Digitisation and Automation in Commercial Lending: Disruption without Distraction

Elaine Wong

Automation and data-driven analytics have become part of our daily lives. Banking is no different. For example, a credit card application can be approved within minutes, and even a mortgage application can be pre-approved within a few days. With the growing influence of fintech on retail banking platforms, the banking sector worldwide benefits from data-driven analytics and credit-decision automation for money transfers, payment services and product recommendations to enhance customer relationships. Interestingly, however, we have seen few breakthroughs in commercial and corporate lending, which have remained largely unchanged by the technological advances since the early 2000s.

The technology lag within commercial lending stems from fundamental differences in the nature of commercial and consumer credit. Consumers are both far more numerous than companies and, by and large, financially simpler, with financial characteristics easily categorised and quantified. It is therefore no surprise that consumer credit data has long been highly standardised and readily available in machine-readable form. Commercial financial data, on the other hand, has heretofore been collected largely

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