Fast-forwarding past the global financial crisis to the present, most of the supply chain finance programs supported by technology are focused on providing relatively safe post-shipment financing backed by buyer-accepted invoices. The supporting technology typically consists of either a proprietary bank platform or a multi-funding bank-agnostic platform provided by one of the various technology companies that seem to be being founded on an almost daily basis. Both these bank and non-bank platforms, however, address only a small portion of the market, while scalability remains an ongoing challenge due to on-boarding, KYC, legal, accounting and multiple jurisdiction documentation challenges.

Emerging technologies such as artificial intelligence, natural-language processing, and robotic process automation will undoubtedly play a definitive role in bringing about efficiencies in the SCF space. However, to achieve commercial success and revenue growth, banks must also look at replacing their conventional risk assessment and compliance models (focused on balance sheet and P&L statements) with more dynamic models that utilise both quantitative and qualitative tools.

The quantitative tools will be powered by high-end analytics, which look at matching accounts payable and receivable data from the large buyer or seller’s ERP with the invoices raised, as well as the actual payments received in the supplier’s bank account. A sophisticated web-scraping tool, backed by machine-learning algorithms, will then carry out the next level of analysis to identify suppliers with strong performance track records.