Colombia CO: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 38.300 % in 2020. This records an increase from the previous number of 29.400 % for 2019. Colombia CO: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 39.950 % from Dec 1992 (Median) to 2020, with 22 observations. The data reached an all-time high of 61.400 % in 2001 and a record low of 28.100 % in 2017. Colombia CO: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from around 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Poverty gap at $3.2 a day of Colombia shot up by 17.50% from 4.0 % in 2018 to 4.7 % in 2019. Since the 9.30% slump in 2017, poverty gap at $3.2 a day soared by 20.51% in 2019. Poverty gap at $3.20 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $3.20 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.

Colombia CO: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 19.900 % in 2020. This records an increase from the previous number of 12.700 % for 2019. Colombia CO: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 20.300 % from Dec 1992 (Median) to 2020, with 22 observations. The data reached an all-time high of 37.700 % in 2001 and a record low of 11.100 % in 2018. Colombia CO: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from around 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

From 2017 to 2021, the share of households living under the poverty line in Venezuela has been surpassing 90 percent. In addition, more than six out of every ten households (67.97 percent) lived in extreme poverty in 2021. The overall household poverty rate in Venezuela has registered a steady growth from 2014 to 2019, after having remained relatively stable, below 40 percent, since 2005. Although poverty is widespread among the population as a whole, some groups are more vulnerable than others. That is the case of younger generations and particularly children: 98.03 percent of Venezuelans aged 15 or younger lived in poverty in 2021. An economy in disarray Venezuela, the country with the largest oil reserves in the world and whose economy has been largely dependent on oil revenues for decades, was once one of the most prosperous countries in Latin America. Today, hyperinflation and an astronomic public debt are only some of the many pressing concerns that affect the domestic economy. The socio-economic consequences of the crisis As a result of the economic recession, more than half of the population in every state in Venezuela lives in extreme poverty. This issue is particularly noteworthy in the states of Amazonas, Monagas, and Falcón, where the extreme poverty rate hovers over 80 percent. Such alarming levels of poverty, together with persistent food shortages, provoked a rapid increase in undernourishment, which was estimated at 17.9 percent between 2020 and 2022. The combination of humanitarian crisis, political turmoil and economic havoc led to the Venezuelan refugee and migrant crisis. As of 2020, more than five million Venezuelans had fled their home country, with neighboring Colombia being the main country of destination.

This poverty rate data shows what percentage of the measured population* falls below the poverty line. Poverty is closely related to income: different “poverty thresholds” are in place for different sizes and types of household. A family or individual is considered to be below the poverty line if that family or individual’s income falls below their relevant poverty threshold. For more information on how poverty is measured by the U.S. Census Bureau (the source for this indicator’s data), visit the U.S. Census Bureau’s poverty webpage.

The poverty rate is an important piece of information when evaluating an area’s economic health and well-being. The poverty rate can also be illustrative when considered in the contexts of other indicators and categories. As a piece of data, it is too important and too useful to omit from any indicator set.

The poverty rate for all individuals in the measured population in Champaign County has hovered around roughly 20% since 2005. However, it reached its lowest rate in 2021 at 14.9%, and its second lowest rate in 2023 at 16.3%. Although the American Community Survey (ACS) data shows fluctuations between years, given their margins of error, none of the differences between consecutive years’ estimates are statistically significant, making it impossible to identify a trend.

Poverty rate data was sourced from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Poverty Status in the Past 12 Months by Age.

*According to the U.S. Census Bureau document “How Poverty is Calculated in the ACS," poverty status is calculated for everyone but those in the following groups: “people living in institutional group quarters (such as prisons or nursing homes), people in military barracks, people in college dormitories, living situations without conventional housing, and unrelated individuals under 15 years old."

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (25 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (16 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).

Colombia CO: Multidimensional Poverty Headcount Ratio: Female: % of female population data was reported at 15.700 % in 2021. This records a decrease from the previous number of 17.900 % for 2020. Colombia CO: Multidimensional Poverty Headcount Ratio: Female: % of female population data is updated yearly, averaging 17.100 % from Dec 2019 (Median) to 2021, with 3 observations. The data reached an all-time high of 17.900 % in 2020 and a record low of 15.700 % in 2021. Colombia CO: Multidimensional Poverty Headcount Ratio: Female: % of female population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

Colombia CO: Poverty Gap at $5.50 a Day: 2011 PPP: % data was reported at 17.600 % in 2020. This records an increase from the previous number of 11.400 % for 2019. Colombia CO: Poverty Gap at $5.50 a Day: 2011 PPP: % data is updated yearly, averaging 17.750 % from Dec 1992 (Median) to 2020, with 22 observations. The data reached an all-time high of 31.700 % in 2001 and a record low of 10.400 % in 2017. Colombia CO: Poverty Gap at $5.50 a Day: 2011 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. Poverty gap at $5.50 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $5.50 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.; ; World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from around 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Colombia CO: Increase in Poverty Gap at $3.20: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data was reported at 0.778 USD in 2016. This records a decrease from the previous number of 1.062 USD for 2010. Colombia CO: Increase in Poverty Gap at $3.20: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data is updated yearly, averaging 1.062 USD from Dec 2008 (Median) to 2016, with 3 observations. The data reached an all-time high of 1.193 USD in 2008 and a record low of 0.778 USD in 2016. Colombia CO: Increase in Poverty Gap at $3.20: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Poverty. Increase in poverty gap at $3.20 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure, expressed in US dollars (2011 PPP). The poverty gap increase due to out-of-pocket health spending is one way to measure how much out-of-pocket health spending pushes people below or further below the poverty line (the difference in the poverty gap due to out-of-pocket health spending being included or excluded from the measure of household welfare). This difference corresponds to the total out-of-pocket health spending for households that are already below the poverty line, to the amount that exceeds the shortfall between the poverty line and total consumption for households that are impoverished by out-of-pocket health spending and to zero for households whose consumption is above the poverty line after accounting for out-of-pocket health spending.; ; World Health Organization and World Bank. 2019. Global Monitoring Report on Financial Protection in Health 2019.; Weighted average;

Colombia Unemployed: Barranquilla - Soledad data was reported at 79.442 Person th in Apr 2019. This records an increase from the previous number of 74.494 Person th for Mar 2019. Colombia Unemployed: Barranquilla - Soledad data is updated monthly, averaging 80.954 Person th from Mar 2001 (Median) to Apr 2019, with 218 observations. The data reached an all-time high of 123.229 Person th in Aug 2002 and a record low of 54.533 Person th in Jul 2011. Colombia Unemployed: Barranquilla - Soledad data remains active status in CEIC and is reported by National Statistics Administrative Department. The data is categorized under Global Database’s Colombia – Table CO.G028: Unemployment: Household Survey.

Snapshot img

Microfinance Market Size 2025-2029

The microfinance market size is forecast to increase by USD 206.8 billion at a CAGR of 14.1% between 2024 and 2029.

The market is experiencing significant growth, driven by the emergence of social media and increasing digital connectivity. This trend is particularly prominent in the Asia Pacific region, where the market is expanding rapidly. However, the industry faces challenges related to inadequate risk management. The proliferation of digital platforms is enabling financial inclusion, reaching populations previously underserved by traditional financial institutions. In the Asia Pacific region, for instance, over 200 million adults remain unbanked, presenting a vast opportunity for microfinance institutions. Yet, the sector's growth is not without challenges. Effective risk management remains a significant hurdle, as microfinance institutions grapple with assessing and mitigating risk in an environment characterized by limited financial data and high operational complexity. Companies seeking to capitalize on market opportunities and navigate challenges effectively must invest in advanced risk management solutions, leveraging technology and data analytics to mitigate risk and expand their reach. Additionally, strategic partnerships and collaborations can help microfinance institutions overcome operational complexities and expand their offerings, catering to the diverse financial needs of their clientele.

What will be the Size of the Microfinance Market during the forecast period?

Request Free SampleThe market encompasses loan facilities and financial services catering to the low-income segment, primarily focusing on cottage industries and household income generation. Microfinance credit plays a crucial role in poverty reduction by providing access to financial aid for individuals and microenterprises, often bypassing traditional lending practices. Technological infrastructure, including digital platforms and mobile banking, significantly contributes to the market's growth, enabling financial inclusion and economic empowerment. Peer-to-peer lending and technological integration have reduced operating costs, allowing financial institutions to offer microcredit facilities with competitive interest rates. Traditional banking services are increasingly adopting technology to streamline loan processing, savings accounts, money transfers, leasing services, and financial return tracking. The financial health of microfinance institutions relies on effective credit scoring and maintaining financial return, attracting private sector banks and fintech companies to invest in this sector. Overall, the market continues to expand, driven by the need for affordable financial services and the increasing adoption of technology.

How is this Microfinance Industry segmented?

The microfinance 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-userSmall enterprisesSolo entrepreneursMicro enterprisesUsageAgricultureManufacturing/ProductionTrade and servicesHouseholdOthersTypeBanksNon-banksService TypeGroup and individual micro-creditInsuranceSavings and checking accountsLeasingMicro-investment fundsGeographyAPACBangladeshChinaIndiaIndonesiaVietnamSouth AmericaArgentinaBrazilChileColombiaNorth AmericaUSEuropeMiddle East and Africa

By End-user Insights

The small enterprises segment is estimated to witness significant growth during the forecast period.The market plays a significant role in catering to the financial needs of small businesses, particularly those without access to traditional financial institutions. Fueled by an increasing entrepreneurial spirit, expanding public awareness of microfinance services, and favorable regulatory environments, this market has experienced substantial growth. Microfinance institutions (MFIs) offer loan facilities to various sectors, including rural agriculture, cottage industries, and micro and small enterprises. Digital integration through mobile banking, point-of-sale systems, and peer-to-peer lending platforms has broadened reach and improved accessibility, especially in remote areas. MFIs provide financial services such as savings accounts, money transfers, leasing services, and loan processing to promote financial health and social mobility among unbanked populations. Despite challenges like high interest rates, short repayment periods, and operational costs, MFIs remain crucial in poverty reduction and financial inclusion.

Get a glance at the market report of share of various segments Request Free Sample

The Small enterprises segment was valued at USD 59.80 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 48% to the growth of the global market

Colombia CO: Increase in Poverty Gap at $1.90: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data was reported at 0.180 USD in 2016. This records a decrease from the previous number of 0.199 USD for 2010. Colombia CO: Increase in Poverty Gap at $1.90: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data is updated yearly, averaging 0.199 USD from Dec 2008 (Median) to 2016, with 3 observations. The data reached an all-time high of 0.268 USD in 2008 and a record low of 0.180 USD in 2016. Colombia CO: Increase in Poverty Gap at $1.90: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. Increase in poverty gap at $1.90 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure, expressed in US dollars (2011 PPP). The poverty gap increase due to out-of-pocket health spending is one way to measure how much out-of-pocket health spending pushes people below or further below the poverty line (the difference in the poverty gap due to out-of-pocket health spending being included or excluded from the measure of household welfare). This difference corresponds to the total out-of-pocket health spending for households that are already below the poverty line, to the amount that exceeds the shortfall between the poverty line and total consumption for households that are impoverished by out-of-pocket health spending and to zero for households whose consumption is above the poverty line after accounting for out-of-pocket health spending.;World Health Organization and World Bank. 2019. Global Monitoring Report on Financial Protection in Health 2019. NOTE: This indicator has been discontinued as of December 2021. Please see the following indicators: SH.UHC.FBP1.ZS, SH.UHC.FBP2.ZS, SH.UHC.FBP1.TO and SH.UHC.FBP2.TO.;Weighted average;

（停止更新）多维贫困率：男性：男性占总人口百分比在12-01-2021达16.200%，相较于12-01-2020的18.300%有所下降。（停止更新）多维贫困率：男性：男性占总人口百分比数据按年更新，12-01-2019至12-01-2021期间平均值为17.900%，共3份观测结果。该数据的历史最高值出现于12-01-2020，达18.300%，而历史最低值则出现于12-01-2021，为16.200%。CEIC提供的（停止更新）多维贫困率：男性：男性占总人口百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的哥伦比亚 – Table CO.World Bank.WDI: Social: Poverty and Inequality。

（停止更新）多维贫困率：女性：女性占总人口百分比在12-01-2021达15.700%，相较于12-01-2020的17.900%有所下降。（停止更新）多维贫困率：女性：女性占总人口百分比数据按年更新，12-01-2019至12-01-2021期间平均值为17.100%，共3份观测结果。该数据的历史最高值出现于12-01-2020，达17.900%，而历史最低值则出现于12-01-2021，为15.700%。CEIC提供的（停止更新）多维贫困率：女性：女性占总人口百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的哥伦比亚 – Table CO.World Bank.WDI: Social: Poverty and Inequality。

（停止更新）每日3.20美元水平的贫困人口比例：2011年购买力平价：占人口百分比在12-01-2020达19.900%，相较于12-01-2019的12.700%有所增长。（停止更新）每日3.20美元水平的贫困人口比例：2011年购买力平价：占人口百分比数据按年更新，12-01-1992至12-01-2020期间平均值为20.300%，共22份观测结果。该数据的历史最高值出现于12-01-2001，达37.700%，而历史最低值则出现于12-01-2018，为11.100%。CEIC提供的（停止更新）每日3.20美元水平的贫困人口比例：2011年购买力平价：占人口百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的哥伦比亚 – Table CO.World Bank.WDI: Social: Poverty and Inequality。