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Does it matter who rejects me? Human vs AI decision-making in banking
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Orientador(es)
Resumo(s)
Artificial Intelligence systems allow business decision-making based on statistical analysis and
recommendations – moreover, autonomous AI can decide and execute a decision by itself. Historically,
financial institutions conduct risk assessments before lending money. This assessment is based on
mathematical models. Therefore, applying AI to develop and apply a model seems a natural step to
decrease costs and reduce default rates. By conducting two experiments and analyzing the data
through two-way ANOVA, mediation analysis, and moderated mediation analysis, we found out that
the impact of the decision-maker on customer satisfaction varies according to the credit product. For
personal loans (Study 1), the rejection by an AI causes less dissatisfaction than a rejection by a credit
analyst - this relationship is mediated by the Perceived Role Congruity. The more the bank fulfills its
role, the higher the satisfaction. For credit cards, the decision-maker is indifferent. However, the
relationship between the bank response (approval/rejection), role congruity, and satisfaction is
maintained. In Study 2, we also discovered that a person's Rejection concern determines if they will
have a more extreme perception of role congruity (high concern) or less extreme (lower concern) for
both bank responses.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Marketing Research and CRM
Palavras-chave
Artificial Intelligence Role Congruity Satisfaction Retail Banking Rejection Concern