A unique suite of Machine Learning (ML) algorithms to battle cashflow problems in SMEs

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The issue of slow or late payments from buyers can spell disaster for many SME suppliers. Payment terms generally range from 30 to 90 days, with up to 40% of these invoices paid late, creating a serious cashflow problem. As a result, SMEs need access to short-term financing which is both affordable and quick enough to keep up with incoming orders. Yet, banks are reluctant to loan to SMEs and their credit scoring methods are often unfairly harsh on them. Alternative online financing exists for SMEs, but many of these lenders charge elevated fees or don’t get funding to suppliers when it is most needed: at the start of production. Our solution: Zero1 is a unique suite of Machine Learning (ML) algorithms accessed through an easy-to-use web- and cloud-based platform. It is designed to finally solve the SME funding gap (currently estimated at 2,3 trillion € worldwide), allowing supplier SMEs to get funding as soon as they receive an order from their buyer, at an affordable interest rate. We partner with big multi-national buyers, who grant us access to data, such as their historical relationship with a supplier. The suite of ML algorithms is trained to give the supplier a smarter, more holistic credit scoring. The most reliable suppliers automatically get the best terms for borrowing, buyers receive a data fee and private investors get a good net return. The result is a more efficient supply chain, with benefits for all stakeholders and the economy at large. Zero1 is a project by Beledger, a FinTech start-up based in Madrid. The 4 partners have over 40 years’ combined expertise in finance, agri-food, the supply chain and technology, including big data and AI. During this project, we will first target the agri-food sector, an industry with a malfunctioning, wasteful supply chain and very long payment terms. Zero1 will bring Beledger an EBITDA of 6,75M € in Year 5 of commercialisation and allow us to hire 61 people.