Fintech firm Avenews says the use of technology and transaction data to determine a farmer’s credit worthiness is key in boosting agriculture financing in Kenya.
Avenews Group Chief Executive Officer Jonathan Tseloon said instead of relying on traditional security, the company analyses business records including M-Pesa statements, bank statements and other financial transaction histories to assess a customer’s creditworthiness.
“Avenews is a fintech company providing transaction-based financing to the agri-sector in Kenya. We are basing our credit decisions on data from transactions rather than traditional financing institutions, which base their decisions more on collateral and other securities,” said Tseloon at the Financing Agri-Food Systems (FINAS) Summit in Nairobi.
Using machine learning and artificial intelligence, the platform evaluates hundreds of data points, including transaction patterns and seasonal trends, enabling quick financing decisions.
The firm says the use of data to appraise agriculture loans eliminates the traditional use of collateral such as land titles, buildings or other assets to access agricultural finance.
Avenews also provides working capital to agrovet shops and stockists, allowing them to purchase seeds, fertilisers, animal feeds and other farm inputs ahead of the planting season.
This bridges the cash gap between buying inventory and selling it to farmers, ensuring agricultural supplies remain available when demand peaks.
Additionally, the firm finances agribusinesses that supply produce to off takers but have to wait several weeks before receiving payment. This enables businesses to maintain cash flow while ensuring farmers are paid sooner and can continue producing.
“We can come in all of these transactions in the middle and close the cash gaps which are an inherent part of the agri-sector. That’s what we want to solve,” he added.
Working with cooperatives, aggregators and other ecosystem partners, Avenews says it is also able to assess risk at the grassroots level and finance businesses that would otherwise struggle to access credit.
“We’re very much based on technology. We use self-developed technology to assess the risk and make the credit decisions. We look at hundreds of data points behind the scenes… based on machine learning and artificial intelligence, not on collecting security,” said Tseloon.
The fintech firm says technology-driven lending could play a critical role in expanding financial inclusion across Kenya’s agricultural sector.
