AI has arrived – Machine Learning for Credit Analytics

Artificial Intelligence (AI) has arrived. As a technology making waves across just about every industry, its impact on the rapidly digitalising trade finance space is finally being felt. A new white paper issued by ITFA member Tradeteq outlines how this technology is being applied to tackle directly the pressing issue of inadequate credit scoring for SMEs by banks and other lenders – a problem that is excluding a large number of credit-worthy businesses from accessing the finance they need and helping preserve a vast global trade finance gap.

TradeTeq white paper: Machine Learning for Credit Analytics (login required)

Author Michael Boguslavsky, Tradeteq’s head of AI, explains in the white paper how traditional approaches to trade finance require old-fashioned and labour-intensive processes to assess SME credit. And with banks optimising their balance sheets and scaling back operations in many geographies, many information flows traditional approaches rely on are now being cut.

Boguslavsky notes that existing bank credit underwriting and scoring approaches also use models such as the Altman Z-score that are rigid and require specific accounting information from each applicant. He explains how Tradeteq’s models, meanwhile, draw on broader and deeper sets of data, and use a multitude of different company features as inputs. Boguslavsky explains that machine learning techniques combined with this data then lead to the outperformance of traditional Z-score models, even on pure registration data alone: that is, without any accounting inputs whatsoever.

Nils Behling, co-founder and CFO, Tradeteq explains: “Our approach, using machine learning techniques with non-homogenous data from multiple sources, is a game changer for SMEs seeking trade finance. It allows for better credit decisions, and dramatically expands the number of companies able to win finance – not just from banks, but from institutional lenders too. Our aim is to continue enabling banks, corporates and non-bank investors to come together and transact in ways that are beneficial for all.”

André Casterman, Chair of ITFA FinTech Committee, adds “New technologies such as machine learning are challenging a series of established trade finance practices including credit scoring. They help financial institutions expand addressable markets and solve critical market challenges such as improved access to credit for SMEs. Collaboration between trade banks and data-focused fintechs is vital for incumbent institutions to remain competitive in the future digital trade space.”

A total of nine fintechs (*) joined ITFA over the past 12 months to help financial institutions modernise their trade finance practices and grow their business. Join us in Cape Town where ITFA-registered fintechs such as Tradeteq will demo their platforms during both Tuesday and Thursday fintech afternoons.

(*) INTIX, CCRManager, TradeAssets, Tradeteq, TrustBills, Trade.IX, LiquidX, Mitigram, Levantor Capital.