This dataset provides an overview of government operations and stock positions, as well as several derived balances. The Statement of Government Operations shows revenue and expense, with their main components, the operating balance and net lending/net borrowing, as well as financing. The Balance sheet shows stock positions in assets and liabilities, with their main components, as well as net worth and net financial worth. In addition, data on gross debt and net debt are included.

For further details, please refer to Government Finance Statistics Manual 2014 (GFSM 2014)

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Table of Contents 1. Overview 2. World and Regional Tables 3. Country Tables 4. Annex I. Analytic Presentation of the Balance of Payments 5. Annex II. Standard Presentation of the Balance of Payments 6. Annex III. Standard Components of the International Investment Position 7. Annex IV. Reporting Currency 8. Annex V. Conceptual Framework of the Balance of Payments and International Investment Position 9. Annex VI. Classification and Standard Components of the Balance of Payments and International Investment Position Overview The electronic release of the Balance of Payments Statistics Yearbook (BOPSY), produced by the International Monetary Fund (IMF), contains balance of payments and international investment position (IIP) data in accordance with the sixth edition of the Balance of Payments and International Investment Position Manual (BPM6) published in 2009. Individual country data for all available periods along with world and regional aggregates for the period 2005-2021 are included in this release. The IMF is grateful for countries’ cooperation in providing comprehensive, timely, and regular 1 Volume 1 of the Yearbook, published in 1949, was based on the first edition of the IMF’s Balance of Payments Manual, issued in 1948; Volumes 2–12 were compiled pursuant to the second edition of the Manual, issued in 1950; Volumes 13–23 were based on the third edition of the Manual, issued in 1961; and Volumes 24– 29 were associated with that edition as well as the Balance of Payments Manual: Supplement to Third Edition, issued in 1973. Volumes 30–45 followed the guidance of the fourth edition of the data to the Fund for re-dissemination. These data support the IMF’s Statistics Department (STA) in its efforts to respond to the analytical and policy needs of the IMF, member countries, and the international community. The electronic release, available through the online database accessible at http://data.imf.org, contains a section on the World and Regional Tables, which presents 21 World and Regional Tables for major components of the balance of payments and IIP accounts. Individual country tables covering annual balance of payments and IIP data of individual countries, jurisdictions, and other reporting entities, as well as Balance of Payments and IIP metadata are also published through the online database.. The release of the Yearbook based on BPM61 was endorsed by the IMF’s Committee on Balance of Payments Statistics. The BPM6 provides updated international standards covering the methodologies for compiling, and the presentation of, balance of payments and IIP statistics. It incorporates clarifications and improvements reflecting significant developments and expansion in globalized international trade arrangements and financial markets that had been identified since the release of the fifth edition of the Balance of Payments Manual (BPM5) in 1993. Moreover, the linkages to and consistency with other macroeconomic statistics are maintained and enhanced through the parallel update of the OECD Benchmark Definition of Foreign Direct Investment and the System of National Accounts. Manual, published in 1977. Volumes 46–62 were presented in accordance with the standard components of the BPM5. However, the standard components changed with the publication of Financial Derivatives, a Supplement to the Fifth Edition (1993) of the Balance of Payments Manual, published in 2000 and amended in 2002. As noted, Volume 63 and subsequent volumes were presented based on BPM6. Beginning 2019, BOPSY is released in electronic format only. International Monetary Fund: Balance of Payments Statistics: Introductory Notes, as of November 2023 3 For many decades, the IMF has published data on a basis that is consistent across countries and across time periods. Such data consistency is required to perform cross-country data comparisons, track growth rates across time, and produce regional or global data aggregates. Data conversion work undertaken by IMF staff, in close consultation with IMF member countries, has made possible the presentation in the BPM6 format of data for the few economies that have not yet implemented BPM6. To assist users in understanding the impact of conversion to BPM6, as well as in understanding major methodological changes from BPM5 to BPM6, see FAQs on Conversion from BPM5 to BPM6 The methodologies, compiling practices, and data sources available through data.imf.org are based on information provided to the IMF by reporting countries. The descriptions are intended to enhance user understanding of the coverage, as well as the limitations, of individual country data. At the same time, they are useful in informing compilers of data sources and practices used by their counterparts in other countries.

This folder contains information and instructions to replicate results associated with Tuzcuoglu, K. (2024), Nonlinear Transmission of International Financial Stress, Economic Modelling.

Data and code for peer-reviewed article published in Economic Modelling. Paper published online June 14, 2024.

This data set is a subset of the "Records of foreign capital" (Registros de capitais estrangeiros", RCE) published by the Central Bank of Brazil (CBB) on their website.The data set consists of three data files and three corresponding metadata files. All files are in openly accessible .csv or .txt formats. See detailed outline below for data contained in each. Data files contain transaction-specific data such as unique identifier, currency, cancelled status and amount. Metadata files outline variables in the corresponding data file.RCE_Unclean_full_dataset.csv - all transactions published to the Central Bank website from the four main categories outlined belowMetadata_Unclean_full_dataset.csvRCE_Unclean_cancelled_dataset.csv - data extracted from the RCE_Unclean_full_dataset.csv where transactions were registered then cancelledMetadata_Unclean_cancelled_dataset.csvRCE_Clean_selection_dataset.csv - transaction data extracted from RCE_Unclean_full_dataset.csv and RCE_Unclean_cancelled_dataset.csv for the nine companies and criteria identified belowMetadata_Clean_selection_dataset.csvThe data include the period between October 2000 and July 2011. This is the only time span for the data provided by the Central Bank of Brazil at this stage. The records were published monthly by the Central Bank of Brazil as required by Art. 66 in Decree nº 55.762 of 17 February 1965, modified by Decree nº 4.842 of 17 September 2003. The records were published on the bank’s website starting October 2000, as per communique nº 011489 of 7 October 2003. This remained the case until August 2011, after which the amount of each transaction was no longer disclosed (and publication of these stopped altogether after October 2011). The disclosure of the records was suspended in order to review their legal and technical aspects, and ensure their suitability to the requirements of the rules governing the confidentiality of the information (Law nº 12.527 of 18 November 2011 and Decree nº 7724 of May 2012) (pers. comm. Central Bank of Brazil, 2016. Name of contact available upon request to Authors).The records track transfers of foreign capital made from abroad to companies domiciled in Brazil, with information on the foreign company (name and country) transferring the money, and on the company receiving the capital (name and federative unit). For the purpose of this study, we consider the four categories of foreign capital transactions which are published with their amount and currency in the Central Bank’s data, and which are all part of the “Register of financial transactions” (abbreviated RDE-ROF): loans, leasing, financed import and cash in advance (see below for a detailed description). Additional categories exist, such as foreign direct investment (RDE-IED) and External Investment in Portfolio (RDE-Portfólio), for which no amount is published and which are therefore not included.We used the data posted online as PDFs on the bank’s website, and created a script to extract the data automatically from these four categories into the RCE_Unclean_full_dataset.csv file. This data set has not been double-checked manually and may contain errors. We used a similar script to extract rows from the "cancelled transactions" sections of the PDFs into the RCE_Unclean_cancelled_dataset.csv file. This is useful to identify transactions that have been registered to the Central Bank but later cancelled. This data set has not been double-checked manually and may contain errors.From these raw data sets, we conducted the following selections and calculations in order to create the RCE_Clean_selection_dataset.csv file. This data set has been double-checked manually to secure that no errors have been made in the extraction process.We selected all transactions whose recipient company name corresponds to one of these nine companies, or to one of their known subsidiaries in Brazil, according to the list of subsidiaries recorded in the Orbis database, maintained by Bureau Van Dijk. Transactions are included if the recipient company name matches one of the following:- the current or former name of one of the nine companies in our sample (former names are identified using Orbis, Bloomberg’s company profiles or the company website);- the name of a known subsidiary of one of the nine companies, if and only if we find evidence (in Orbis, Bloomberg’s company profiles or on the company website) that this subsidiary was owned at some point during the period 2000-2011, and that it operated in a sector related to the soy or beef industry (including fertilizers and trading activities).For each transaction, we extracted the name of the company sending capital and when possible, attributed the transaction to the known ultimate owner.The name of the countries of origin sometimes comes with typos or different denominations: we harmonized them.A manual check of all the selected data unveiled that a few transactions (n=14), appear twice in the database while bearing the same unique identification number. According to the Central Bank of Brazil (pers. comm., November 2016), this is due to errors in their routine of data extraction. We therefore deleted duplicates in our database, keeping only the latest occurrence of each unique transaction. Six (6) transactions recorded with an amount of zero were also deleted. Two (2) transactions registered in August 2003 with incoherent currencies (Deutsche Mark and Dutch guilder, which were demonetised in early 2002) were also deleted.To secure that the import of data from PDF to the database did not contain any systematic errors, for instance due to mistakes in coding, data were checked in two ways. First, because the script identifies the end of the row in the PDF using the amount of the transaction, which can sometimes fail if the amount is not entered correctly, we went through the extracted raw data (2798 rows) and cleaned all rows whose end had not been correctly identified by the script. Next, we manually double-checked the 486 largest transactions representing 90% of the total amount of capital inflows, as well as 140 randomly selected additional rows representing 5% of the total rows, compared the extracted data to the original PDFs, and found no mistakes.Transfers recorded in the database have been made in different currencies, including US dollars, Euros, Japanese Yens, Brazilian Reais, and more. The conversion to US dollars of all amounts denominated in other currencies was done using the average monthly exchange rate as published by the International Monetary Fund (International Financial Statistics: Exchange rates, national currency per US dollar, period average). Due to the limited time period, we have not corrected for inflation but aggregated nominal amounts in USD over the period 2000-2011.The categories loans, cash in advance (anticipated payment for exports), financed import, and leasing/rental, are those used by the Central Bank of Brazil in their published data. They are denominated respectively: “Loans” (“emprestimos” in original source) - : includes all loans, either contracted directly with creditors or indirectly through the issuance of securities, brokered by foreign agents. “Anticipated payment for exports” (“pagamento/renovacao pagamento antecipado de exportacao” in original source): defined as a type of loan (used in trade finance)“Financed import” (“importacao financiada” in original source): comprises all import financing transactions either direct (contracted by the importer with a foreign bank or with a foreign supplier), or indirect (contracted by Brazilian banks with foreign banks on behalf of Brazilian importers). They must be declared to the Central Bank if their term of payment is superior to 360 days.“Leasing/rental” (“arrendamento mercantil, leasing e aluguel” in original source) : concerns all types of external leasing operations consented by a Brazilian entity to a foreign one. They must be declared if the term of payment is superior to 360 days.More information about the different categories can be found through the Central Bank online.(Research Data Support provided by Springer Nature)

Vietnam VN: Domestic Credit: to Private Sector: % of GDP data was reported at 130.673 % in 2017. This records an increase from the previous number of 123.815 % for 2016. Vietnam VN: Domestic Credit: to Private Sector: % of GDP data is updated yearly, averaging 60.467 % from Dec 1992 (Median) to 2017, with 25 observations. The data reached an all-time high of 130.673 % in 2017 and a record low of 13.657 % in 1992. Vietnam VN: Domestic Credit: to Private Sector: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Bank Loans. Domestic credit to private sector refers to financial resources provided to the private sector by financial corporations, such as through loans, purchases of nonequity securities, and trade credits and other accounts receivable, that establish a claim for repayment. For some countries these claims include credit to public enterprises. The financial corporations include monetary authorities and deposit money banks, as well as other financial corporations where data are available (including corporations that do not accept transferable deposits but do incur such liabilities as time and savings deposits). Examples of other financial corporations are finance and leasing companies, money lenders, insurance corporations, pension funds, and foreign exchange companies.; ; International Monetary Fund, International Financial Statistics and data files, and World Bank and OECD GDP estimates.; Weighted average;

Abstract

The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

Geographic coverage

National Coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

Research instrument

The English version of the questionnaire is provided for download.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

The global financial data services market is on a significant growth trajectory, driven by the increasing digitization of the financial industry and the escalating demand for data-driven insights for investment and risk management. This expansion is fueled by the growing complexity of global financial markets, stringent regulatory compliance requirements, and the proliferation of advanced technologies like AI and machine learning for predictive analytics. Key market players are focusing on providing real-time, accurate, and comprehensive data solutions to cater to a diverse clientele, including banks, asset management firms, and hedge funds. The Asia Pacific region is emerging as the fastest-growing market, presenting lucrative opportunities, while North America continues to hold the largest market share due to its mature financial infrastructure and high technology adoption rate.

Key strategic insights from our comprehensive analysis reveal:

The integration of Artificial Intelligence (AI) and Machine Learning (ML) is no longer a trend but a fundamental driver, enabling predictive analytics, algorithmic trading, and personalized financial advice, thereby creating significant value.
The Asia-Pacific region, led by China and India, is projected to witness the highest CAGR, driven by rapid economic growth, increasing foreign investment, and widespread digital transformation in its BFSI sector.
There is a surging demand for specialized data services, particularly in Environmental, Social, and Governance (ESG) criteria and alternative data (e.g., satellite imagery, social media sentiment), as investors seek a more holistic view for decision-making.

Global Market Overview & Dynamics of Financial Data Services Market Analysis The global financial data services market is experiencing robust growth, set to expand from $19,761.5 million in 2021 to an estimated $52,972.4 million by 2033, progressing at a compound annual growth rate (CAGR) of 8.564%. This growth is underpinned by the financial sector's digital revolution, where real-time, accurate data is crucial for maintaining a competitive edge, ensuring regulatory compliance, and managing complex risks. The increasing adoption of cloud computing and AI is further democratizing access to sophisticated analytical tools, broadening the market's reach. Global Financial Data Services Market Drivers

Increasing Regulatory Complexity and Compliance Demands: Stringent regulations like MiFID II, Dodd-Frank, and Basel III mandate greater transparency and robust reporting, compelling financial institutions to invest heavily in reliable data services to ensure compliance and manage risk effectively.
Growth of Algorithmic and High-Frequency Trading: The rising prevalence of automated trading strategies that rely on instantaneous access to vast amounts of market data to execute trades in microseconds is a primary driver for real-time data feed services.
Digital Transformation in the BFSI Sector: The broad shift towards digital platforms in banking, wealth management, and insurance necessitates sophisticated data services for everything from customer analytics and personalized services to fraud detection and operational efficiency.

Global Financial Data Services Market Trends

Adoption of AI and Machine Learning for Predictive Analytics: Financial firms are increasingly leveraging AI/ML to analyze market trends, forecast asset performance, and automate investment decisions, driving demand for high-quality, structured datasets.
Surge in Demand for ESG Data: A growing investor focus on sustainability and ethical investing has created a massive trend for specialized ESG (Environmental, Social, and Governance) data services to assess corporate performance beyond traditional financial metrics.
Rise of Cloud-Based Data Platforms: The shift towards cloud-based solutions offers financial institutions greater flexibility, scalability, and cost-efficiency in accessing and analyzing large datasets, moving away from legacy on-premise systems.

Global Financial Data Services Market Restraints

Data Security and Privacy Concerns: The high sensitivity of financial data makes it a prime target for cyberattacks. The risk of data breaches and the need to comply with data privacy regulations like GDPR pose significant challenges and operational costs.
High Cost of Premium Data Services: Subscriptions to premium, real-time financial data feeds and sophisticated...

Journal of Finance Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of Finance publishes leading research across all the major fields of financial research. It is the most widely cited academic journal on finance. Each issue of the journal reaches over 8,000 academics, finance professionals, libraries, government, and financial institutions around the world. Published six times a year, the journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics. Aims and Scope The Journal of Finance publishes leading research across all the major fields of financial research. It is one of the most widely cited academic journals on finance and one of the most widely cited journals in all of economics as well. Each issue of the journal reaches over 8,000 academics, finance professionals, libraries, government, and financial institutions around the world. Published six times a year, the journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics. Keywords finance, journal, American, association, AFA, financial, economics, theory, markets, international, exchange, derivatives, trading, structures, journal, article, periodical, analysis, research, modeling, macroeconomics, policy Society Information The American Finance Association (AFA) is the premier academic organization devoted to the study and promotion of knowledge about financial economics. The purpose of the Association is to provide for the mutual association of persons with an interest in finance to improve public understanding of financial problems, and to provide for the exchange of financial ideas through the distribution of a periodical and other media; to encourage the study of finance in colleges and universities; to conduct such other activities as may be appropriate for a non-profit, professional society in the field of finance. The AFA was planned at a meeting in December 1939 in Philadelphia. The Journal of Finance was first published in August 1946 when dues were $3 a year. Association membership has grown steadily over time. Today the AFA has over 8,000 members and dues are $40 a year. The AFA sponsors an annual meeting each January where the President speaks on a chosen topic and papers which cover the gamut of financial topics are presented. The current President of the Association is René Stulz of Ohio State University. David Pyle of the University of California, Berkeley serves as Executive Secretary and Treasurer. The Association has a board that rotates over time and assists in key decisions. Abstracting and Indexing Information ABI/INFORM Collection (ProQuest) Accounting, Tax & Banking Collection (ProQuest) Business Abstracts (EBSCO Publishing) Business ASAP (GALE Cengage) Business Premium Collection (ProQuest) CatchWord (Publishing Technology) Current Contents: Social & Behavioral Sciences (Clarivate Analytics) Current Index to Statistics (ASA/IMS) EBSCO Online (EBSCO Publishing) EconLit (AEA) Emerald Management Reviews (Emerald) InfoTrac (GALE Cengage) Journal Citation Reports/Social Science Edition (Clarivate Analytics) OmniFile Full Text Mega Edition (HW Wilson) Periodical Index Online (ProQuest) Proquest Business Collection (ProQuest) ProQuest Central (ProQuest) ProQuest Central K-321 ProQuest Politics Collection (ProQuest) ProQuest Sociology Collection (ProQuest) RePEc: Research Papers in Economics Research Library (ProQuest) Research Library Prep (ProQuest) Social Science Premium Collection (ProQuest) Social Sciences Citation Index (Clarivate Analytics) Journal of Finance Additional details - Scimago Country: United Kingdom H Index: 264 Subject Area and Category: Business, Management, and Accounting, Accounting, Economics, Econometrics and Finance, Economics and Econometrics, Finance Publication Type: Journals Coverage: 1946-ongoing

Browse LSEG's I/B/E/S Estimates, discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.

Financial overview and grant giving statistics of Legacy International Online High School

Snapshot img

Financial Service Application Market Size 2025-2029

The financial service application market size is forecast to increase by USD 69.8 billion, at a CAGR of 8.6% between 2024 and 2029.

The market is experiencing significant growth, driven by increasing government initiatives to digitalize the financial sector. This shift towards digitization is fueled by a growing recognition of the benefits it brings, including increased efficiency and accessibility. Software development and Network Security ensure the reliability and security of financial applications. However, this trend is not without challenges. One of the most pressing concerns is the rising awareness among customers about finance and digitization, which places heightened importance on the security and privacy of financial data. As a result, financial institutions must prioritize robust security measures to mitigate potential risks and maintain customer trust.
Additionally, privacy concerns continue to pose a challenge, with stringent regulations requiring strict adherence to data protection policies. Navigating these challenges will be crucial for companies seeking to capitalize on the opportunities presented by the digital transformation of the financial sector. By focusing on innovative solutions that address these concerns, organizations can differentiate themselves and position themselves for long-term success.

What will be the Size of the Financial Service Application Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, with technology playing a pivotal role in shaping the industry's dynamics. Machine learning algorithms are integrated into investment platforms for predictive analysis and algorithmic trading, enhancing the efficiency of financial transactions. Tax planning tools assist users in optimizing their tax liabilities, while user interfaces are designed to offer seamless experiences. Wealth management and estate planning applications provide comprehensive solutions for managing assets and legacy planning. Account management and risk management tools enable users to monitor and mitigate financial risks.

Savings accounts, interest rates, and digital wallets offer convenience and flexibility for managing personal finances. Payment gateways and processing systems facilitate secure transactions, while fraud detection and data analytics help prevent financial losses. Insurtech and insurance products leverage technology to streamline insurance processes, from customer onboarding to claims processing. Open banking and loan origination systems enable financial institutions to offer more personalized services. High-frequency trading and financial modeling tools cater to the needs of institutional investors. Retirement planning tools help individuals plan for their future, while blockchain technology ensures secure and transparent transactions. The continuous unfolding of market activities and evolving patterns underscores the importance of staying informed and adaptable in the ever-changing market.

How is this Financial Service Application Industry segmented?

The financial service application industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Large enterprises
  SMEs


Deployment

  On-premises
  Cloud-based


Application

  Banking
  Payment gateways
  Insurance
  Wealth management
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Switzerland
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By End-user Insights

The large enterprises segment is estimated to witness significant growth during the forecast period. The market is experiencing significant growth due to the increasing adoption of digital payments and online banking services. Companies in the banking, financial services, and insurance (BFSI), IT, and manufacturing sectors are major contributors to this trend, as they generate a large volume of transactions. The expansion of BFSI enterprises and the intensification of intraregional cross-border banking activity are also driving the demand for financial service applications. Modern vending machines equipped with contactless and card-based payments are another factor fueling market growth. Financial technology (fintech) innovations, such as fraud detection, data analytics, algorithmic trading, and API integration, are enhancing the functionality of financial service applications.

cloud computing, data security, and user experience (UX) are also critical factors influencing the market's evol

Financial overview and grant giving statistics of International Internet Chamber Of Commerce Inc

Journal of Finance Acceptance Rate - ResearchHelpDesk - The Journal of Finance publishes leading research across all the major fields of financial research. It is the most widely cited academic journal on finance. Each issue of the journal reaches over 8,000 academics, finance professionals, libraries, government, and financial institutions around the world. Published six times a year, the journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics. Aims and Scope The Journal of Finance publishes leading research across all the major fields of financial research. It is one of the most widely cited academic journals on finance and one of the most widely cited journals in all of economics as well. Each issue of the journal reaches over 8,000 academics, finance professionals, libraries, government, and financial institutions around the world. Published six times a year, the journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics. Keywords finance, journal, American, association, AFA, financial, economics, theory, markets, international, exchange, derivatives, trading, structures, journal, article, periodical, analysis, research, modeling, macroeconomics, policy Society Information The American Finance Association (AFA) is the premier academic organization devoted to the study and promotion of knowledge about financial economics. The purpose of the Association is to provide for the mutual association of persons with an interest in finance to improve public understanding of financial problems, and to provide for the exchange of financial ideas through the distribution of a periodical and other media; to encourage the study of finance in colleges and universities; to conduct such other activities as may be appropriate for a non-profit, professional society in the field of finance. The AFA was planned at a meeting in December 1939 in Philadelphia. The Journal of Finance was first published in August 1946 when dues were $3 a year. Association membership has grown steadily over time. Today the AFA has over 8,000 members and dues are $40 a year. The AFA sponsors an annual meeting each January where the President speaks on a chosen topic and papers which cover the gamut of financial topics are presented. The current President of the Association is René Stulz of Ohio State University. David Pyle of the University of California, Berkeley serves as Executive Secretary and Treasurer. The Association has a board that rotates over time and assists in key decisions. Abstracting and Indexing Information ABI/INFORM Collection (ProQuest) Accounting, Tax & Banking Collection (ProQuest) Business Abstracts (EBSCO Publishing) Business ASAP (GALE Cengage) Business Premium Collection (ProQuest) CatchWord (Publishing Technology) Current Contents: Social & Behavioral Sciences (Clarivate Analytics) Current Index to Statistics (ASA/IMS) EBSCO Online (EBSCO Publishing) EconLit (AEA) Emerald Management Reviews (Emerald) InfoTrac (GALE Cengage) Journal Citation Reports/Social Science Edition (Clarivate Analytics) OmniFile Full Text Mega Edition (HW Wilson) Periodical Index Online (ProQuest) Proquest Business Collection (ProQuest) ProQuest Central (ProQuest) ProQuest Central K-321 ProQuest Politics Collection (ProQuest) ProQuest Sociology Collection (ProQuest) RePEc: Research Papers in Economics Research Library (ProQuest) Research Library Prep (ProQuest) Social Science Premium Collection (ProQuest) Social Sciences Citation Index (Clarivate Analytics) Journal of Finance Additional details - Scimago Country: United Kingdom H Index: 264 Subject Area and Category: Business, Management, and Accounting, Accounting, Economics, Econometrics and Finance, Economics and Econometrics, Finance Publication Type: Journals Coverage: 1946-ongoing

Overview This dataset contains 5,000 meticulously generated banking transaction records from 2023 to 2024. It includes essential details such as transaction IDs, amounts, timestamps, payment methods, and customer demographics. Designed with realistic variability, it mimics real-world financial data to provide an authentic experience for financial analysis and machine learning applications.

Features A. Transaction Details: - Transaction_ID: Unique identifier for each transaction. - Transaction_Date: Date and time of the transaction. - Transaction_Amount: Monetary value of the transaction. - Transaction_Type: Type of transaction (Debit or Credit).

B. Customer Information: - Customer_Age: Age of the customer (18–70). - Customer_Gender: Gender of the customer (Male, Female, Others). - Customer_Income: Annual income of the customer. - Account_Balance: Account balance after the transaction.

C. Categorization: - Category: Categorized transactions into relevant sectors such as Food, Transport, Entertainment, Grocery, Electronics, and more.

D. Merchant and Payment Information: - Merchant_Name: The name of the merchant or vendor. - Payment_Method: Method of payment (Credit Card, Debit Card, Cash, Online Transfer, etc.).

E. Additional Details: - City: Location of the transaction (major US cities). - Fraud_Flag: Indicates whether the transaction is flagged as fraudulent. - Transaction_Status: Status of the transaction (Success, Failed, Pending). - Loyalty_Points_Earned: Rewards points earned from the transaction. - Discount_Applied: Boolean indicating if a discount was applied.

ESG debt instruments, including green bonds, social bonds, sustainability bonds, and sustainability-linked bonds, are fixed-income securities designed to sustain or improve the condition of the environment or society or governance practices. Green Bonds are fixed income instruments where the proceeds will be exclusively directed to finance or re-finance, in part or in full, new and/or existing green projects. Social bonds have use of proceeds that are dedicated to projects with positive social outcomes. Sustainability bonds have a mix of green and social use of proceeds. Sustainability linked bonds (SLB) are financial instruments where financial and structural characteristics are linked to achieving performance objectives that improve the condition of the environment or society. SLBs are not use-of proceed bonds. They typically include key performance indicators which are structurally connected to the issuer’s goal achievement. Sources: LSEG. Accessed on 2025-02-24; IMF staff calculations. Category: Climate Finance Data series:  The following data series are available by debt instruments: ESG Bond Issuances ESG Bond Outstanding ESG Bond Issuances by Type of Issuers ESG Bond Issuances by Country Cumulative ESG Bond Issuances by Type of Currency Cumulative Green Bond Issuances by Use of Proceeds Cumulative Social Bond Issuances by Use of Proceeds Cumulative Sustainability Bond Issuances by Use of Proceeds Sovereign Green Bond Issuances Metadata:  The source dataset is based on LSEG (formerly Refinitiv), which contain bond-by-bond issuances for Green Bonds, Social Bonds, Sustainability Bonds, and Sustainability-Linked Bonds starting from 2006 to 2024. Bonds by type encompass investment grade, high-yield, and not-rated bonds, commercial papers, certificates of deposit, and sukuks. By issuer type, bonds encompass government, corporate, agency, non-US munis, and other gov/supra bonds. Methodology:  The data are aggregated by country of incorporations, use of proceeds, type of currency and type of issuers (nonfinancial corporations, other financial corporations, banks, state owned entities, sovereign, state and local governments and international organizations). Sovereign green bonds are green bonds issued by central governments and central banks. Compilation of the indicator is based on the methodology used by London Stock Exchange Group, and divergences may be observed when compared to data from other providers.

F CNBC International is a leading global financial news and information services company, providing unparalleled insights and analysis to business stakeholders around the world. Founded in 2005, the company has established itself as a trusted authority in the realm of financial news, broadcasting, and online content.

With a focus on coverage of global markets, financial trends, and economic developments, F CNBC International offers a broad range of data and information on companies, industries, and markets worldwide. From stock prices and trading data to market research and economic indicators, the company's platform provides a comprehensive and easily accessible array of financial resources for professionals and individuals alike, offering unparalleled insight into the world of global finance.

Journal of Finance Abstract & Indexing - ResearchHelpDesk - The Journal of Finance publishes leading research across all the major fields of financial research. It is the most widely cited academic journal on finance. Each issue of the journal reaches over 8,000 academics, finance professionals, libraries, government, and financial institutions around the world. Published six times a year, the journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics. Aims and Scope The Journal of Finance publishes leading research across all the major fields of financial research. It is one of the most widely cited academic journals on finance and one of the most widely cited journals in all of economics as well. Each issue of the journal reaches over 8,000 academics, finance professionals, libraries, government, and financial institutions around the world. Published six times a year, the journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics. Keywords finance, journal, American, association, AFA, financial, economics, theory, markets, international, exchange, derivatives, trading, structures, journal, article, periodical, analysis, research, modeling, macroeconomics, policy Society Information The American Finance Association (AFA) is the premier academic organization devoted to the study and promotion of knowledge about financial economics. The purpose of the Association is to provide for the mutual association of persons with an interest in finance to improve public understanding of financial problems, and to provide for the exchange of financial ideas through the distribution of a periodical and other media; to encourage the study of finance in colleges and universities; to conduct such other activities as may be appropriate for a non-profit, professional society in the field of finance. The AFA was planned at a meeting in December 1939 in Philadelphia. The Journal of Finance was first published in August 1946 when dues were $3 a year. Association membership has grown steadily over time. Today the AFA has over 8,000 members and dues are $40 a year. The AFA sponsors an annual meeting each January where the President speaks on a chosen topic and papers which cover the gamut of financial topics are presented. The current President of the Association is René Stulz of Ohio State University. David Pyle of the University of California, Berkeley serves as Executive Secretary and Treasurer. The Association has a board that rotates over time and assists in key decisions. Abstracting and Indexing Information ABI/INFORM Collection (ProQuest) Accounting, Tax & Banking Collection (ProQuest) Business Abstracts (EBSCO Publishing) Business ASAP (GALE Cengage) Business Premium Collection (ProQuest) CatchWord (Publishing Technology) Current Contents: Social & Behavioral Sciences (Clarivate Analytics) Current Index to Statistics (ASA/IMS) EBSCO Online (EBSCO Publishing) EconLit (AEA) Emerald Management Reviews (Emerald) InfoTrac (GALE Cengage) Journal Citation Reports/Social Science Edition (Clarivate Analytics) OmniFile Full Text Mega Edition (HW Wilson) Periodical Index Online (ProQuest) Proquest Business Collection (ProQuest) ProQuest Central (ProQuest) ProQuest Central K-321 ProQuest Politics Collection (ProQuest) ProQuest Sociology Collection (ProQuest) RePEc: Research Papers in Economics Research Library (ProQuest) Research Library Prep (ProQuest) Social Science Premium Collection (ProQuest) Social Sciences Citation Index (Clarivate Analytics) Journal of Finance Additional details - Scimago Country: United Kingdom H Index: 264 Subject Area and Category: Business, Management, and Accounting, Accounting, Economics, Econometrics and Finance, Economics and Econometrics, Finance Publication Type: Journals Coverage: 1946-ongoing

Cameroon CM: Net Bilateral Aid Flows from Development Assistance Committee Donors: France data was reported at 230.130 USD mn in 2022. This records an increase from the previous number of 135.740 USD mn for 2021. Cameroon CM: Net Bilateral Aid Flows from Development Assistance Committee Donors: France data is updated yearly, averaging 94.650 USD mn from Dec 1964 (Median) to 2022, with 59 observations. The data reached an all-time high of 596.230 USD mn in 2007 and a record low of 9.600 USD mn in 1965. Cameroon CM: Net Bilateral Aid Flows from Development Assistance Committee Donors: France data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cameroon – Table CM.World Bank.WDI: Defense and Official Development Assistance. Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Lithuania, Luxembourg, The Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovienia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.;Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: https://data-explorer.oecd.org/.;Sum;

The United States recorded a capital and financial account surplus of 190139 USD Million in September of 2025. This dataset provides the latest reported value for - United States Net Treasury International Capital Flows - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 52 companies listed on the Bahamas International Securities Exchange (XBAA) in Bahamas. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Bahamas:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Bahamas:

Bahamas International Securities Exchange (BISX) Index: The BISX Index is the main stock market index of the Bahamas International Securities Exchange (BISX). It tracks the performance of the listed companies on the exchange, representing various sectors of the Bahamian economy.

Commonwealth Bank (CBL): Commonwealth Bank is one of the largest banks in the Bahamas, providing a range of financial services including banking, lending, and investment products. It is listed on the Bahamas International Securities Exchange (BISX).

Fidelity Bank (FBB): Fidelity Bank (Bahamas) Limited is a commercial bank offering a variety of banking and financial services to individuals and businesses in the Bahamas. Its shares are traded on the Bahamas International Securities Exchange (BISX).

Cable Bahamas (CAB): Cable Bahamas is a telecommunications and entertainment company that provides cable TV, internet, and other related services in the Bahamas. It is listed on the Bahamas International Securities Exchange (BISX).

Bahamas Telecommunications Company (BTC): The Bahamas Telecommunications Company is the national telecommunications provider in the Bahamas, offering services such as fixed-line and mobile telephony, internet, and data services. It is listed on the Bahamas International Securities Exchange (BISX).

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Bahamas, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Bahamas ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Bahamas?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Bahamas exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. Wh...