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.

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.

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 ---

AI investment is forecast to continue growing following a massive spike in 2021. Investment levels in AI nearly doubled between 2020 and 2021, with global private AI investment reaching 93.5 billion U.S. dollars in 2021.

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 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%.

In the first quarter of 2023, the total artificial intelligence (AI) startup funding worldwide had slumped to a low not seen since early 2018, dropping to 5.4 billion U.S. dollars. This is a correction from the incredible levels of startup funding in 2021 and 2022 following the Covid-19 pandemic. As a broader economic crisis looms in 2023 the funding for less reliable and forward looking projects like startups shrinks. AI Funding Over the past decade or so, the global startup funding of artificial intelligence has exponentially grown from 670 million U.S. dollars in 2011 to 36 billion U.S. dollars in 2020. Given what we know about the first and second quarter of 2022 for AI’s startup funding, it appears that 2022 as a whole will see a slowdown and correction in AI startup funding. The more recent top funded artificial intelligence startups in the United States are that of UiPath, Nuro, and Indigo Ag to name a few. Many of these startups are robotic process automation (RPA) companies that are situated in a growing market. UiPath UiPath is an AI startup to watch that specializes in robotic process automation (RPA) with the purpose of accelerating human achievement as its technique helps to take over repetitive and routine data entry and basic processing tasks. The startup recently launched its initial public offering (IPO) at a valuation relatively close to what it received from venture capital. UiPath is considered the second most valuable unicorn startup worldwide at 35 billion U.S. dollars and has accomplished the designation of the most popular robotic process automation (RPA) product vendor across Global 2000 enterprises.

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...

The Investor Series: Opportunities in the AI-based Drug Discovery Market, report provides detailed information on the AI-based Drug Discovery Market, along with a focus on drug discovery

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.

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.

...

The global fund management software market is experiencing robust growth, driven by increasing demand for efficient portfolio management, regulatory compliance, and advanced analytical capabilities. The market size in 2025 is estimated at $5 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting both large and small fund managers. Furthermore, increasing regulatory scrutiny and the need for robust risk management systems are pushing market expansion. The integration of artificial intelligence (AI) and machine learning (ML) into fund management software is enhancing decision-making processes and optimizing investment strategies. Growth is also spurred by the rising need for personalized client portals, allowing for improved client communication and enhanced transparency. The market is segmented by software version (PC and Mobile) and application (Personal and Commercial), with the commercial segment dominating due to the higher volume of transactions and need for sophisticated reporting. Key players in the market such as Totem, Profile Software, and Temenos Multifonds are continuously innovating and expanding their product offerings to cater to the evolving needs of fund managers. The market's regional distribution reflects the global distribution of financial institutions. North America and Europe currently hold significant market shares, driven by the presence of established financial hubs and a mature regulatory landscape. However, the Asia-Pacific region is projected to witness substantial growth in the coming years, fueled by rapid economic development and increasing investments in fintech. While the market faces challenges such as high implementation costs and the need for specialized expertise, the ongoing technological advancements and increasing demand for efficiency are expected to offset these restraints, leading to sustained market expansion throughout the forecast period. The continued development of innovative solutions that address specific fund management needs will be a key driver of future growth.

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.

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.

Success.ai’s Private Company Data Solutions offer businesses access to over 28 million verified company profiles, delivering detailed insights into private company data across multiple industries. Our solution includes firmographic data and business location data for companies of all sizes, from large enterprises to small businesses. Whether you're seeking small business contact data or company funding data, Success.ai’s company data solutions empower businesses with the accuracy and depth they need to drive B2B sales, marketing, and research initiatives.

At Success.ai, we offer tailored B2B datasets to meet specific business requirements. With our white-glove service, you’ll receive curated datasets customized to fit your needs, without the hassle of managing data platforms yourself. Our solution is GDPR-compliant, AI-validated with a 99% accuracy rate, and offers the best price guarantee on the market.

Why choose Success.ai?

• Best Price Guarantee: Our pricing beats any competitor, ensuring you get the best deal.
• Global Reach: 28M verified company profiles spanning 195 countries, providing coverage across industries.
• AI-Validated Accuracy: 99% accuracy rate, ensuring high-quality, actionable data.
• Real-Time Updates: Data is continuously updated to ensure you’re working with the freshest insights.
• Ethically Sourced & Compliant: All data is GDPR-compliant and ethically sourced from trusted partners.
• Comprehensive Data: Over 15 key data points per company, including firmographic data, funding history, company size, and technologies used.
• Tailored Service: Custom datasets are delivered directly to you, eliminating the need for platform navigation.

Our database includes comprehensive insights into company structures, employee counts, key technologies, and company funding data. Whether you’re targeting companies by business location or looking for detailed firmographic data, Success.ai’s datasets ensure you have all the data you need to drive your strategy.

Comprehensive data points:

Company Name LinkedIn URL Company Domain Company Description Business Location: Full details down to the city, state, and country Company Industry Employee Count Technologies Used Funding Information: Total funding and the latest funding dates

Maximize your sales potential by targeting decision-makers and building targeted account lists using Success.ai’s B2B contact data and company profiles. Our datasets are ideal for account-based marketing (ABM), investment research, market analysis, and CRM enrichment. Success.ai’s company data provides sales and marketing teams with the actionable insights they need to scale their efforts efficiently.

Key Use Cases:

• Targeted Lead Generation: Build precise lead lists by filtering company data by industry, size, or location.
• Account-Based Marketing (ABM): Use detailed firmographic data to focus marketing efforts on high-value accounts.
• Investment Research: Analyze company growth trends and funding history to identify high-potential investments.
• Market Research: Gain insights into industry trends, competitor activity, and market positioning for strategic planning.
• CRM Enrichment: Keep your CRM updated with verified company data, ensuring streamlined workflows.

With Success.ai, you’ll benefit from our best price guarantee, industry-leading accuracy, and white-glove service. We specialize in private company data, small business contact data, and business location data, providing comprehensive solutions for B2B marketing, sales, and research teams. Whether you need firmographic data or insights on company funding, our real-time datasets will help you stay ahead of the competition.

Get started with Success.ai today and take advantage of our price match guarantee, ensuring you receive the best possible deal on high-quality company data. Contact us to receive your custom dataset and transform your business with real-time insights.

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.