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AI helps to narrow the funding gap for supplier SMEs

Slow or late payments from buyers can spell disaster for many supplier SMEs, creating serious cashflow problems. An EU initiative delivers machine learning algorithms via a user-friendly online platform to smooth the working relationship between supplier and buyer.

Digital Economy

SMEs struggle to find access to short-term financing that’s both affordable and fast enough to keep up with incoming orders. Banks don’t have enough information about SMEs’ commercial transactions to provide loans, and the loans’ small size and short duration makes any thorough background research inefficient in terms of costs.

Show me the money

“Banks have risk teams to assess large loans, but the rest are evaluated by traditional credit scoring models that are often unfairly harsh on SMEs,” explains José Antonio Fernández Martínez, co-founder and Chief Investment Officer of Zero1 Capital, the Madrid-based start-up that coordinated the EU-funded Zero1 project. “This has led to spiralling expenses for SMEs, whose borrowing costs have shot up by 150 % in the euro area in recent years.” Such costs inevitably get passed on to consumers, who end up paying higher prices. This situation has led to a proliferation of alternative online financing solutions for SMEs. However, many SMEs still struggle to find a suitable option, as many of these lenders charge elevated fees or don’t get funding to suppliers at the start of production when it’s most needed. The Zero1 team developed a novel suite of machine learning algorithms that are accessed through an easy-to-use web- and cloud-based platform. Supplier SMEs can apply for funding at an affordable interest rate as soon as they receive an order from their buyer. With just one click, they can apply for funding the moment they receive the purchase order. “By simplifying the process, it’s possible to increase the volume of operations significantly,” notes Fernández Martínez. “Using proven and validated AI will reduce financing costs and lower the risk for the financier, removing supply chain finance inefficiencies.” The algorithms’ powerful forecast capabilities provide a clear view of hidden clients in the data, and easily detect any potential operational issue.

AI-powered transactions that are fast, secure and profitable

Zero1 successfully validated the algorithms by applying them to the supply chain database of a European multinational buyer in the fast-moving consumer goods sector and to its suppliers that are mainly European SMEs. Validation at an international bank, and private funds and credit rating agencies demonstrated to lenders and financiers that the solution is very attractive as a new bank product. “Other lending platforms also connect suppliers to potential investors, but our algorithms go much further,” comments Fernández Martínez. “They allow suppliers to leverage their commercial relationships and buyers to participate and monetise their enterprise resource planning systems’ commercial data.” He continues: “We partner with big multinational buyers who grant us access to data like their historical relationship with a certain supplier. The algorithms are trained to give the supplier a smarter, more holistic credit scoring. All parties benefit.” The most reliable suppliers automatically get the best terms for borrowing, buyers receive a data fee, and banks or private investors yield a good net return. “Zero1 enables a more efficient chain of transactions between supplier and buyer, allowing for the prosperous growth of job-creating SMEs – the core of any economy,” concludes Fernández Martínez. “Buyers or suppliers can optimise their relationship, minimising operational risk across the supply chain.”

Keywords

Zero1, supplier, SMEs, buyer, bank, funding, supplier SMEs, financing

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29 October 2020