Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.

Key Features of Success.ai's Company Financial Data:

Global Coverage: Access data from over 70 million businesses worldwide, including public and private companies across all major industries and regions. Our datasets span 250+ countries, offering extensive reach for your financial analysis and market research.

Detailed Financial Profiles: Gain insights into company financials, including revenue, profit margins, funding rounds, and operational costs. Profiles are enriched with key contact details, including work emails, phone numbers, and physical addresses, ensuring direct access to decision-makers.

Industry-Specific Data: Tailored datasets for sectors such as financial services, manufacturing, technology, healthcare, and energy, among others. Each dataset is customized to meet the unique needs of industry professionals and analysts.

Real-Time Accuracy: With continuous updates powered by AI-driven validation, our financial data maintains a 99% accuracy rate, ensuring you have access to the most reliable and up-to-date information available.

Compliance and Security: All data is collected and processed in strict adherence to global compliance standards, including GDPR, ensuring ethical and lawful usage.

Why Choose Success.ai for Company Financial Data?

Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.

AI-Validated Accuracy: Our advanced AI algorithms meticulously verify every data point to ensure precision and reliability, helping you avoid costly errors in your financial decision-making.

Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.

Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.

Comprehensive Use Cases for Financial Data:

1. Strategic Financial Planning:

Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.

1. Mergers and Acquisitions (M&A):

Access key financial details and contact information to streamline your M&A processes. Identify potential acquisition targets or partners with verified profiles and financial data.

1. Investment Analysis:

Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.

1. Lead Generation and Sales:

Enhance your sales outreach by targeting CFOs, financial analysts, and other decision-makers with verified contact details. Utilize accurate email and phone data to increase conversion rates.

1. Market Research:

Understand market trends and financial benchmarks with our industry-specific datasets. Use the data for competitive analysis, benchmarking, and identifying market gaps.

APIs to Power Your Financial Strategies:

Enrichment API: Integrate real-time updates into your systems with our Enrichment API. Keep your financial data accurate and current to drive dynamic decision-making and maintain a competitive edge.

Lead Generation API: Supercharge your lead generation efforts with access to verified contact details for key financial decision-makers. Perfect for personalized outreach and targeted campaigns.

Tailored Solutions for Industry Professionals:

Financial Services Firms: Gain detailed insights into revenue streams, funding rounds, and operational costs for competitor analysis and client acquisition.

Corporate Finance Teams: Enhance decision-making with precise data on industry trends and benchmarks.

Consulting Firms: Deliver informed recommendations to clients with access to detailed financial datasets and key stakeholder profiles.

Investment Firms: Identify potential investment opportunities with verified data on financial performance and market positioning.

What Sets Success.ai Apart?

Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.

Ethical Practices: Our data collection and processing methods are fully comp...

Access in-depth profiles, hard-to-find details, and robust screening tools for private companies with exclusive private equity insights.

Our comprehensive and advanced database is completed with all the information you need, with up to >1million company financial records at your disposal. This allows you to easily perform company search on company profile and company directory, with maximised coverage in Thailand.

Our database also contains company profiles on private limited or limited companies globally, including information such as shareholders and financial accounts can be accessed instantly.

Discover verified Company Financial Data with Success.ai. Includes profiles of CFOs, financial analysts, and corporate treasurers with work emails and phone numbers. Continuously updated and AI-validated. Best price guaranteed.

Our comprehensive and advanced database is completed with all the information you need, with up to >1.5 million company financial records at your disposal. This allows you to easily perform company search on company profile and company directory, with 99% coverage in Malaysia.

Our database also contains company profiles on private limited or limited companies globally, including information such as shareholders and financial accounts can be accessed instantly.

View the credit condition and financial health of private companies with LSEG's StarMine Private Company SmartRatios Credit Risk Model (PCSRCR).

Graph and download economic data for Capital transfers paid, by private business sector: Financial corporations (W942RC1A027NBEA) from 1989 to 2023 about capital transfers, paid, finance companies, companies, finance, capital, sector, financial, business, private, GDP, and USA.

Private Company Valuation Market Outlook

The global market size for private company valuation is projected to grow from USD 2.3 billion in 2023 to USD 4.9 billion by 2032, reflecting a compound annual growth rate (CAGR) of 8.4% during the forecast period. This significant growth can be attributed to an increasing number of private equity deals and mergers and acquisitions (M&A) activity, which are driving the demand for accurate and reliable valuation services.

Several factors contribute to the robust growth of the private company valuation market. Firstly, the continuous rise in private equity investments and venture capital funding is generating a high demand for precise valuation services. Investors are keen on assessing the true worth of private companies before making substantial financial commitments. This trend is particularly pronounced in the technology and healthcare sectors, where innovative startups frequently attract significant investment. Moreover, valuation is crucial for determining the financial health and potential growth trajectories of these companies, thereby ensuring informed decision-making for investors.

Another significant growth driver is the increasing complexity of financial regulations and reporting standards across the globe. Compliance with these regulations necessitates meticulous and transparent valuation processes. Companies need to adhere to international financial reporting standards (IFRS) and generally accepted accounting principles (GAAP), which require comprehensive valuation reports. This regulatory complexity ensures a steady demand for valuation experts who can navigate these requirements and provide accurate appraisals.

Furthermore, the global trend towards digital transformation is reshaping the valuation landscape. Advanced technologies such as artificial intelligence (AI), machine learning, and big data analytics are being integrated into valuation methodologies, enhancing their accuracy and efficiency. These technologies enable the processing of vast amounts of financial data, thereby providing more precise valuations and streamlined reporting. Consequently, private companies are increasingly leveraging these technological advancements to gain a competitive edge in the market.

Regionally, North America dominates the private company valuation market, owing to its mature financial ecosystem and a high volume of M&A activities. However, the Asia Pacific region is expected to witness the fastest growth during the forecast period. This can be attributed to the rapid economic development in countries like China and India, which are experiencing a surge in startup activities and private investments. Additionally, the increasing adoption of digital technologies in the financial sector across the region is further propelling market growth.

Valuation Method Analysis

The private company valuation market can be segmented by valuation method into Discounted Cash Flow (DCF), Comparable Company Analysis, Precedent Transactions, Asset-Based Valuation, and others. Each of these methods has its unique advantages and applications, catering to different needs of valuation.

The Discounted Cash Flow (DCF) method is widely regarded as one of the most reliable valuation techniques, especially for companies with predictable cash flows. This method involves estimating the future cash flows of a company and discounting them to their present value using a discount rate. The DCF method is particularly useful for valuing companies in the technology and healthcare sectors, where future growth potential is a critical consideration. By assessing the present value of expected future earnings, this method provides a comprehensive view of a company's intrinsic value.

Comparable Company Analysis, also known as market multiples, involves comparing a private company to similar publicly traded companies. This method is popular due to its simplicity and reliance on observable market data. By analyzing the valuation multiples of comparable companies, such as the price-to-earnings (P/E) ratio or enterprise value-to-EBITDA (EV/EBITDA) ratio, valuators can derive reasonable estimates for the subject company. This method is particularly effective in industries with a large number of publicly traded peers, such as consumer goods and financial services.

Precedent Transactions involve analyzing the valuation multiples of similar companies that have been acquired or merged in the past. This method provides a historical perspective on how companies in the same industry h

China Outward Investment: Non Financial: accumulated: Private Company data was reported at 151.573 USD bn in 2021. This records an increase from the previous number of 145.568 USD bn for 2020. China Outward Investment: Non Financial: accumulated: Private Company data is updated yearly, averaging 11.955 USD bn from Dec 2006 (Median) to 2021, with 15 observations. The data reached an all-time high of 151.573 USD bn in 2021 and a record low of 750.255 USD mn in 2006. China Outward Investment: Non Financial: accumulated: Private Company data remains active status in CEIC and is reported by Ministry of Commerce. The data is categorized under China Premium Database’s Investment – Table CN.OB: Outward Direct Investment: Non Financial.

This dataset simulates detailed financial statement records for public and private companies, enriched with fraud risk indicators and audit outcomes. It is designed for developing and benchmarking machine learning models to detect financial statement fraud, with comprehensive fields for financial metrics, suspicious activity counts, and risk scoring. The dataset is ideal for forensic analysis, risk assessment, and audit research in the finance industry.

Abstract

The performance evaluation undertaken included administrative financial data from MFIs and MSMEs which received grants under the Benin Compact as well as survey data and qualitative data from grant recipients. Only MFIs and MSMEs which received grants were included in the data collection. Questionnaires recorded information about the MFIs' and MSMEs' past activities, their interaction with the project, and the agencies it supported, and their overall impressions of the project.

Based on the surveys and financial analysis, it appears that the grants, especially the training, equipment, and the external supervision have played a major role in allowing many MFIs to maintain or expand their operations and maintain or improve performance in spite of unfavorable management/governance factors, external shocks, or an unfavorable policy environment, which are beyond the scope of this evaluation.

The financial analysis of the grantee MSMEs reveals a split between the enterprises continuing to operate with various degree of profitability (about 50% of the enterprises) and those that have either closed or are heavily dependent on further subsidies for continued operations. Among the grantees were five private enterprises, 23 associations, and 14 cooperatives. Of the five private enterprises, four are doing relatively well and one intends to start operations in late 2016.

As an overall conclusion, it can be said that the support to the MFI sector had a strategic impact and made a major contribution to strengthening the MFI sector while contributing to the revival and growth of the sector after the 2010 crisis. For the MFI sector, therefore, the project had a positive systemic impact. However, the same cannot be said of the support to MSMEs.

Geographic coverage

National coverage.

Analysis unit

Enterprise and MFI

Universe

MFIs and MSMEs which received either a S1, S2 or S3 grant through the Benin Compact.

Kind of data

Administrative records data [adm]

Research instrument

Qualitative questionnaires were administered to MFIs and MSMEs that participated in the data collection. For MFIs, these included various information on the MFI, including its starting year for activities, its registration and authorization status, and details regarding its branches. The questionnaire also recorded information on the support received from MCA, audits performed by MCA, the use of any equipment received and the perceived impact of the support received. The questionnaire also included modules on the MFI's interactions with ANSSFD and the services of the CEI.

For MSMEs, the questionnaire recorded various information on the MSME, including its activity areas, its number of employees, and the company's legal status. The questionnaire also recorded information on the support received from MCA, including equipment, and the perceptions of this support. The questionnaire recorded the MSMEs perceptions of the impact of the project on their capacity, market access, and access to micro- and project finance.

Cleaning operations

The questionnaires' data were entered by the evaluation team in Benin and shared via secure server with the evaluation team at NORC in the United States. The NORC team reviewed these questionnaires and collected further information or clarifications, as needed, from the evaluation team in Benin.

Response rate

Twenty-one of 42 MSMEs (50%) shared complete financial data from 2009-2015. For MFIs, 32 institutions were contacted for data, which includes the 23 grantees and their branches. From these, 23 (71%) shared complete financial data from 2009-2015.

Non-financial data was collected from 41 of 42 MSMEs (97%) and from 30 of the 32 MFIs (93%) approached.

Qualitative data was collected from 43 MSMEs (100%) and from 32 MFIs (100%). Some MSMEs applied for a grant as a consortium. When the head of the consortium was not found, the evaluation team collected this qualitative data from the two MSMEs which comprised the consortium, resulting in qualitative data being collected from 43 MSMEs.

All MFIs were interviewed (23 of 23--i.e. 100%) and all but one MSME was interviewed (41 of 42--i.e. 97%).

Explore LSEG's Private Equity Deals Data, including data and insight regarding a wide range of global private equity activities.

The Global Private Equity Market is Segmented by Fund Type (Buyout and Growth, Venture Capital, Mezzanine, and More), Sector (Technology, Healthcare, Real Estate, Financial Services, Industrials, Telecom, and More), Investments (Large Cap, Upper-Middle Market, and More), and Region (Europe, North America, South America, Asia-Pacific, and Middle East and Africa). The Market Forecasts are Provided in Terms of Value (USD).

The research data in this article comes from the data of Chinese A-share listed companies from 2000 to 2023; The annual reports of relevant companies are obtained from the official websites of the Shenzhen and Shanghai Stock Exchanges; The relevant data of listed companies comes from the CSMAR database of Guotai An. At the same time, this article conducts a 1% truncation process on non ratio continuous variables to reduce the impact of outliers. (1) Due to the lack of mandatory disclosure of carbon emission data by the Chinese government, there is currently a lack of micro level data on corporate carbon emissions. This study adopted the method of Chapple et al. (2013) to indirectly measure the carbon dioxide emissions of enterprises. Due to the lack of 23 years of carbon emission data, this study borrowed the ARIMA-BP prediction method from Hu Jianbo (2013) and Zhao SL et al. (2024) to fill in the predictions. (2) The degree of digital transformation of listed companies (Digital) The measurement methods for digital transformation of companies are relatively mature, and the measurement method adopts text analysis. This article first constructs numbers Keyword table for transformation; Then use Python software to match the vocabulary with the text of the annual report of the listed company, and use Jieba's method The module can calculate the frequency of relevant keywords appearing in the annual report documents of listed companies; Finally, add 1 to the frequency of the word and perform logarithmic processing Obtain indicators for enterprise digital transformation. Please refer to Wu Fei's (2021) approach (Managing the World) for specific details. (3) Control variables. This study includes enterprise level indicators as control variables: property rights nature of enterprises (SOE), with state-owned enterprises set to 0 and private enterprises set to 0 1) For operating enterprises, the board size (logarithm of the number of board members), the logarithm of the age of the enterprise (age), and the assets and liabilities Rate (lev), return on equity (roe), operating cash flow (CF), sales growth rate (growth), net profit growth rate (gprofit) Proportion of tangible assets (tangibi), proportion of independent directors (indep), proportion of the largest shareholder's shareholding (top 1) The dual role of chairman and general manager, and the nature of property rights (SOE). This study was supported by the Key Support Project for College Students' Innovation and Entrepreneurship in Hunan Province - Research on the Factors and Mechanisms of Digital Transformation of Construction Enterprises in the Digital Economy (S202411532001)

United States Private Sector Payroll: sa: Industry: Financial Activities data was reported at 8,555.812 Person th in Jun 2018. This records an increase from the previous number of 8,548.632 Person th for May 2018. United States Private Sector Payroll: sa: Industry: Financial Activities data is updated monthly, averaging 8,080.515 Person th from Mar 2001 (Median) to Jun 2018, with 208 observations. The data reached an all-time high of 8,555.812 Person th in Jun 2018 and a record low of 7,681.000 Person th in Mar 2011. United States Private Sector Payroll: sa: Industry: Financial Activities data remains active status in CEIC and is reported by Automatic Data Processing Inc. The data is categorized under Global Database’s USA – Table US.G045: ADP National Employment Report: New Methodology.

Snapshot img

Private and Public Cloud Market in the Financial Services Industry Size 2024-2028

The private and public cloud market in the financial services industry size is forecast to increase by USD 106.43 billion, at a CAGR of 19% between 2023 and 2028. The market is driven by the increasing demand for virtually unlimited storage and big data processing capabilities.

Major Market Trends & Insights

APAC dominated the market and accounted for a 39% share in 2022.
The market is expected to grow significantly in North America region as well over the forecast period.
Based on the Service Type, the SaaS segment led the market and was valued at USD 35.04 billion of the global revenue in 2022.
Based on the Deployment, the public cloud segment accounted for the largest market revenue share in 2022.

Market Size & Forecast

Market Opportunities: USD 90.04 Billion
Future Opportunities: USD 106.43 Billion
CAGR (2023-2028): 19%
APAC: Largest market in 2022

The trend is particularly prominent in the financial sector, where managing vast amounts of data is essential for risk assessment, fraud detection, and customer service. However, the adoption of cloud solutions in financial services is not without challenges. Data security and privacy remain major concerns, as sensitive financial information must be protected from cyber threats and unauthorized access. The development of OpenStack, an open-source cloud computing platform, offers potential solutions to these issues through enhanced security features and greater control over data.

What will be the Size of the Private and Public Cloud Market in the Financial Services Industry during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
Request Free Sample

Application performance monitoring, serverless computing platforms, and disaster recovery solutions are essential components of modern IT infrastructure. Software-defined networking and high availability clusters ensure optimal network performance and business continuity. Capacity planning tools and service level agreements help manage workloads and ensure consistent service delivery. Data loss prevention, cloud cost optimization, and regulatory compliance clouds are crucial for maintaining security and regulatory adherence. Financial data analytics, API security gateways, and container orchestration technology facilitate efficient data processing and streamlined operations. Payment processing platforms, automated compliance checks, and IT infrastructure optimization contribute to enhanced productivity and cost savings. The IaaS segment is the second largest segment of the service type and was valued at USD 20.87 billion in 2022.

Risk management systems, database replication systems, data governance frameworks, blockchain technology finance, financial data encryption, and financial transaction processing are integral to secure and efficient financial operations. Network security firewalls, virtual machine migration, public cloud scalability, and cloud security compliance are essential for maintaining a robust and secure IT environment. Microservices architecture and multi-cloud strategies enable flexibility and agility, while network security firewalls and virtual machine migration ensure seamless integration and migration between cloud environments. The ongoing unfolding of market activities underscores the continuous evolution of cloud technology in the financial services industry.

Financial institutions must navigate the complexities of implementing and managing these systems effectively to mitigate risks and ensure regulatory compliance. As companies in the financial services industry explore the benefits of cloud solutions, they must carefully consider both opportunities and challenges to optimize their IT infrastructure and maintain a competitive edge. By focusing on robust security measures and effective implementation strategies, financial institutions can capitalize on the potential of cloud technologies to drive innovation and growth.

How is this Private and Public Cloud in the Financial Services Industry Industry segmented?

The private and public cloud in the financial services industry industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Service Type

  SaaS
  IaaS
  PaaS


Deployment

  Public cloud
  Private cloud


Solution

  Financial forecasting
  Financial reporting & analysis
  Security
  Governance, Risk & Compliance
  Others


Application

  Revenue management
  Wealth management
  Account management
  Customer relationship management
  Asset management
  Others


Geography

  North America

    US
    Canada


  Europ

Finland - Private sector debt: debt securities: Non-financial corporations was 13.00 % of GDP in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Finland - Private sector debt: debt securities: Non-financial corporations - last updated from the EUROSTAT on July of 2025. Historically, Finland - Private sector debt: debt securities: Non-financial corporations reached a record high of 18.20 % of GDP in December of 2014 and a record low of 5.90 % of GDP in December of 1996.

Key information about US Credit to Private Non-Financial Sector

• US Credit to Private Non-Financial Sector was reported at 41,870.562 USD bn in Sep 2024
• This records an increase from the previous number of 41,536.266 USD bn for Jun 2024
• United States Credit to Private Non-Financial Sector data is updated quarterly, averaging 4,502.229 USD bn from Dec 1945 to Sep 2024, with 316 observations
• The data reached an all-time high of 41,870.562 USD bn in Sep 2024 and a record low of 85.382 USD bn in Dec 1945
• United States Credit to Private Non-Financial Sector data remains active status in CEIC and is reported by Bank for International Settlements
• The data is categorized under World Trend Plus’s Association: Banking Sector – Table RC.BIS.CNFS: F2 Credit from All Sector to Private Non-Financial Sector (PNFS): Market Value: USD

United States - Capital transfers paid, by private business sector: Financial corporations was 0.00000 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Capital transfers paid, by private business sector: Financial corporations reached a record high of 78.18800 in January of 2017 and a record low of 0.00000 in January of 1990. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Capital transfers paid, by private business sector: Financial corporations - last updated from the United States Federal Reserve on August of 2025.

Slovenia - Private sector credit flow: debt securities: Non-financial corporations was -0.10 % of GDP in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Slovenia - Private sector credit flow: debt securities: Non-financial corporations - last updated from the EUROSTAT on September of 2025. Historically, Slovenia - Private sector credit flow: debt securities: Non-financial corporations reached a record high of 1.00 % of GDP in December of 2009 and a record low of -0.60 % of GDP in December of 2016.