Difficult decisions in uncertain times: AI and automation in commercial lending

Sean Hunter and Onur Güzey
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Sean Hunter: OakNorth Analytical Intelligence, UK
Onur Güzey: OakNorth, UK

Journal of AI, Robotics & Workplace Automation, 2021, vol. 1, issue 1, 63-69

Abstract: Progress in artificial intelligence (AI) and automation has improved many parts of financial services. These techniques have struggled, however, to make inroads in many areas of commercial lending, largely because of the relative unavailability of sufficient data. Traditional techniques of extrapolation from historical data are also inadequate in times of significant disruption (such as the COVID-19 pandemic). In this paper we discuss these challenges and present techniques such as driver analysis, nowcasting and the use of AI to enable granular subsector classification and forecasting. These allow greater use of data-driven AI-augmented decision making even where full decision automation is not necessarily possible or desirable. Finally, we examine the case study of OakNorth Bank in the UK, which has used these techniques to achieve very promising results since its launch in 2015.

Keywords: nowcasting; commercial lending; driver analysis; small to medium enterprises (SME) (search for similar items in EconPapers)
JEL-codes: G2 M15 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:aza:airwa0:y:2021:v:1:i:1:p:63-69

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