Calibrating appropriate trust of non-expert users in artificial intelligence (AI) systems is a challenging yet crucial task. To align subjective levels of trust with the objective trustworthiness of a system, users need information about its strengths and weaknesses. The specific explanations that help individuals avoid over- or under-trust may var...
Krisciukaityte, KarolinaBalezentis, TomasStreimikiene, Dalia
Efficiency generally translates to better financial performance and profitability and, thus, is often taken into account when analyzing activity of the banking sector. The sustainability approach adds social and environmental effects to the economic ones. Even though there have been studies on the different facets of the sustainable banking and its...
Arenas, LauraGil-Lafuente, Anna MaríaBoria Reverter, Josefa
This paper uses the case of Spain to investigate whether and how disruptive technology impacts banking stock returns under a high volatility regime and a low volatility regime. For this purpose, a two-factor model with heteroscedastic Markov switching regimes has been applied. The results indicate that disruptive technologies have an impact on Span...
One of the main sectors that makes heavy use of the development of advanced computational methods is the banking sector. The goals of our research are as follows: 1) to compare scientific and regulatory approaches to defining artificial intelligence (AI) and machine learning (ML), 2) to propose AI and ML definitions for regulatory purposes that all...
This thesis examines the impacts of technical and organizational change on the geographies of finance via infrastructure for cross-border payments, employing a qualitative methodology of semi-structured expert interviews. The study finds that SWIFT’s messaging system together with the correspondent banking system, a decentralized global network of ...
