for considerable expansion fueled by evolving investor demands and the inherent resilience of alternative investment strategies. Recent developments include: January 2024: The Palm Beach Hedge Fund Association (PBHFA), the premier trade association for investors and financial professionals in South Florida, and Entoro, a leading boutique finance and investment banking group, announced a strategic partnership to improve deal distribution for hedge funds., October 2022: Divya Nettimi, a former Viking Global Investors portfolio manager who oversaw over USD 4 billion at the Greenwich, Connecticut-based hedge fund firm, became the first woman to launch a hedge fund that has committed more than USD 1 billion.. Key drivers for this market are: Positive Trends in Equity Market is Driving the Market. Potential restraints include: Positive Trends in Equity Market is Driving the Market. Notable trends are: Rise of the Crypto Hedge Funds in United States.

In 2022, the global total corporate investment in artificial intelligence (AI) reached almost 92 billion U.S. dollars, a slight decrease from the previous year. In 2018, the yearly investment in AI saw a slight downturn, but that was only temporary. Private investments account for a bulk of total AI corporate investment. AI investment has increased more than sixfold since 2016, a staggering growth in any market. It is a testament to the importance of the development of AI around the world.

What is Artificial Intelligence (AI)?

Artificial intelligence, once the subject of people’s imaginations and the main plot of science fiction movies for decades, is no longer a piece of fiction, but rather commonplace in people’s daily lives whether they realize it or not. AI refers to the ability of a computer or machine to imitate the capacities of the human brain, which often learns from previous experiences to understand and respond to language, decisions, and problems. These AI capabilities, such as computer vision and conversational interfaces, have become embedded throughout various industries’ standard business processes.

AI investment and startups

The global AI market, valued at 142.3 billion U.S. dollars as of 2023, continues to grow driven by the influx of investments it receives. This is a rapidly growing market, looking to expand from billions to trillions of U.S. dollars in market size in the coming years. From 2020 to 2022, investment in startups globally, and in particular AI startups, increased by five billion U.S. dollars, nearly double its previous investments, with much of it coming from private capital from U.S. companies. The most recent top-funded AI businesses are all machine learning and chatbot companies, focusing on human interface with machines.

Analysis of ‘Ratio of non-state investment leveraged to MHT administered funds awarded’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/233a4303-4a0b-45ac-b8b2-75c542f97b21 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This data shows how much private investment is generated with awards of state funds.

--- Original source retains full ownership of the source dataset ---

The Global Fintech-as-a-Service Platform Market Size Was Worth USD 232.17 Billion in 2021 and Is Expected To Reach USD 949 Billion by 2028, CAGR of 17%.

Lucror Analytics: Proprietary Hedge Funds Data for Credit Quality & Bond Valuation

At Lucror Analytics, we provide cutting-edge corporate data solutions tailored to fixed income professionals and organizations in the financial sector. Our datasets encompass issuer and issue-level credit quality, bond fair value metrics, and proprietary scores designed to offer nuanced, actionable insights into global bond markets that help you stay ahead of the curve. Covering over 3,300 global issuers and over 80,000 bonds, we empower our clients to make data-driven decisions with confidence and precision.

By leveraging our proprietary C-Score, V-Score , and V-Score I models, which utilize CDS and OAS data, we provide unparalleled granularity in credit analysis and valuation. Whether you are a portfolio manager, credit analyst, or institutional investor, Lucror’s data solutions deliver actionable insights to enhance strategies, identify mispricing opportunities, and assess market trends.

What Makes Lucror’s Hedge Funds Data Unique?

Proprietary Credit and Valuation Models Our proprietary C-Score, V-Score, and V-Score I are designed to provide a deeper understanding of credit quality and bond valuation:

C-Score: A composite score (0-100) reflecting an issuer's credit quality based on market pricing signals such as CDS spreads. Responsive to near-real-time market changes, the C-Score offers granular differentiation within and across credit rating categories, helping investors identify mispricing opportunities.

V-Score: Measures the deviation of an issue’s option-adjusted spread (OAS) from the market fair value, indicating whether a bond is overvalued or undervalued relative to the market.

V-Score I: Similar to the V-Score but benchmarked against industry-specific fair value OAS, offering insights into relative valuation within an industry context.

Comprehensive Global Coverage Our datasets cover over 3,300 issuers and 80,000 bonds across global markets, ensuring 90%+ overlap with prominent IG and HY benchmark indices. This extensive coverage provides valuable insights into issuers across sectors and geographies, enabling users to analyze issuer and market dynamics comprehensively.

Data Customization and Flexibility We recognize that different users have unique requirements. Lucror Analytics offers tailored datasets delivered in customizable formats, frequencies, and levels of granularity, ensuring that our data integrates seamlessly into your workflows.

High-Frequency, High-Quality Data Our C-Score, V-Score, and V-Score I models and metrics are updated daily using end-of-day (EOD) data from S&P. This ensures that users have access to current and accurate information, empowering timely and informed decision-making.

How Is the Data Sourced? Lucror Analytics employs a rigorous methodology to source, structure, transform and process data, ensuring reliability and actionable insights:

Proprietary Models: Our scores are derived from proprietary quant algorithms based on CDS spreads, OAS, and other issuer and bond data.

Global Data Partnerships: Our collaborations with S&P and other reputable data providers ensure comprehensive and accurate datasets.

Data Cleaning and Structuring: Advanced processes ensure data integrity, transforming raw inputs into actionable insights.

Primary Use Cases

1. Portfolio Construction & Rebalancing Lucror’s C-Score provides a granular view of issuer credit quality, allowing portfolio managers to evaluate risks and identify mispricing opportunities. With CDS-driven insights and daily updates, clients can incorporate near-real-time issuer/bond movements into their credit assessments.

2. Portfolio Optimization The V-Score and V-Score I allow portfolio managers to identify undervalued or overvalued bonds, supporting strategies that optimize returns relative to credit risk. By benchmarking valuations against market and industry standards, users can uncover potential mean-reversion opportunities and enhance portfolio performance.

3. Risk Management With data updated daily, Lucror’s models provide dynamic insights into market risks. Organizations can use this data to monitor shifts in credit quality, assess valuation anomalies, and adjust exposure proactively.

4. Strategic Decision-Making Our comprehensive datasets enable financial institutions to make informed strategic decisions. Whether it’s assessing the fair value of bonds, analyzing industry-specific credit spreads, or understanding broader market trends, Lucror’s data delivers the depth and accuracy required for success.

Why Choose Lucror Analytics for Hedge Funds Data? Lucror Analytics is committed to providing high-quality, actionable data solutions tailored to the evolving needs of the financial sector. Our unique combination of proprietary models, rigorous sourcing of high-quality data, and customizable delivery ensures that users have the insights they need to make smarter dec...

Middle Office Outsourcing Market size was valued at USD 8087.59 Million in 2023 and is projected to reach USD 14844.38 Million by 2031, growing at a CAGR of 8.70% from 2024 to 2031.

Key Market Drivers:
Cost Efficiency and Scalability: One of the key reasons for middle office outsourcing is the possibility of cost savings. Outsourcing middle office operations such as risk management, compliance, and trade processing allows businesses to drastically cut operational expenses associated with keeping in-house staff. Outsourcing providers frequently have specialized knowledge and economies of scale allowing them to provide certain services more efficiently.
Access to Advanced Technology and Expertise: Another important factor is having access to cutting-edge technology and specialized knowledge. Middle office operations necessitate complex tools and systems for data management, analytics, and compliance monitoring. Outsourcing providers invest extensively in these technologies allowing their clients to access cutting-edge solutions that would be prohibitively expensive to develop in-house.
Regulatory Compliance and Risk Management: The growing complexity of regulatory regulations is another major driver of middle office outsourcing. Financial organizations face severe rules that necessitate strong compliance and risk management systems. Companies that outsource these services can reduce the risk of non-compliance and the resulting penalties. Outsourcing firms specialize in keeping up with changing rules and have the means to keep their clients compliant.

AIML hedge funds, which are hedge funds using artificial intelligence or machine learning, performed better than systematic hedge funds and all hedge funds during the second quarter 2019, but performed the worst during the other quarters of that year. During the third quarter 2019, AIML hedge funds had negative net returns of 2.82 percent, while systematic hedge funds had negative net returns of -0.11 percent. However, AIML hedge funds outperform other hedge funds in the long run.

The largest private investment in artificial intelligence (AI) companies was in the medical and healthcare field. The investment there was over six billion U.S. dollars. Other substantial investments were found in data management, fintech, and cybersecurity, with around or over five point five billion U.S. dollars in investment within each of those fields. The lowest amount of investment was in AI companies in the venture capital (VC) field, with barely 20 million U.S. dollars invested. The only other industry with such low investment numbers was facial recognition, with barely 70 million U.S. dollars invested.

The financial sector's spending on artificial intelligence (AI) is projected to experience substantial growth, with an estimated increase from 35 billion U.S. dollars in 2023 to 126.4 billion U.S. dollars in 2028. This represents a compound annual growth rate (CAGR) of 29 percent, indicating a significant upward trajectory in AI investment within the financial industry. AI investment across industries In 2023, the banking and retail sectors led in AI investments, with the banking sector accounting for 20.6 billion U.S. dollars and the retail sector investing 19.7 billion U.S. dollars. This demonstrates the varying degrees of AI adoption across different industries, with the financial sector poised for substantial growth over the coming years. These findings highlight the competitive landscape of AI investment and the potential for the financial sector to capitalize on AI technologies. Global corporate AI investment trends The global corporate investment in AI reached nearly 92 billion U.S. dollars in 2022, marking a significant increase from previous years. Private investments played a substantial role in driving this growth, underscoring the increasing importance of AI development worldwide. This trend signifies a strong foundation for the expansion of AI technologies, with implications for the financial sector's investment landscape as it navigates the evolving AI market.

Comprehensive dataset of insider trading activities for Golden Gate Capital Investment Fund II-A (AI), L.P., including Form 4 filings and transaction visualizations across multiple companies.

This data sample illustrates how Consumer Edge data can be used by public investors to track quarterly performance, providing quarterly spend for a set of public tickers and private companies.

Inquire about a CE subscription to perform more complex, near real-time quantitative analysis on public tickers and private brands like: • Analyze transaction-level data to uncover hidden trends, identify emerging consumer preferences, and be the first to anticipate shifts in market forces • Leverage the largest panel with the most history and unprecedented accuracy to inform buy/sell/hold decisions for enhanced ability to capture alpha

Consumer Edge offers a variety of datasets covering the US and Europe (UK, Austria, France, Germany, Italy, Spain), with subscription options serving a wide range of business needs.

Use Case: Tracking Quarterly Performance

Problem Understand growth drivers and age demographics of off-price retailers to predict quarterly performance.

Solution Leverage CE Data to monitor off-price retailers traffic growth and age demographics. June 2024: Following another quarter of sales growth, off-price retailers TJX and ROST cited increased traffic and marketability across age demographics as drivers of performance. CE data shows that TJX is growing among the youngest and oldest shoppers, whereas ROST experienced a rise in traffic among the middle-aged cohorts.

Off-price retailer TJX Companies, Inc. (TJX) recently reported US Sales Growth of 5.3%, close to CE Implied Reported Growth of 5.0% and below consensus of 5.6%.

Off-price retailer Ross Stores, Inc (ROST) reported net sales of 8.1%, in line with CE Implied Reported Growth of 8.1% and above consensus of 7.4%.

Clients can utilize CE cohort tools to monitor traffic among different age demographics at off-price retailers such as TJX and ROST.

Corporate researchers and consumer insights teams use CE Vision for:

Corporate Strategy Use Cases • Ecommerce vs. brick & mortar trends • Real estate opportunities • Economic spending shifts

Marketing & Consumer Insights • Total addressable market view • Competitive threats & opportunities • Cross-shopping trends for new partnerships • Demo and geo growth drivers • Customer loyalty & retention

Investor Relations • Shareholder perspective on brand vs. competition • Real-time market intelligence • M&A opportunities

Most popular use cases for private equity and venture capital firms include: • Deal Sourcing • Live Diligences • Portfolio Monitoring

Public and private investors can leverage insights from CE’s synthetic data to assess investment opportunities, while consumer insights, marketing, and retailers can gain visibility into transaction data’s potential for competitive analysis, understanding shopper behavior, and capturing market intelligence.

Most popular use cases among public and private investors from quant and systematic funds to quantamental and fundamental funds include: • Track Key KPIs to Company-Reported Figures • Understanding TAM for Focus Industries • Competitive Analysis • Evaluating Public, Private, and Soon-to-be-Public Companies • Ability to Explore Geographic & Regional Differences • Cross-Shop & Loyalty • Drill Down to SKU Level & Full Purchase Details • Customer lifetime value • Earnings predictions • Uncovering macroeconomic trends • Analyzing market share • Performance benchmarking • Understanding share of wallet • Seeing subscription trends

Fields Include: • Day • Merchant • Subindustry • Industry • Spend • Transactions • Spend per Transaction (derivable) • Cardholder State • Cardholder CBSA • Cardholder CSA • Age • Income • Wealth • Ethnicity • Political Affiliation • Children in Household • Adults in Household • Homeowner vs. Renter • Business Owner • Retention by First-Shopped Period • Churn • Cross-Shop • Average Ticket Buckets

AIML hedge funds, which utilize artificial intelligence or machine learning, performed better than other hedge funds in the long run. AIML hedge funds had the lowest average return during 2019, but higher returns than the other over a three-year and five-year perspective.

Success.ai’s Private Equity (PE) Funding Data provides reliable, verified access to the contact details of investment professionals, fund managers, analysts, and executives operating in the global private equity landscape. Drawn from over 170 million verified professional profiles, this dataset includes work emails, direct phone numbers, and LinkedIn profiles for key decision-makers in PE firms. Whether you’re seeking new investment opportunities, looking to pitch your services, or building strategic relationships, Success.ai delivers continuously updated and AI-validated data to ensure your outreach is both precise and effective.

Why Choose Success.ai’s Private Equity Professionals Data?

1. Comprehensive Contact Information

   • Access verified work emails, direct phone numbers, and social profiles for PE fund managers, analysts, partners, and principals.
   • AI-driven validation ensures 99% accuracy, reducing wasted efforts and enabling confident communication with industry leaders.

2. Global Reach Across Private Equity Markets

   • Includes profiles of professionals involved in leveraged buyouts, growth capital, venture investments, and secondary market deals.
   • Covers North America, Europe, Asia-Pacific, South America, and the Middle East, ensuring a global perspective on PE investments.

3. Continuously Updated Datasets

   • Real-time updates keep you informed about changes in roles, firm structures, and portfolio focus, helping you stay aligned with an ever-evolving investment environment.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and other international data privacy regulations, ensuring your outreach is both ethical and legally compliant.

Data Highlights:

• 170M+ Verified Professional Profiles: Includes private equity professionals, decision-makers, and influential players worldwide.
• 50M Work Emails: AI-validated for direct, accurate communication.
• 30M Company Profiles: Gain insights into private equity firms, their portfolio companies, investment stages, and sector focuses.
• 700M Global Professional Profiles: Enriched datasets supporting broad market analysis, strategic planning, and competitive assessments.

Key Features of the Dataset:

1. Investment Decision-Maker Profiles

   • Identify and connect with fund managers, dealmakers, and senior executives overseeing capital allocation, portfolio management, and exit strategies.
   • Engage with professionals who influence investment theses, valuation approaches, and cross-border deals.

2. Advanced Filters for Precision Targeting

   • Refine outreach by region, deal size, industry preference, fund type, or specific job functions within the PE firm.
   • Tailor campaigns to align with unique investment philosophies, market segments, and strategic focuses.

3. AI-Driven Enrichment

   • Profiles are enriched with actionable data, equipping you with insights to personalize messaging, highlight unique value propositions, and enhance engagement outcomes.

Strategic Use Cases:

1. Deal Origination and Pipeline Building

   • Reach out to PE fund managers and analysts to present investment opportunities, co-investment deals, or M&A prospects.
   • Identify partners receptive to new growth capital deployments, early-stage investments, or strategic acquisitions.

2. Advisory and Professional Services

   • Offer due diligence, valuation, legal, or consulting services directly to decision-makers at private equity firms.
   • Position your expertise to streamline deal execution, portfolio optimization, or exit planning.

3. Fundraising and Investor Relations

   • Connect with IR professionals, placement agents, and fund administrators to discuss fundraising targets, investor outreach strategies, or institutional capital requirements.
   • Engage with professionals managing limited partner relationships, capital calls, and reporting obligations.

4. Market Research and Competitive Intelligence

   • Utilize PE data for comprehensive market analysis, competitor benchmarking, and trend identification.
   • Understand investment patterns, portfolio performance, and sector preferences to refine your business strategies.

Why Choose Success.ai?

1. Best Price Guarantee

   • Secure premium-quality verified data at competitive prices, maximizing the ROI of your outreach and lead-generation efforts.

2. Seamless Integration

   • Incorporate verified contact data into your CRM or marketing automation platforms using APIs or downloadable formats for streamlined data management.

3. Data Accuracy with AI Validation

   • Rely on 99% accuracy to guide data-driven decisions, improve targeting, and enhance the effectiveness of your investment-related initiatives.

4. Customizable and Scalable Solutions

   • Adapt datasets to focus on particular geographies, deal sizes, or industry sectors, adjusting as your business needs evolve.

...

Funding for artificial intelligence companies in the United States has increased exponentially in recent years, growing from a little under 300 million U.S. dollars in 2011 to around 16.5 billion in 2019. Overall worldwide funding in AI startups amounted to approximately 26.6 billion U.S. dollars in the same year. Artificial intelligence refers to the creation of intelligent hardware or software able to replicate human behaviors such as learning and problem solving.

Machine learning applications most funded   

Companies focusing on machine learning applications are the most funded in the artificial intelligence (AI) market. Machine learning application companies raised 37 billion U.S. dollars in cumulative funding as of September 2019. Other well-funded AI categories include machine learning platforms as well as computer vision applications and platforms. Intel Capital is the leading AI investor with a total of 60 investments in AI companies as of April 2021. 500 Startups, NEA and Y Combinator also rank high in terms of AI investment deals.