TXF went to ITFA’s Fintech briefing in London in mid-June to investigate what practical progress is being made in the tradetech space and what individual companies present at the event are working on. Transparency and accurate data are key and artificial intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) are all coming into play.

Within trade finance, up to 200 documents are exchanged among supply chain entities on a transaction, a costly, time consuming and complex process. ITFA’s fintech briefing in mid-June focused on the developments in trade finance and credit management, such as AI and ML, technologies which can complete tasks with superior accuracy and efficiently than when carried out manually. According to a report by Markets and Markets, the AI market value is expected to reach $190.61 billion by 2025 and the finance industry is thought to be particularly suited to its benefits.

Rebecca Harding, CEO of Coriolis Tradetech, spoke on the importance of data within her business. Based on the belief that the future of trade is data, and using new multilateral technology, the company aims to build the “Bloomberg for trade finance” by developing publicly available data with bespoke sector data, such as bank, logistics and company data. It is then augmented with the digital footprint of banks and companies onto one platform, using AI and ML to create risk analytics around it. The final platform is due to be launched in Africa by 1 December 2019.

Traydstream is developing a technology that uses a simple scanner to automate the processing of trade finance documentation, combining ML and AI with NLP to create intelligence pattern recognition. Following the announcement of a 10-week pilot partnership with Nokia in mid-June, Traydstream CEO, Sameer Sehgal, reported that the technology has the potential to do 28 days of manual work in five minutes, and that the company is very close to perfecting this. Although promising, there was no mention of a guaranteed date of completion.

While many fintechs are relatively new, others have been around for years, such as working capital solutions provider Taulia which has just celebrated its 10th birthday. Taulia’s platform boasts one million interactions daily and offers working capital solutions for corporates by liberating cash within the supply chain. In April 2019, Taulia announced a partnership with Google Cloud to launch an AI-powered automated end-to-end invoicing process for buyers and suppliers. This is set to reduce the cost of processing invoices and speed up the process, so suppliers will be able to access earlier payments.

Michael Boguslavsky, Head of AI at cloud-based technology project Tradeteq, says, “There is a lot of work to do for trade finance to become investable as an asset. A lot of this is about better information and transparency.” Although other fintechs such as blockchain are known for being transparent, AI and ML can lack transparency as not all techniques are interpretable. Another potential issue is that they are reliant on data quality and cannot use the “bigger picture” to predict outliers in the same way humans can. That considered, AI and ML allow for proactive supply chain management, increasing cost efficiency and accuracy.