Note: These data sources are suggestive. You are not mandated to use any or all of them. Please feel free to use other relevant data sources and generate your own data as it suits your purpose.

Task 1: Access to Affordable Finance: Unlocking Access to Finance for the Next Generation of Agripreneurs

Data Sources You Can Leverage:

Farmer Survey Data:

Source: LSMS-ISA Nigeria Agriculture Panel

URL: https://microdata.worldbank.org/index.php/catalog/2734

Financial Inclusion Data:

Explore EFInA's research initiatives and access various A2F survey reports:

URL: https://efina.org.ng/our-work/research/​

2020 Survey Report:

Access the full 2020 A2F survey report detailing financial inclusion metrics:

URL: https://efina.org.ng/wp-content/uploads/2021/10/A2F-2020-Final-Report.pdf​efina.org.ng+1efina.org.ng+1

2023 Survey Key Highlights:

Review the key findings from the 2023 A2F survey:

URL: https://efina.org.ng/wp-content/uploads/2024/03/A2F-2023-Event-Day-Presentation-Version4-1.pdf​

NBS Microdata Portal:

https://microdata.nigerianstat.gov.ng/​

Nigeria Labour Force Survey Q2 2024 Microdata:

https://microdata.nigerianstat.gov.ng/index.php/catalog/152

Agricultural Productivity Data:

Source: FAO Nigeria Agricultural Statistics

URL: https://www.fao.org/faostat/en/#country/158

List of CBN Licensed Microfinance Banks as at December 31, 2021

URL: https://www.cbn.gov.ng/out/2022/fprd/list%20of%20microfinance%20banks%20as%20at%20december%2031%2C%202021.pdf​

Weather Data: World Bank Climate Portal – Nigeria — https://climateknowledgeportal.worldbank.org/country/nigeria/climate-data-historical

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Task 2: Post-Harvest Losses Problem: Reducing Post-Harvest Losses to Build Youth-Led Agri-Businesses

Datasets You Can Leverage:

FAO Report: "Research on the Measurement of Post-Harvest Losses"

https://openknowledge.fao.org/items/7ad23dcc-5a83-4a04-95bd-e51799cd48bf​

FAO Report: "Post-Harvest Losses in Inland Fisheries in Nigeria"

https://www.fao.org/4/t0606b/T0606B11.htm

NASC 2022 Community Listing https://microdata.nigerianstat.gov.ng/index.php/catalog/80

Weather and Climate Risk Data:

Source: World Bank Climate Portal Nigeria

URL: https://climateknowledgeportal.worldbank.org/country/nigeria

Transportation and Market Access Data:

Source: Global Open Data for Agriculture and Nutrition (GODAN)

URL: https://www.godan.info/

PS: These data sources are merely suggestive. You are not mandated to use any or all of them. Please feel free to use other data sources or generate your own data as it suits your purpose

Data Strategy:

• Description of datasets used and sources.
• Steps taken for cleaning and analyzing the data.

Farmer Finance Profile:

• Visualizations or scoring models that assess the likelihood of young farmers to succeed or repay loans.
• Insights into what makes a farmer "low risk" or "investment-ready."

Predictive Model(Optional but bonus points):

• A credit scoring model or farm business success prediction.

Solution Proposal:

• A concept or prototype (e.g., an app/dashboard for loan applications, farmer credit scorecards, microfinance risk dashboards).
• How the solution builds trust between farmers and financiers.

• Design an app prototype.
• Include farmer education features (e.g., "how to improve your credit score" tips).
• Build a dashboard that lenders or agricultural investors can easily use.

1. Access to Affordable Finance: Unlocking Access to Finance for the Next Generation of Agripreneurs

Background:

Access to affordable finance remains one of the biggest barriers preventing young Nigerians from entering agriculture.

According to the EFInA Access to Financial Services in Nigeria 2020 survey, only 27% of rural adults have access to formal financial services. Among young people aged 18–25, access to loans for business purposes is even lower at 6%.

Meanwhile, agriculture employs about 35% of Nigeria’s workforce (World Bank, 2022), but contributes less than 25% to the GDP — suggesting underinvestment.

Commercial banks often consider agriculture "too risky" because of factors like climate variability, land tenure issues, and lack of credit history. Without access to credit, young farmers cannot invest in seeds, technology, irrigation, or machinery needed to boost yields and incomes.

How can we use data to bridge this finance gap and make agriculture a bankable, attractive industry for youth?

Objective:

Develop a data-driven solution that helps young agripreneurs obtain access to affordable finance.

You are expected to collect, process, analyze, and model data to:

Identify factors that make farmers "creditworthy."

Predict future repayment behavior or business success.

Design tools that banks, investors, or grant bodies could trust to fund young farmers.