The Economic Indicator Service (EIS) aims to deliver economic content to financial institutions on both buy and sell-side and service providers. This new service currently covers 34,351 recurring macro-economic indicators from 135 countries ( as of December 16, 2019 ) such as GDP data, unemployment releases, PMI numbers etc.

Economic Indicator Service gathers the major economic events from a variety of regions and countries around the globe and provides an Economic Events Data feed and Economic Calendar service to our clients. This service includes all previous historic data on economic indicators that are currently available on the database.

Depending on availability, information regarding economic indicators, including the details of the issuing agency as well as historical data series can be made accessible for the client. Key information about EIS: • Cloud-based service for Live Calendar – delivered via HTML/JavaScript application formats, which can then be embedded onto any website using iFrames • Alternatives methods available – such as API and JSON feed for the economic calendar that can be integrated into the company’s system • Live data – updated 24/5, immediately after the data has been released • Historical data – includes a feed of all previous economic indicators available We are currently adding additional indicators/countries from Africa as well as expanding our coverage of Indicators in G20. The calendar includes the following. • Recurring & Non-recurring indicators covering 136 countries across 21 regions. • Indicators showing high, medium, and low impact data. • Indicators showing actual, previous, and forecast data. • Indicators can be filtered across 16 subtypes. • News generation for selected high-impact data. • Indicator description and historical data up to the latest eight historical points with a chart.

This Dataset comes from the R Package wbstats. The World Bank[https://www.worldbank.org/] is a tremendous source of global socio-economic data; spanning several decades and dozens of topics, it has the potential to shed light on numerous global issues. To help provide access to this rich source of information, The World Bank themselves, provide a well structured RESTful API. While this API is very useful for integration into web services and other high-level applications, it becomes quickly overwhelming for researchers who have neither the time nor the expertise to develop software to interface with the API. This leaves the researcher to rely on manual bulk downloads of spreadsheets of the data they are interested in. This too is can quickly become overwhelming, as the work is manual, time consuming, and not easily reproducible. The goal of the wbstats R-package is to provide a bridge between these alternatives and allow researchers to focus on their research questions and not the question of accessing the data. The wbstats R-package allows researchers to quickly search and download the data of their particular interest in a programmatic and reproducible fashion; this facilitates a seamless integration into their workflow and allows analysis to be quickly rerun on different areas of interest and with realtime access to the latest available data.

World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates. Copied from https://databank.worldbank.org/source/world-development-indicators.

Highlighted features of the wbstats R-package: * Uses version 2 of the World Bank API that provides access to more indicators and metadata than the previous API version * Access to all annual, quarterly, and monthly data available in the API * Support for searching and downloading data in multiple languages * Returns data in either wide (default) or long format * Support for Most Recent Value queries * Support for grep style searching for data descriptions and names * Ability to download data not only by country, but by aggregates as well, such as High Income or South Asia

More information can be found at https://www.rdocumentation.org/packages/wbstats/versions/1.0.4

Note for Version 1. Version 1 published January 2023. Its primary focus is on the featured indicator of climate change. Other versions planned will cover other featured indicators such as economy, education, energy, environment, debt, gender, health, infrastructure, poverty, science and technology.

Financial Data Exchange API Integration Market Outlook

According to our latest research, the Financial Data Exchange API Integration market size reached USD 3.42 billion globally in 2024. The market is experiencing a robust expansion, registering a CAGR of 23.1% from 2025 to 2033. By the end of 2033, the market is forecasted to attain a value of USD 25.09 billion. This remarkable growth trajectory is propelled by the increasing adoption of open banking, regulatory mandates for data transparency, and the growing demand for seamless connectivity between financial institutions, fintech firms, and third-party service providers.

One of the most significant growth factors driving the Financial Data Exchange API Integration market is the widespread adoption of open banking initiatives across the globe. Regulatory frameworks such as PSD2 in Europe, the Consumer Data Right in Australia, and similar policies in North America are compelling banks and financial institutions to provide secure, standardized API access to customer data. This not only enhances customer experience by enabling personalized financial services but also fosters innovation by allowing third-party developers to build novel financial products. As a result, the market is witnessing a surge in demand for robust, scalable, and secure API integration solutions that can handle complex data exchange requirements while ensuring compliance with evolving regulatory standards.

Another pivotal driver fueling the market’s expansion is the rapid digital transformation within the financial services sector. Financial institutions are increasingly leveraging APIs to enhance operational efficiency, streamline workflows, and deliver real-time services such as instant payments, automated wealth management, and digital lending. The proliferation of fintech startups and the entry of technology giants into the financial domain have further intensified the need for seamless data connectivity and interoperability. This has led to a significant uptick in investments in API integration platforms and services, as organizations seek to modernize legacy systems, reduce integration complexities, and accelerate time-to-market for new digital offerings.

The growing emphasis on customer-centricity and data-driven decision-making is also contributing to the robust growth of the Financial Data Exchange API Integration market. Financial institutions are increasingly harnessing APIs to aggregate and analyze vast volumes of customer data from multiple sources, enabling them to deliver hyper-personalized products, improve risk assessment, and enhance fraud detection capabilities. The integration of advanced technologies such as artificial intelligence, machine learning, and blockchain with financial data exchange APIs is opening up new avenues for innovation, further amplifying the market’s growth potential. Moreover, the shift towards cloud-based API integration solutions is enabling organizations to achieve greater scalability, flexibility, and cost-efficiency, thereby accelerating the adoption of API-driven architectures across the financial ecosystem.

From a regional perspective, North America currently dominates the Financial Data Exchange API Integration market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The presence of a highly developed financial services infrastructure, early adoption of open banking regulations, and a vibrant fintech ecosystem are key factors contributing to North America’s leadership. However, the Asia Pacific region is expected to exhibit the fastest growth during the forecast period, driven by rapid digitalization, increasing smartphone penetration, and supportive government policies promoting financial inclusion. Europe remains a significant market due to its stringent regulatory environment and proactive stance on data privacy and security. Meanwhile, Latin America and the Middle East & Africa are gradually emerging as promising markets, fueled by rising investments in fintech and digital banking initiatives.

Component Analysis

The Component segment of the Financial Data Exchange API Integration market is categorized into Software, Services, and Platforms. Software solutions form the backbone of API integration, providing the essential tools and frameworks required to establish secure, scalable, and co

Access Market Research Intellect's Financial Data Apis Market Report for insights on a market worth USD 3.5 billion in 2024, expanding to USD 10.2 billion by 2033, driven by a CAGR of 15.9%.Learn about growth opportunities, disruptive technologies, and leading market participants.

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. It provides data on economic output, income, expenditures, employment, production and price indexes. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This dataset represents a snapshot of the FRED catalog, captured on 2025-03-24.

What is FRED? As per the FRED website,

Short for Federal Reserve Economic Data, FRED is an online database consisting of hundreds of thousands of economic data time series from scores of national, international, public, and private sources. FRED, created and maintained by the Research Department at the Federal Reserve Bank of St. Louis, goes far beyond simply providing data: It combines data with a powerful mix of tools that help the user understand, interact with, display, and disseminate the data. In essence, FRED helps users tell their data stories. The purpose of this article is to guide the potential (or current) FRED user through the various aspects and tools of the database.

The FRED database is an abolute gold mine of economic data time series. Thousands of such series are published on the FRED website, organized by category and avialable for viewing and downloading. In fact, a number of these economic datasets have been uploaded to kaggle. With in the current notebook, however, we are not interested in the individual time series; rather, we are focused on catalog itself.

The FRED API has been used for gaining access to the catalog. The catalog consists of two files

• categories.csv - the heirarchy of categories used for organizing the time series
• series.csv - the list of avialable time series themselves

A given category is identified by a category_id. And, in a similar fashion, a given series is identified by a series_id. In a given category, one may find both a group of series and a set of sub-categories. As such every series record contains a category_id to identify the immediate category under which it is found category record contains a parent_id to indicate where in the category heirarchy it resides

The ERS content and data APIs (including our pre-made widgets for embedding charts) are currently out of service while we redesign our site. Check back here for updates--we'll keep you informed as to the progress. Contact us at webadmin@ers.usda.gov with questions. The Data APIs provide programmatic access to select data sets.

United Kingdom Total Economy (TE): Uses: Allocations of Primary Income Account (API data was reported at 673,594.000 GBP mn in Mar 2018. This records a decrease from the previous number of 673,744.000 GBP mn for Dec 2017. United Kingdom Total Economy (TE): Uses: Allocations of Primary Income Account (API data is updated quarterly, averaging 420,984.000 GBP mn from Mar 1987 (Median) to Mar 2018, with 125 observations. The data reached an all-time high of 673,744.000 GBP mn in Dec 2017 and a record low of 168,250.000 GBP mn in Mar 1987. United Kingdom Total Economy (TE): Uses: Allocations of Primary Income Account (API data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s UK – Table UK.AB023: ESA10: Resources and Uses: Total Economy: Primary Income.

API Heating Oil in the United States increased to -0.43 BBL/1Million in April 12 from -0.47 BBL/1Million in the previous week. This dataset provides - United States API Heating Oil- actual values, historical data, forecast, chart, statistics, economic calendar and news.

United Kingdom TE: RC: sa: API: Tax data was reported at 67,652.000 GBP mn in Jun 2018. This records an increase from the previous number of 65,579.000 GBP mn for Mar 2018. United Kingdom TE: RC: sa: API: Tax data is updated quarterly, averaging 35,954.000 GBP mn from Mar 1987 (Median) to Jun 2018, with 126 observations. The data reached an all-time high of 67,652.000 GBP mn in Jun 2018 and a record low of 14,182.000 GBP mn in Jun 1987. United Kingdom TE: RC: sa: API: Tax data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.AB023: ESA10: Resources and Uses: Total Economy: Primary Income.

Finnhub is the ultimate stock api in the market, providing real-time and historical price for global stocks with Rest API and websocket. We also support a tons of other financial data like stock fundamentals, analyst estimates, fundamental data and more. Download the file to access balance sheet of Amazon.

FinTech Climate Data API Market Outlook

According to our latest research, the FinTech Climate Data API market size reached USD 1.23 billion globally in 2024, demonstrating robust momentum as financial institutions increasingly integrate climate data into their operations. The market is projected to grow at a CAGR of 22.7% from 2025 to 2033, reaching a forecasted value of USD 9.94 billion by 2033. This rapid expansion is driven by mounting regulatory pressures, rising investor demand for climate transparency, and the urgent need for financial entities to assess climate-related risks and opportunities.

A primary growth driver for the FinTech Climate Data API market is the global shift towards sustainable finance and the intensifying focus on environmental, social, and governance (ESG) criteria. Financial institutions are under increasing pressure from regulators and investors to quantify and disclose climate-related risks embedded in their portfolios. This has led to a surge in demand for sophisticated climate data APIs that can deliver real-time, granular, and actionable insights. These APIs enable banks, asset managers, and insurance companies to integrate climate risk analytics directly into their existing risk assessment, investment analysis, and compliance workflows. As a result, the market is witnessing accelerated adoption, particularly among organizations aiming to align with international frameworks such as the Task Force on Climate-related Financial Disclosures (TCFD) and the European Union’s Sustainable Finance Disclosure Regulation (SFDR).

Another significant factor propelling the FinTech Climate Data API market is the rapid digital transformation within the financial services sector. The proliferation of cloud computing, artificial intelligence, and big data analytics has enabled the development of advanced climate data solutions that are scalable, interoperable, and easily integrated via API infrastructure. Financial technology (FinTech) companies are leveraging these capabilities to offer innovative services such as climate-adjusted portfolio management, carbon accounting, and scenario analysis. This technological evolution is lowering barriers to entry for smaller financial institutions and fintech startups, broadening the market’s user base and fostering a competitive ecosystem. Moreover, the growing collaboration between climate data providers and financial software vendors is catalyzing the creation of end-to-end solutions tailored to specific use cases across banking, asset management, and insurance.

The increasing frequency and severity of climate-related events, such as floods, wildfires, and hurricanes, have heightened awareness of the financial risks associated with climate change. This has compelled financial institutions to seek more accurate and timely data to model potential impacts on asset values, loan portfolios, and insurance liabilities. The FinTech Climate Data API market is responding by offering APIs that aggregate and normalize data from diverse sources, including satellite imagery, meteorological data, and corporate emissions disclosures. By facilitating comprehensive risk modeling and scenario analysis, these APIs are becoming indispensable tools for financial decision-makers. The trend is particularly pronounced in developed markets, where regulatory frameworks and investor expectations are driving the integration of climate data into mainstream financial analysis.

From a regional perspective, North America and Europe currently dominate the FinTech Climate Data API market, accounting for the largest share of global revenues. This leadership is attributed to the presence of major financial hubs, stringent regulatory requirements, and a high level of technological maturity. However, the Asia Pacific region is emerging as a key growth engine, supported by rapid fintech adoption, expanding financial markets, and increasing government initiatives to promote sustainable finance. Latin America and the Middle East & Africa, while still nascent, are expected to offer significant opportunities as awareness of climate risk grows and digital infrastructure improves. The regional landscape is thus characterized by a dynamic interplay of regulatory, technological, and market-driven factors shaping the adoption of climate data APIs.

Permutable AI’s Global Macro Sentiment API provides aggregated sentiment data for global macroeconomic topics, including inflation, GDP, monetary policy, fiscal policy, geopolitics, and natural disasters. With support for Python, R, and Java client libraries, plus webhook integration, the API allows developers and analysts to retrieve structured insights from news sources within custom date ranges. Parameters include start and end dates (30-day lookback), filtering by sources, and strict real-time extraction options. Data outputs include sentiment scores, topic classifications, and aggregated publication timestamps—ideal for market insights, trading strategies, and research applications. Full API reference documentation is available at copilot-api.permutable.ai/redoc .

Context

The dataset was created to predict market recession as inspired by assignment notebook in an online course, Python and Machine Learning for Asset Management by Edhec Business School, on Coursera. However, I aimed at doing this exercise for Indian economy but due to lack of monthly data for most indicators, I used FRED database similarly used in the course.

Content

The time period chosen is 1996-2020 according to most data available.

Acknowledgements

1. Python and Machine Learning for Asset Management by EDHEC Business School, www.coursera.org for recession period data formed according to NBER. 2.FRED, fred.stloiusfed.org for macro-economic indicator data
2. Business cycle dating, www.nber.org
3. Yahoo Finance for stock market data
4. Macrotrends.net for PE ratio
5. quandl.com for snp dividend yield

Inspiration

This dataset is inspired by the assignment notebook in the online course mentioned to predict market recession for portfolio management.

API Crude Imports in the United States increased to 0.05 BBL/1Million in February 23 from 0.02 BBL/1Million in the previous week. This dataset provides - United States Api Crude Imports- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Table of INEBase Economic indicators by Autonomous Communities and Cities. Autonomous Cities and Communities. Surveys on Water Supply and Sewerage

Financial Data Exchange API Integration Market Outlook

According to our latest research, the global Financial Data Exchange API Integration market size reached USD 3.84 billion in 2024, underscoring the sector’s robust expansion. The market is projected to grow at a CAGR of 17.2% from 2025 to 2033, with the market size expected to reach USD 15.36 billion by 2033. This surge is attributed to the rapid digital transformation in the financial sector, increasing adoption of open banking, and the growing need for seamless, secure, and real-time data sharing among financial institutions and third-party providers.

One of the key drivers fueling the growth of the Financial Data Exchange API Integration market is the widespread adoption of open banking initiatives worldwide. Regulatory frameworks such as PSD2 in Europe and similar mandates in other regions are compelling banks and financial institutions to open their data via secure APIs, fostering innovation and competition. This regulatory push has accelerated the need for robust API integration platforms that can securely manage complex data exchanges between banks, fintechs, and other financial entities. Furthermore, consumer demand for personalized, real-time financial services is pushing organizations to integrate APIs that enable instant access to account information, payment initiation, and financial analytics, thus driving market expansion.

Another significant growth factor is the proliferation of fintech startups and digital-first financial service providers. These companies rely heavily on API integrations to connect with traditional financial institutions, aggregate customer data, and deliver innovative solutions such as mobile banking, robo-advisory, and payment gateways. The competitive landscape is encouraging established banks and insurance providers to modernize their IT infrastructure and adopt API-centric architectures. As a result, the demand for scalable, secure, and compliant API integration solutions is rising, further propelling the market forward. Additionally, the COVID-19 pandemic has accelerated digital adoption, making seamless data exchange a necessity for remote operations and digital customer engagement.

The increasing focus on customer experience and operational efficiency is also acting as a catalyst for market growth. Financial institutions are leveraging API integrations to automate workflows, reduce manual processing, and provide customers with unified, omnichannel experiences. The integration of APIs with advanced technologies like artificial intelligence, blockchain, and machine learning is enabling real-time fraud detection, credit scoring, and personalized financial recommendations. These technological advancements are not only enhancing service delivery but also creating new revenue streams for market participants, thereby contributing to the overall growth of the Financial Data Exchange API Integration market.

From a regional perspective, North America continues to dominate the market, accounting for the largest share in 2024 due to the early adoption of digital banking, a mature fintech ecosystem, and favorable regulatory environments. Europe follows closely, driven by strong regulatory mandates and a collaborative approach between traditional banks and fintechs. The Asia Pacific region is witnessing the fastest growth, fueled by a rapidly expanding digital economy, increasing smartphone penetration, and supportive government policies promoting financial inclusion. Latin America and the Middle East & Africa are also experiencing steady growth, albeit at a slower pace, as financial institutions in these regions accelerate their digital transformation journeys.

Component Analysis

The Component segment of the Financial Data Exchange API Integration market is primarily divided into Software and Services. The Software component encompasses API management platforms, integration middleware, and security solutions that

United Kingdom PF: Uses: API: PI: Rent data was reported at 0.000 GBP mn in Jun 2018. This stayed constant from the previous number of 0.000 GBP mn for Mar 2018. United Kingdom PF: Uses: API: PI: Rent data is updated quarterly, averaging 0.000 GBP mn from Mar 1987 (Median) to Jun 2018, with 126 observations. United Kingdom PF: Uses: API: PI: Rent data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.AB031: ESA10: Resources and Uses: Public Non Financial Corporations: Primary Income.

View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.

API Crude Oil Stock Change in the United States decreased to -2.48 BBL/1Million in November 28 from -1.90 BBL/1Million in the previous week. This dataset provides - United States API Crude Oil Stock Change- actual values, historical data, forecast, chart, statistics, economic calendar and news.