Impacts of Artificial Intelligence Technology to Customer Credit Evaluation in Banking and Finance Industry

EasyChair Preprint 8076

Abstract

This paper aims to review previous literature related to the application of artificial intelligent (AI) technologies in finance. The method of systematic literature associating the topics of AI Technology and customer credit evaluation is utilised. Based on the review, several key findings were identified. Firstly, the importance of credit evaluation can be recognised from the Key of AI technologies in the financial sector. Secondly, the contributions of AI are mainly in the optimisation of the credit evaluation system, which can significantly reduce the risks and costs that need to be considered in the financial sector. Thirdly, potential limitations of AI include that it is not subject to human intervention; therefore, AI is unable to analyse customer information without considering the customer's emotional and behavioural issues, which leads to mistrust and resistance to AI from customers. Moreover, banks or financial institutions cannot hold AI accountable when its analysis is flawed or faulty. In the event of specific risks, the first responsible party cannot be found. However, there are limitations of this research, for example it does not incorporate empirical evidence. Therefore, future research is needed to obtain data related to AI in finance through observation and experimentation. Research hypotheses could then be formulated and tested to investigate this research question further.

Keyphrases: Artificial Intelligence, Banking and Finance Industry, credit evaluation

@booklet{EasyChair:8076,
  author    = {Lingran Xu and Sam Chu},
  title     = {Impacts of Artificial Intelligence Technology to Customer Credit Evaluation in Banking and Finance Industry},
  howpublished = {EasyChair Preprint 8076},
  year      = {EasyChair, 2022}}