Agricultural lending carries risks that ordinary retail credit does not: harvests depend on rainfall, prices swing between seasons, and most borrowers have no formal financial statements. Lenders that rely only on collateral and guarantor visits either turn good farmers away or carry hidden losses. Data now offers a more reliable route, whether it comes from delivery records, input purchases, mobile wallets or field measurements.

Across five days, the Data and Analytics for Agri-Finance & Value-Chain Lending Training Course moves from raw data to decisions. Participants start with data sources and quality, then analyse value chains to see where finance is needed and who carries the risk. They build crop and livestock cash-flow models, develop simple scoring approaches, and examine how contract farming, warehouse receipts and aggregator relationships reduce repayment risk. The closing sessions concentrate on portfolio analytics, reporting to management and the ethical use of farmer data.

Work is hands-on, using sample portfolios and spreadsheets that participants keep. By the end, each person has a working scorecard prototype, a dashboard layout and a plan for applying analytics in their own institution.

After completing the course, participants will be able to:

• Identify and assess the data sources available for farm and agribusiness lending.
• Clean, combine and summarise loan and farm data using Excel and Power BI.
• Map a value chain and locate the credit needs and risks of each actor.
• Build seasonal cash-flow and repayment-capacity models for crop and livestock enterprises.
• Develop and test a simple credit scorecard that uses alternative data.
• Interpret weather, yield and price indicators as portfolio risk signals.
• Design dashboards that monitor arrears, concentration and early-warning triggers.
• Apply data protection and fair-treatment principles when using farmer data.

The course suits professionals who lend to, analyse or support agricultural borrowers, including:

• Agricultural and agribusiness loan officers
• Credit analysts and credit risk officers in banks
• SACCO, microfinance and village bank managers
• Agri-fintech and digital lending product teams
• Cooperative and aggregator finance managers
• Development finance and guarantee fund staff
• Portfolio monitoring and MIS officers
• Agribusiness advisers and value-chain facilitators

Participants take away:

• A prototype scorecard that uses transaction, production and delivery data.
• A seasonal cash-flow template adaptable to several crops and livestock enterprises.
• A portfolio dashboard layout with the indicators credit committees ask for.
• A value-chain map showing where finance and risk sit.
• A checklist for data quality, consent and responsible use of farmer information.
• A 90-day plan for introducing analytics into their lending operation.

Learning is practical and centred on realistic agricultural lending files. The programme includes:

• Guided laboratory sessions in Excel and Power BI using sample loan portfolios
• Worked cases from dairy, tea, horticulture and grain value chains
• Small-group build exercises for scorecards and cash-flow models
• Critique sessions where participants challenge each other's dashboards
• Templates and datasets provided for use back at work

Participants who attend the full programme and complete the practical exercises are awarded a CPD-accredited Certificate of Completion by Vision Reach Global Consultancy.