Financial Access and Usage

Global Comparative Ratios Across 189 Jurisdictions

By International Monetary Fund [source]

About this dataset

This dataset provides an unprecedented opportunity to explore global financial access and usage trends from 2004-2016 from 189 of the world's reporting jurisdictions—which cover over 99 percent of the total adult population. With 152 time series and 47 indicator ratios, this Financial Access Survey gives insight into ways that access to and usage of financial services differ by households vs small/medium enterprises, life vs non-life insurance, deposits & microfinance institutions as well as credit unions & financial cooperatives. Utilizing this data, we can gain a better understanding of how policies or shifts in the global economy may influence or relate to access or utilization of services in certain regions while having comparable cross-economy comparisons. The IMF Monetary and Financial Statistics Manual Compilation Guide is utilized for all methodologies used in accumulating these datasets, while all data is available “as-is” with no guarantee provided either express or implied. Are you looking for ways to implement insightful macroeconomic analyses? Download FAS 2004–2016 now!

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How to use the dataset

The Financial Access Survey provides global supply-side data on access to and usage of financial services by households and firms for 189 reporting jurisdictions, covering 99 percent of the world’s adult population. With a robust selection of time series in this dataset, users can make meaningful insights into trends over time or across countries concerning various indicators related to access and usage of financial services. To help users navigate this large dataset, the following guide explains how to use the data most effectively.

Understanding The Dataset Columns

The columns in the dataset provide information about each indicator such as country name, indicator name, code for that indicator, its attribute (i.e., rate/ratio), when data is available for that particular indicator. Once you have identified an interesting measure/indicator whether it be credit union density or life insurance penetration rate measure in a given country during a certain year period then you can look up those numbers from the rows provided in this dataset .

Understanding The Different Years Available & Comparing Numbers Over Time

It is useful for users to compare different indicators over time by looking at specific years within this dataset which will allow us to see if rates are increasing or decreasing worldwide patterns across these trends among different countries based on these various measures listed provided in this survey such as mortgage lending rate or ratio GDP per capita etc that have been collected . We can therefore make use of our knowledge off economic changes that have occurred over time within certain parts of world , no matter if they are longer term economic effects due increases certain capabilities within a geographical area or shorter term changes due taxation laws by governments etc driving some people either towards using or away from using certain kinds financial products .

#### Comparing Between Countries

This datasets allows us direct comparisons between different countries with regards how many people are currently making use particular types off finances services , we certainly be able analyse current international relationships between services providers as well customers where ever concerned about particular attributes mentioned above whether being deposit interest rates small business credits terms tenders so forth . Knowing more about related dynamics helps build better user experiences with providers who understand needs risks impacts generating larger customer bases globally which often beneficial both parties involved exchange relationship so not forget always keep cross border motif whenever eye process from afar !

Research Ideas

• Comparing the access to and usage of financial services in different countries to better inform research policy decisions.
• Analyzing trends in financial access and usage by jurisdiction over time, to identify areas needing improvement in order to promote financial inclusion and stability.
• Cross-referencing FAS data with macroeconomic indicators such as GDP information to measure the potential impact of changes in level of access on economic growth or other metrics specific to a country or region of interest

Acknowledgements

If you use this dataset in yo...

Techsalerator’s Business Funding Data for Liberia

Techsalerator’s Business Funding Data for Liberia provides a detailed and insightful collection of information essential for businesses, investors, and financial analysts. This dataset delivers an in-depth analysis of funding activities across various sectors in Liberia, capturing and categorizing data related to funding rounds, investment sources, and financial milestones.

For access to the full dataset, contact us at info@techsalerator.com or visit Techsalerator Contact Us.

Techsalerator’s Business Funding Data for Liberia

Techsalerator’s Business Funding Data for Liberia offers a comprehensive overview of critical information for businesses, investors, and financial analysts. This dataset provides a thorough examination of funding activities across diverse sectors in Liberia, detailing data related to funding rounds, investment sources, and key financial milestones.

Top 5 Key Data Fields

1. Company Name: Identifies the company receiving funding. This information helps investors spot potential opportunities and allows analysts to track funding trends within specific industries.

2. Funding Amount: Displays the total amount of funding a company has received. Understanding these amounts provides insights into the financial health and growth potential of businesses and the scale of investment activities.

3. Funding Round: Indicates the stage of funding, such as seed, Series A, Series B, or later stages. This helps investors gauge a business’s maturity and growth trajectory.

4. Investor Name: Provides details about the investors or investment firms involved. Knowing the investors helps assess the credibility of the funding source and their strategic interests.

5. Investment Date: Records when the funding was completed. The timing of investments can reflect market trends, investor confidence, and potential impacts on a company’s future.

Top 5 Funding Trends in Liberia

1. Technology and Startups: Significant investments are being made in technology startups, including fintech, e-commerce, and digital solutions. These investments are crucial for driving innovation and digital growth in Liberia.

2. Renewable Energy: With increasing emphasis on sustainability, funding is directed towards renewable energy projects like solar and wind, aiming to reduce reliance on traditional energy sources and promote environmental sustainability.

3. Healthcare and Biotechnology: Increased funding is flowing into healthcare infrastructure, biotechnology, and health tech to address the healthcare needs of the population and support medical research and innovation.

4. Agriculture and Food Security: Funding is being allocated to modernize agricultural practices, enhance food security, and support agritech solutions that improve productivity and sustainability in the sector.

5. Education and Skill Development: Investments are directed towards educational initiatives and vocational training programs aimed at improving literacy rates, enhancing skills, and creating employment opportunities.

Top 5 Companies with Notable Funding Data in Liberia

1. Liberia Telecommunications Corporation: A leading provider of telecommunications services, it has received substantial funding to enhance infrastructure and expand its service offerings.

2. Gold Mines Inc.: A major player in the mining sector, particularly gold, this company has secured significant investment to support exploration and production activities.

3. Liberia Bank of Commerce: As a key financial institution, it has attracted notable funding to expand its services and improve financial inclusion across the country.

4. Liberia Health Group: This health organization has garnered substantial investment to improve healthcare delivery and expand medical services.

5. AgriLiberia: A key player in the agriculture sector, AgriLiberia has received significant funding to support modern farming techniques and boost food security.

Accessing Techsalerator’s Business Funding Data

To obtain Techsalerator’s Business Funding Data for Liberia, contact info@techsalerator.com with your specific needs. Techsalerator will provide a customized quote based on the required data fields and records, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

• Company Name
• Funding Amount
• Funding Round
• Investor Name
• Investment Date
• Funding Type (Equity, Debt, Grants, etc.)
• Sector Focus
• Deal Structure
• Investment Stage
• Contact Information

For detailed insights into funding activities and financial trends in Liberia, Techsalerator’s dataset is an invaluable resource for investors, business analysts, and financial professionals seeking informed, strategic decisions.

Abstract

Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector - the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies.

The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.

Geographic coverage

National Coverage.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above. The sample is nationally representative.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2011 calendar year, covering more than 150,000 adults in 148 economies and representing about 97 percent of the world's population. Since 2005, Gallup has surveyed adults annually around the world, using a uniform methodology and randomly selected, nationally representative samples. The second round of Global Findex indicators was collected in 2014 and is forthcoming in 2015. The set of indicators will be collected again in 2017.

Surveys were conducted face-to-face in economies where landline telephone penetration is less than 80 percent, or where face-to-face interviewing is customary. The first stage of sampling is the identification of primary sampling units, consisting of clusters of households. The primary sampling units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid.

Surveys were conducted by telephone in economies where landline telephone penetration is over 80 percent. The telephone surveys were conducted using random digit dialing or a nationally representative list of phone numbers. In selected countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to teach a person in each household, spread over different days and times of year.

The sample size in Latvia was 1,006 individuals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup, Inc. also provided valuable input. The questionnaire was piloted in over 20 countries using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on insurance, mobile payments, and loan purposes were asked only in developing economies. The indicators on awareness and use of microfinance insitutions (MFIs) are not included in the public dataset. However, adults who report saving at an MFI are considered to have an account; this is reflected in the composite account indicator.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country- and indicator-specific standard errors, refer to the Annex and Country Table in Demirguc-Kunt, Asli and L. Klapper. 2012. "Measuring Financial Inclusion: The Global Findex." Policy Research Working Paper 6025, World Bank, Washington, D.C.

Techsalerator’s Business Funding Data for Finland

Techsalerator’s Business Funding Data for Finland provides a comprehensive and insightful overview of crucial information for businesses, investors, and financial analysts. This dataset offers an in-depth analysis of the funding activities of companies across various sectors in Finland, capturing and categorizing data related to their funding rounds, investment sources, and financial milestones.

If you need the full dataset, reach out to us at info@techsalerator.com or https://www.techsalerator.com/contact-us.

Techsalerator’s Business Funding Data for Finland

Techsalerator’s Business Funding Data for Finland presents a detailed and insightful overview of essential information for businesses, investors, and financial analysts. This dataset delivers an in-depth examination of funding activities across various sectors in Finland, detailing data related to funding rounds, investment sources, and key financial milestones.

Top 5 Key Data Fields

1. Company Name: Identifies the company receiving funding. This information helps investors spot potential opportunities and allows analysts to track funding trends within specific industries.

2. Funding Amount: Shows the total amount of funding a company has received. Understanding these amounts provides insights into the financial health and growth potential of businesses and the scale of investment activities.

3. Funding Round: Indicates the stage of funding, such as seed, Series A, Series B, or later stages. This helps investors assess a business’s maturity and growth trajectory.

4. Investor Name: Provides details about the investors or investment firms involved. Knowing the investors helps gauge the credibility of the funding source and their strategic interests.

5. Investment Date: Records when the funding was completed. The timing of investments can reflect market trends, investor confidence, and potential impacts on a company’s future.

Top 5 Funding Trends in Finland

1. Technology and Innovation: Finland's technology sector is seeing significant investments, particularly in areas such as artificial intelligence, cybersecurity, and fintech. These investments drive innovation and enhance Finland’s position as a tech hub.

2. Clean Energy and Sustainability: Investments are flowing into clean energy projects, including wind, solar, and bioenergy. These initiatives support Finland's commitment to sustainability and reducing its carbon footprint.

3. Healthcare and Biotech: Increased funding is directed towards healthcare infrastructure, biotechnology research, and health tech innovations, aiming to improve medical services and drive advancements in healthcare.

4. Education and Edtech: Funding is being allocated to educational initiatives and edtech startups focused on enhancing learning experiences, digital education tools, and expanding access to quality education.

5. Smart Cities and Infrastructure: Investments in smart city projects and infrastructure development are growing, with a focus on urban planning, digital infrastructure, and improving city living standards.

Top 5 Companies with Notable Funding Data in Finland

1. Supercell: Known for its successful mobile games, Supercell has attracted substantial funding to expand its game development and international market presence.

2. Rovio Entertainment: The company behind the Angry Birds franchise has received notable investment to develop new games and expand its digital entertainment offerings.

3. Wärtsilä: A global leader in smart technologies and complete lifecycle solutions for the marine and energy markets, Wärtsilä has secured funding for innovations in energy efficiency and marine technology.

4. KONE: Specializing in elevators and escalators, KONE has garnered significant investment to enhance its technology and expand its global reach.

5. Valmet: A provider of technologies and services for the pulp, paper, and energy industries, Valmet has received funding to drive advancements in industrial processes and sustainability initiatives.

Accessing Techsalerator’s Business Funding Data

To obtain Techsalerator’s Business Funding Data for Finland, contact info@techsalerator.com with your specific needs. Techsalerator will provide a customized quote based on the required data fields and records, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

• Company Name
• Funding Amount
• Funding Round
• Investor Name
• Investment Date
• Funding Type (Equity, Debt, Grants, etc.)
• Sector Focus
• Deal Structure
• Investment Stage
• Contact Information

For detailed insights into funding activities and financial trends in Finland, Techsalerator’s dataset is an invaluable resource for investors, business analysts, and financial professionals seeking informed, strategic decisions.

Abstract

Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector - the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies.

The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.

Geographic coverage

National Coverage.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above. The sample is nationally representative.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2011 calendar year, covering more than 150,000 adults in 148 economies and representing about 97 percent of the world's population. Since 2005, Gallup has surveyed adults annually around the world, using a uniform methodology and randomly selected, nationally representative samples. The second round of Global Findex indicators was collected in 2014 and is forthcoming in 2015. The set of indicators will be collected again in 2017.

Surveys were conducted face-to-face in economies where landline telephone penetration is less than 80 percent, or where face-to-face interviewing is customary. The first stage of sampling is the identification of primary sampling units, consisting of clusters of households. The primary sampling units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid.

Surveys were conducted by telephone in economies where landline telephone penetration is over 80 percent. The telephone surveys were conducted using random digit dialing or a nationally representative list of phone numbers. In selected countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to teach a person in each household, spread over different days and times of year.

The sample size in Kazakhstan was 1,000 individuals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup, Inc. also provided valuable input. The questionnaire was piloted in over 20 countries using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on insurance, mobile payments, and loan purposes were asked only in developing economies. The indicators on awareness and use of microfinance insitutions (MFIs) are not included in the public dataset. However, adults who report saving at an MFI are considered to have an account; this is reflected in the composite account indicator.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country- and indicator-specific standard errors, refer to the Annex and Country Table in Demirguc-Kunt, Asli and L. Klapper. 2012. "Measuring Financial Inclusion: The Global Findex." Policy Research Working Paper 6025, World Bank, Washington, D.C.

Abstract

Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector - the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies.

The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.

Geographic coverage

National Coverage.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2011 calendar year, covering more than 150,000 adults in 148 economies and representing about 97 percent of the world's population. Since 2005, Gallup has surveyed adults annually around the world, using a uniform methodology and randomly selected, nationally representative samples. The second round of Global Findex indicators was collected in 2014 and is forthcoming in 2015. The set of indicators will be collected again in 2017.

Surveys were conducted face-to-face in economies where landline telephone penetration is less than 80 percent, or where face-to-face interviewing is customary. The first stage of sampling is the identification of primary sampling units, consisting of clusters of households. The primary sampling units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid.

Surveys were conducted by telephone in economies where landline telephone penetration is over 80 percent. The telephone surveys were conducted using random digit dialing or a nationally representative list of phone numbers. In selected countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to teach a person in each household, spread over different days and times of year.

The sample size in Afghanistan was 1,000 individuals. Gender-matched sampling was used during the final stage of selection.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup, Inc. also provided valuable input. The questionnaire was piloted in over 20 countries using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on insurance, mobile payments, and loan purposes were asked only in developing economies. The indicators on awareness and use of microfinance insitutions (MFIs) are not included in the public dataset. However, adults who report saving at an MFI are considered to have an account; this is reflected in the composite account indicator.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country- and indicator-specific standard errors, refer to the Annex and Country Table in Demirguc-Kunt, Asli and L. Klapper. 2012. "Measuring Financial Inclusion: The Global Findex." Policy Research Working Paper 6025, World Bank, Washington, D.C.

The John H. Chafee Foster Care Program for Successful Transition to Adulthood (the Chafee program) provides funding to support youth/ young adults in or formerly in foster care in their transition to adulthood. The program is funded through formula grants awarded to child welfare agencies in States (including the District of Columbia, Puerto Rico and the U.S. Virgin Islands) and participating Tribes. The program is funded at $143 million a year.

Chafee funds are used to assist youth/ young adults in a wide variety of areas designed to support a successful transition to adulthood. Activities and programs include, but are not limited to, help with education, employment, financial management, housing, emotional support and assured connections to caring adults. Specific services and supports are determined by the child welfare agency, vary by State, locality and agency, and are often based on the individual needs of the young person. Many State or local agencies contract with private organizations to deliver services to young people.

Eligibility for the program, as outlined in federal law, includes:

States and Tribes may have additional requirements for eligibility. State and Tribal agencies may elect to serve young adults up to age 23 only if the agencies also offers foster care to young people up to age 21. The following states have opted to provide Chafee services to young people up to age 23: Colorado, Connecticut, Delaware, District of Columbia, Florida, Hawaii, Idaho, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nebraska, New Mexico, New York, New Hampshire, North Dakota, Oregon, Pennsylvania, Puerto Rico, Tennessee, Utah, Vermont, Virginia, Washington, West Virginia, and Wisconsin.

The Chafee program has an additional appropriation of approximately $43 million annually for the Educational and Training Vouchers (ETV) Program. The ETV program provides financial resources to meet the post-secondary education and training needs of young adults who have experienced foster care after age 14. The program provides formula grants to States and participating Tribes to help young people pay for post-secondary educational and training. Under federal program requirements, agencies may award a voucher of up to $5,000 per year per young person to cover the unmet needs of the student’s cost of attendance at a post-secondary institution. The program can provide assistance to young people up to age 26, but an individual may receive a voucher for no more than a total of 5 years.

States receiving Chafee funding are required to submit data to the National Youth in Transition Database (NYTD). NYTD data are used to learn more about services provided to and outcomes experienced by youth transitioning out of foster care. For more information on NYTD, visit the Children's Bureau NYTD webpage.

If you or someone you know may be eligible for Chafee services and/or the ETV program, please contact your local child welfare agency or state program manager.

Metadata-only record linking to the original dataset. Open original dataset below.

The Paris Agreement’s nationally driven structure puts the spotlight on financing strategies at the national level. The role of national funding vehicles in mobilizing climate finance, however, has not received extensive attention. This paper remedies this gap by introducing a novel dataset of national climate funds established in developing countries. The database creates an inventory of national financing vehicles and tracks their major attributes, including scope, legal form, and the host, among others. We show that 39 countries have established national climate funds. These funds seek to access and mobilize finance from various sources, domestic and international. Most of these funds have broad mandates to tackle climate change, while a smaller share has a more targeted, sectoral focus. Funding sources vary from taxes to international aid. The funds offer a limited range of financial instruments, primarily awarding grants. The funds also differ in how integrated they are with overarching climate plans and strategies. We also find that most developing countries use existing budget lines to target finance towards climate change objectives. Only five countries track public expenditure on the basis of dedicated budget codes. This paper contributes to the literature by providing an empirical basis to pursue questions regarding the role and effectiveness of national climate funds. For policymakers, the limited range of instruments at the disposal of many of these national climate funds also suggests a need to ensure that the national climate funds have the design features they need to support the implementation of national policy goals. Key policy insightsSystematic data on public climate finance are scarce. Most governments do not use climate change codes to track their expenditures related to climate change. Policymakers should adopt practices that will help instil transparency in public expenditure on climate change.Policymakers have to revisit the design features of national climate funds such as legal form and areas of operation as the wider operating context changes.Funds accredited with multilateral climate funds are underutilized by fund contributors. The Green Climate Fund’s direct access modality offers one major avenue to foster synergies between national climate funds and multilateral climate funds.Policymakers have the opportunity to harvest lessons from existing funds and calibrate climate policies accordingly, especially as countries contemplate setting revenue-generating carbon prices. Systematic data on public climate finance are scarce. Most governments do not use climate change codes to track their expenditures related to climate change. Policymakers should adopt practices that will help instil transparency in public expenditure on climate change. Policymakers have to revisit the design features of national climate funds such as legal form and areas of operation as the wider operating context changes. Funds accredited with multilateral climate funds are underutilized by fund contributors. The Green Climate Fund’s direct access modality offers one major avenue to foster synergies between national climate funds and multilateral climate funds. Policymakers have the opportunity to harvest lessons from existing funds and calibrate climate policies accordingly, especially as countries contemplate setting revenue-generating carbon prices.

Abstract

Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector - the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies.

The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.

Geographic coverage

See Methodology document for country-specific geographic coverage details.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Global Findex indicators are drawn from survey data collected by Gallup, Inc. over the 2011 calendar year, covering more than 150,000 adults in 148 economies and representing about 97 percent of the world's population. Since 2005, Gallup has surveyed adults annually around the world, using a uniform methodology and randomly selected, nationally representative samples. The second round of Global Findex indicators was collected in 2014 and is forthcoming in 2015. The set of indicators will be collected again in 2017.

Surveys were conducted face-to-face in economies where landline telephone penetration is less than 80 percent, or where face-to-face interviewing is customary. The first stage of sampling is the identification of primary sampling units, consisting of clusters of households. The primary sampling units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid.

Surveys were conducted by telephone in economies where landline telephone penetration is over 80 percent. The telephone surveys were conducted using random digit dialing or a nationally representative list of phone numbers. In selected countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to teach a person in each household, spread over different days and times of year.

The sample size in the majority of economies was 1,000 individuals.

Mode of data collection

Face-to-face [f2f] OR Landline telephone OR Landline and cellular telephone

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup, Inc. also provided valuable input. The questionnaire was piloted in over 20 countries using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on insurance, mobile payments, and loan purposes were asked only in developing economies. The indicators on awareness and use of microfinance insitutions (MFIs) are not included in the public dataset. However, adults who report saving at an MFI are considered to have an account; this is reflected in the composite account indicator.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country- and indicator-specific standard errors, refer to the Annex and Country Table in Demirguc-Kunt, Asli and L. Klapper. 2012. "Measuring Financial Inclusion: The Global Findex." Policy Research Working Paper 6025, World Bank, Washington, D.C.

This dataset provides information about the number of programs that have received Agency Review funding, how many of those programs had defined measurable outcome goals (DMOG) specified in the agency's funding request applications, and how many programs achieved their DMOG.The Agency Review process was developed to distribute human services funds to non-profit agencies. Agency Review funds come from the City of Tempe General Revenue Fund, Federal Community Development Block Grants, and water utility customer donations through Tempe’s Help to Others.This page provides data for the Human Services Grant performance measure.Identifies the people served as a result of the Agency Review grant funding to non-profit agencies.The performance measure dashboard is available at 3.10 Human Services Grants.Additional InformationSource: e-CImpactContact: Octavia HarrisContact E-Mail: octavia_harris@tempe.govData Source Type: ExcelPreparation Method: Data downloaded from e-CImpact, then compiled in a spreadsheet to establish yes/no fields for aggregate calculations by population servedPublish Frequency: AnnualPublish Method: ManualData Dictionary

This data set contains Help to Buy: Equity Loan statistics at local authority level. The figures cover the launch of the scheme on 1 April 2013 until 31 October 2014. Information on the allocation of completed sales to postcode sectors is derived using the latest available information on the full postcode for each scheme, which may be subject to revision. For sales before 31 March 2014, properties are included under the local authority district to which they were initially allocated. In some cases, this differs from latest information, which forms the basis of the first column of local authority district figures. Figures for some local authorities may be subject to revisions later in the year. Although local authority information is validated against other geographic data at the time of data entry, detailed reconciliation of the data, conducted twice a year, may result in a small number of changes to these monthly releases, for example where a new development crosses a local authority boundary. An equity loan is Government financial assistance given to eligible applicants to purchase an eligible home through a Government equity mortgage secured on the home. The Government equity mortgage is ranked second in priority behind an owner’s main mortgage lender. This scheme offers up to 20 per cent of the value as Government assistance to purchasers buying a new build home. The buyer must provide a cash deposit of at least 5 per cent and a main mortgage lender must provide a loan of at least 75 per cent. The Government assistance to buy is made through an equity loan made by the Homes and Communities Agency (HCA) to the purchaser. Help to Buy equity loans are only available on new build homes and the maximum purchase price is £600,000. Equity loan assistance for purchasers is paid via house builders registered with the HCA to participate in the Help to Buy equity loan initiative. The payment is made to builders (via solicitors) at purchaser legal completion. The equity loan is provided without fees for the first five years of ownership. The property title is held by the home owner who can therefore sell their home at any time and upon sale should provide the government the value of the same equity share of the property when it is sold. For further information see Help to Buy (equity loan) scheme monthly statistics.

Pension Credit claimants (financial help for people aged 60 or over whose income is below a certain level set by the law) Source: Department for Work and Pensions (DWP) Publisher: Department for Work and Pensions (DWP) Geographies: Lower Layer Super Output Area (LSOA), Middle Layer Super Output Area (MSOA), Ward, Local Authority District (LAD), County/Unitary Authority, Government Office Region (GOR), National Geographic coverage: England and Wales Time coverage: 2003 to 2009 Type of data: Administrative data Notes: Pension Credit, introduced on 6 October 2003, is an entitlement for people aged 60 and over living in Great Britain. It is not necessary to have paid National Insurance contributions to be eligible. The guarantee credit provides financial help for people aged 60 or over whose income is below a certain level set by the law. The level that applies depends on your circumstances, this is the standard, minimum guarantee. The awarded amount will depend on other sources of income, such as other pensions and savings. Extra amounts will be added to the standard minimum guarantee for those who have relevant housing costs, severe disabilities, or caring responsibilities. https://www.gov.uk/government/collections/dwp-statistical-summaries

This data set contains Help to Buy: Equity Loan statistics at postcode district level. For data released from 5 March 2015 onwards, the Homes and Community Agency (HCA) have revised the completion date for the entire Help to Buy Equity Loan time series. The HCA have stopped counting payment date (when the money out is paid out by the HCA) and now report on the expected actual completion date. It is more accurate and is closer to the live situation, especially when HCA now recognise an asset based on a completion, rather than exchange and approved claim. As a result (and due to reinstating accounts) HCA have seen movement of actual completions dates. There should not be this level of difference moving forward, it was a one off activity. The figures cover the launch of the scheme on 1 April 2013 until 30 September 2016. Figures have been attributed to an individual constituency by reconciling data against the ONS Postcode Directory (May 2014) where possible. Figures for some constituencies may be subject to revision later in the year. For sales before 31 March 2014, properties are included under the local authority district to which they were initially allocated. In some cases, this differs from latest information, which forms the basis of the first column of local authority district figures. Figures for some local authorities may be subject to revisions later in the year. Although local authority information is validated against other geographic data at the time of data entry, detailed reconciliation of the data, conducted twice a year, may result in a small number of changes to these monthly releases, for example where a new development crosses a local authority boundary. An equity loan is Government financial assistance given to eligible applicants to purchase an eligible home through a Government equity mortgage secured on the home. The Government equity mortgage is ranked second in priority behind an owner’s main mortgage lender. This scheme offers up to 20 per cent of the value as Government assistance to purchasers buying a new build home. The buyer must provide a cash deposit of at least 5 per cent and a main mortgage lender must provide a loan of at least 75 per cent. The Government assistance to buy is made through an equity loan made by the Homes and Communities Agency (HCA) to the purchaser. Help to Buy equity loans are only available on new build homes and the maximum purchase price is £600,000. Equity loan assistance for purchasers is paid via house builders registered with the HCA to participate in the Help to Buy equity loan initiative. The payment is made to builders (via solicitors) at purchaser legal completion. The equity loan is provided without fees for the first five years of ownership. The property title is held by the home owner who can therefore sell their home at any time and upon sale should provide the government the value of the same equity share of the property when it is sold. For further information see Help to Buy (equity loan) scheme monthly statistics.

Project overview

The main goal of this model is to help me create an app that count How much money does a picture has.

Descriptions of each class type

I don't seperate country base money and don't seperate front and back

EUR-1-cent   dasdasd
EUR-2-cent
EUR-5-cent
EUR-10-cent
EUR-20-cent
EUR-50-cent
EUR-1-euro
EUR-2-euro

Current status and timeline

• Adding EUR (currently)
• Adding CHF

Links to external resources

Contribution and labeling guidelines

Techsalerator’s Business Funding Data for Saudi Arabia

Techsalerator’s Business Funding Data for Saudi Arabia provides a comprehensive and detailed collection of information crucial for businesses, investors, and financial analysts. This dataset offers an in-depth analysis of the funding activities of companies across various sectors in Saudi Arabia, capturing and categorizing data related to their funding rounds, investment sources, and financial milestones.

If you need the full dataset, reach out to us at info@techsalerator.com or visit https://www.techsalerator.com/contact-us.

Techsalerator’s Business Funding Data for Saudi Arabia

Techsalerator’s Business Funding Data for Saudi Arabia offers a thorough and insightful overview essential for businesses, investors, and financial analysts. This dataset examines funding activities across diverse sectors in Saudi Arabia, detailing data on funding rounds, investment sources, and key financial milestones.

Top 5 Key Data Fields

Company Name: Identifies the company receiving funding. This information helps investors spot potential opportunities and allows analysts to track funding trends within specific industries.

Funding Amount: Shows the total amount of funding a company has received. Understanding these amounts reveals insights into the financial health and growth potential of businesses and the scale of investment activities.

Funding Round: Indicates the stage of funding, such as seed, Series A, Series B, or later stages. This helps investors assess a business’s maturity and growth trajectory.

Investor Name: Provides details about the investors or investment firms involved. Knowing the investors helps gauge the credibility of the funding source and their strategic interests.

Investment Date: Records when the funding was completed. The timing of investments can reflect market trends, investor confidence, and potential impacts on a company’s future.

Top 5 Funding Trends in Saudi Arabia

Renewable Energy: Significant investments are being directed towards renewable energy projects, including solar and wind energy. These investments are crucial for Saudi Arabia’s Vision 2030 and its goals for sustainable development.

Technology and Innovation: There is a strong focus on funding technology startups and innovation hubs, particularly in fintech, artificial intelligence, and cybersecurity, reflecting the country’s drive towards becoming a tech-driven economy.

Healthcare and Biotechnology: Increased funding is flowing into healthcare infrastructure, biotechnology, and health tech to address the healthcare needs of the population and support medical advancements.

Real Estate and Urban Development: Investments are being made in large-scale real estate and urban development projects, aligning with the country’s goals to diversify its economy and improve living standards.

Education and Talent Development: Funding is being allocated to educational initiatives and programs aimed at enhancing skills and creating job opportunities, supporting the country’s aim to build a knowledge-based economy.

Top 5 Companies with Notable Funding Data in Saudi Arabia

STC Group: As a leading telecommunications provider, STC Group has secured substantial funding to expand its network and enhance its digital services.

Saudi Aramco: The state-owned oil giant has received significant investment for diversification projects, including investments in renewable energy and technology.

NEOM: The futuristic city project NEOM has attracted considerable funding to support its development and innovative urban planning.

Al Habtoor Group: This conglomerate has garnered funding to expand its real estate and hospitality ventures within Saudi Arabia and beyond.

Tahaluf Al Emarat Technical Solutions: This tech company has received funding to advance its technology solutions and contribute to Saudi Arabia’s tech ecosystem.

Accessing Techsalerator’s Business Funding Data

To obtain Techsalerator’s Business Funding Data for Saudi Arabia, contact info@techsalerator.com with your specific needs. Techsalerator will provide a customized quote based on the required data fields and records, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

Company Name Funding Amount Funding Round Investor Name Investment Date Funding Type (Equity, Debt, Grants, etc.) Sector Focus Deal Structure Investment Stage Contact Information For detailed insights into funding activities and financial trends in Saudi Arabia, Techsalerator’s dataset is an invaluable resource for investors, business analysts, and financial professionals seeking informed, strategic decisions.

Themen: Einschätzung der Beziehung jüngerer und älterer Menschen: unterschiedliche Vorstellungen von der Gesellschaft, Alte als Last für die Gesellschaft, Dramatisierung des Konflikts durch die Medien, geringere Berücksichtigung der Bedürfnisse der Jüngeren bei Wahlen, Arbeitsplatzmangel durch Anhebung des Rentenalters, Verarmungsrisiko für ältere Frauen ist höher als für ältere Männer, höhere Produktivität junger Menschen; Meinung zur Rente: Zweifel an den zukünftigen Möglichkeiten der Regierung zum Unterstützen der Renten, mangelnde Bereitschaft Berufstätiger für ältere aufzukommen, zu geringe Ausgaben der Regierung für Bildung junger Menschen, Akzeptanz von Rentenreformen durch die Älteren zur Minimierung der finanziellen Last der Arbeitsfähigen, Forderung nach höheren Ausgaben für die Altenpflege, Wunsch nach Erleichterungen für Ältere nach Beginn des Rentenalters noch zu arbeiten; Einschätzung des Beitrags von Älteren für die Gesellschaft: als Ehrenamtliche, für Familie und Verwandtschaft, in Form von finanzieller Hilfe für jüngere Verwandte, zu geringe Gelegenheiten des Kontakts zwischen Älteren und Jüngeren in den Gemeinden, Produkte für Ältere als Wirtschaftsfaktor; Einschätzung der Probleme bei der Pflege ältere Menschen: gute Ausbildung der Pfleger und Ärzte, ausreichende Unterstützung von Menschen, die ältere Familienmitglieder pflegen, ausreichend soziale Dienste zur häuslichen Pflege von Alten, mangelnde Anpassung der Wohnung von Älteren (Barrierefreiheit), größerer Gesellschaftsbeitrag Älterer bei besserer Mobilität; Rolle der öffentlichen Behörden: intensivere Förderung der Beziehung zwischen Jung und Alt in der Schule, Wunsch nach stärkerer Unterstützung von Vereinen, Zufriedenheit mit der Arbeit der Regierung bei der Beziehung zwischen Jung und Alt, Forderung nach öffentlichen Stellen zur Vermittlung von ehrenamtlichen Tätigkeiten. Demographie: Geschlecht; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Urbanisierungsgrad. Zusätzlich verkodet wurde: Befragten-ID; Interviewer-ID; Interviewsprache; Land; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Anzahl der Kontaktversuche; Region; Gewichtungsfaktor. Intergenerational solidarity in an ageing society. Topics: attitude towards selected issues regarding relationships between younger and older people: different views on what is best for society, older people as a burden for society, exaggerated media reports on the risk of a generation conflict, future political decision making in favour of older people, fewer jobs available for younger people as older people work longer, higher risk of older women than of men of falling into poverty in the own country, better performance of companies which employ younger people; attitude towards the following statements related to pensions: increasing difficulty for governments to pay for older people, increasing reluctance of people in employment to pay for older ones, too little government spendings for young people compared to older ones, acceptance of major pension reforms by older people in order to take financial burdens from the younger generations, need for increased financial support of older people, simplified possibility to continue work beyond normal retirement age; attitude towards selected statements with regard to the role of older people to society: major contribution as volunteers in charitable and community organisations in the own country, no appropriate appreciation of older people who care for relatives, importance of financial help of parents and grand-parents for the young ones, support older and younger people in meeting and working together in associations and local community initiatives, products and services responding to the needs of older people will become a key driver in the national economy; attitude towards selected statements on elderly care: well-trained medical personnel in the own country, good support from national social services for people who care for older family members, sufficiency of national social services to help old people stay in their homes, no sufficient adaption of homes to the needs of frail people, higher contribution of older people to society if it was easier to move around; attitude towards the role of public authorities in intergenerational relationships: schools should promote better relations, local authorities should support organisations that foster stronger relationships, government is doing good job to promote better intergenerational understanding, support older people to find opportunities for volunteering. Demography: sex; age; age at end of education; occupation; professional position; type of community. Additionally coded was: respondent ID; interviewer ID; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; call history; region; weighting factor.

Well-functioning financial systems serve a vital purpose, offering savings, credit, payment, and risk management products to people with a wide range of needs. Yet until now little had been known about the global reach of the financial sector the extent of financial inclusion and the degree to which such groups as the poor, women, and youth are excluded from formal financial systems. Systematic indicators of the use of different financial services had been lacking for most economies. The Global Financial Inclusion (Global Findex) database provides such indicators. This database contains the first round of Global Findex indicators, measuring how adults in more than 140 economies save, borrow, make payments, and manage risk. The data set can be used to track the effects of financial inclusion policies globally and develop a deeper and more nuanced understanding of how people around the world manage their day-to-day finances. By making it possible to identify segments of the population excluded from the formal financial sector, the data can help policy makers prioritize reforms and design new policies.

GOArt (Göteborg Organ Art Center) is a research center that specializes in integrated studies of instruments and performance. The pipe organ and its related keyboard instruments - the clavichord, harpsichord, harmonium, and fortepiano - form the research field. The organ database system was developed 1995 - 2000. The main goal was to create a database structure in which it is possible to store both technical and historical information on organs. In addition to storing information on organs, it was important to be able to store information on archive documents and persons related to the instruments. The database thus consists of four main parts, divided into: technical information about the organs, historical information, other archival data, and information about persons linked to the organs. This structure makes it possible to select a certain point of time in history and to trace the historical process, in the database stored as a network between organs, documents, and persons. The user can navigate backwards or forwards in time and will always be informed about connections between organs, documents, and persons at every point in this historical network. The purpose of the database has been to serve as a documentation tool for results from research as well as a tool for analysis and evaluation. The database is also a source of information for future research projects. There are at present more than 200 historical Swedish organs, 870 archive documents and 1900 person records in the database.

Purpose:

The purpose of the database has been to serve as a documentation tool for results from research as well as a tool for analysis and evaluation. The collection of data to the database helps to preserve a unique Swedish cultural heritage for posterity, thus supporting sustainable development. The database information may help curators to make decisions with financial implications, as it may provide a basis for assessing the need and value of measures. The database will also contribute to the documentation and inventory of parts of organs that are unique and protected by the Antiquities Act.

Techsalerator’s Business Funding Data for Somalia

Techsalerator’s Business Funding Data for Somalia provides a comprehensive and insightful collection of information essential for businesses, investors, and financial analysts. This dataset offers an in-depth analysis of funding activities across various sectors in Somalia, capturing and categorizing data related to funding rounds, investment sources, and financial milestones.

If you need the full dataset, reach out to us at info@techsalerator.com or https://www.techsalerator.com/contact-us.

Techsalerator’s Business Funding Data for Somalia

Techsalerator’s Business Funding Data for Somalia delivers a detailed and insightful overview of crucial information for businesses, investors, and financial analysts. This dataset offers an in-depth examination of funding activities across diverse sectors in Somalia, detailing data related to funding rounds, investment sources, and key financial milestones.

Top 5 Key Data Fields

Company Name: Identifies the company receiving funding. This information helps investors pinpoint potential opportunities and allows analysts to monitor funding trends within specific industries.

Funding Amount: Shows the total amount of funding a company has received. Understanding these amounts reveals insights into the financial health and growth potential of businesses and the scale of investment activities.

Funding Round: Indicates the stage of funding, such as seed, Series A, Series B, or later stages. This helps investors assess a business’s maturity and growth trajectory.

Investor Name: Provides details about the investors or investment firms involved. Knowing the investors helps gauge the credibility of the funding source and their strategic interests.

Investment Date: Records when the funding was completed. The timing of investments can reflect market trends, investor confidence, and potential impacts on a company’s future.

Top 5 Funding Trends in Somalia

Infrastructure Development: Investments are focusing on essential infrastructure projects, including roads, bridges, and energy initiatives. These investments are critical for the country's economic development and stability.

Agriculture and Agritech: With agriculture being a vital part of Somalia’s economy, funding is directed towards modernizing agricultural practices through agritech, emphasizing sustainability and productivity enhancements.

Telecommunications and Digital Connectivity: The telecom sector in Somalia is attracting significant investment, aimed at improving digital connectivity and access to information, crucial for economic growth and social development.

Healthcare and Pharmaceuticals: Increased funding is flowing into healthcare infrastructure, pharmaceuticals, and health tech to address the healthcare needs of the population and support medical research and innovation.

Education and Vocational Training: Investments are being allocated to educational initiatives and vocational training programs designed to improve literacy rates, enhance skills, and create employment opportunities.

Top 5 Companies with Notable Funding Data in Somalia

Somtel: A leading telecommunications provider, Somtel has received substantial funding to expand its network coverage, enhance digital services, and support community development.

Hormuud Telecom: Another major telecom player, Hormuud Telecom, has secured funding for network infrastructure upgrades, digital service expansions, and innovative technology implementations.

Premier Bank: This financial institution has attracted significant investment to enhance its banking services, broaden its reach across the country, and promote financial inclusion.

Dalsan Group: Dalsan Group has received notable funding to support its expansion into various sectors, including logistics and infrastructure, boosting its role in Somalia’s economic growth.

Somalia Red Crescent Society: The humanitarian organization has garnered funding to expand healthcare services, support disaster relief efforts, and improve medical care access in underserved areas.

Accessing Techsalerator’s Business Funding Data

To obtain Techsalerator’s Business Funding Data for Somalia, contact info@techsalerator.com with your specific needs. Techsalerator will provide a customized quote based on the required data fields and records, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

• Company Name
• Funding Amount
• Funding Round
• Investor Name
• Investment Date
• Funding Type (Equity, Debt, Grants, etc.)
• Sector Focus
• Deal Structure
• Investment Stage
• Contact Information

For detailed insights into funding activities and financial trends in Somalia, Techsalerator’s dataset is an invaluable resource for investors, business analysts, and financial professionals seeking informed, strategic decisions.