The Application of Artificial Intelligence Models in Commercial Banks - Opportunities and Threats

• Autorzy: Adam Chwila

Warianty tytułu

Wykorzystanie modeli sztucznej inteligencji w bankach komercyjnych - szanse i zagrożenia

• Języki publikacji: EN

Abstrakty

EN

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 allow us to clearly state if a given method is AI/ML or not, 3) to compare the complex quantitative methods applied in banking in terms of complexity and interpreta- bility in order to provide a clear classification of methods to the interested parties (practitioners and management), 4) to propose a possible approach towards the further development of quantitative methods in the areas of required strict interpretability. Our literature review focuses on the definitions of AI/ML applied by scientists and regulators, as well as the proposals of application of complex quantitative solutions in different banking domains. We propose practical definitions of AI and ML based on the current state of the art and requirements of clarity in the banking industry (a very limited risk appetite regarding regulations non-compliance) and compare quantitative methods applied in different banking domains. For regulatory purposes, we propose general and inclusive definitions of AI and ML which allow for a clear classification of specific methods. In the case of strict requirements towards the interpretability of applied methods, we propose a gradual and controlled increase in the complexity of existing solutions. Therefore, we propose the differentiation of quantitative methods in terms of interpretability and complexity. We also think that the definitions of AI/ML in further regulations should make it possible to clearly say whether particular approaches are AI/ML. Our research is directed to policymakers, practitioners, and executives related to the banking sector. (original abstract)

Jednym z głównych sektorów, które w dużym stopniu wykorzystują rozwój zaawansowanych metod obliczeniowych, jest sektor bankowy. Cele badań przedstawionych w artykule to: 1) porównanie naukowego i regulacyjnego podejścia do definiowania sztucznej inteligencji (AI) i uczenia maszynowego (ML); 2) zaproponowanie definicji AI i ML na potrzeby regulacyjne, które pozwolą jednoznacznie stwierdzić, czy dana metoda jest AI/ML, czy nie; 3) porównanie złożonych metod ilościowych stosowanych w bankowości pod względem złożoności i interpretowalności w celu jasnej klasyfikacji metod dla zainteresowanych stron (praktyków i kadry zarządzającej); 4) zaproponowanie możliwego podejścia do dalszego rozwoju metod ilościowych w obszarach o wymaganej ścisłej interpretowalności. Przegląd literatury koncentruje się na definicjach AI/ML stosowanych przez naukowców i regulatorów oraz propozycjach zastosowania złożonych rozwiązań ilościowych w różnych domenach bankowości. Badania skupione są na proponowaniu praktycznych definicji AI i ML na podstawie aktualnego stanu wiedzy i wymogów przejrzystości w branży bankowej (bardzo ograniczony apetyt na ryzyko, dotyczący niezgodności z regulacjami) oraz na porównaniu metod ilościowych stosowanych w różnych domenach bankowości wraz z ich oceną. Autor proponuje ogólne i inkluzywne definicje AI i ML na potrzeby regulacyjne, które pozwalają jednoznacznie sklasyfikować konkretne metody. W przypadku zaostrzonych wymagań dotyczących interpretowalności stosowanych metod proponuje stopniowe i kontrolowane zwiększanie złożoności istniejących rozwiązań. Z tego powodu przedstawia ocenę metod ilościowych pod względem interpretowalności i złożoności. Autor uważa również, że definicje AI/ML w dalszych regulacjach powinny umożliwiać jednoznaczne zaklasyfikowanie konkretnych podejść jako AI/ML. Badania skierowane są do twórców regulacji, praktyków i kadry zarządzającej związanej z sektorem bankowym. (abstrakt oryginalny)

Słowa kluczowe

EN

Artificial intelligence; Machine learning; Ethics; Banking; Commercial banks

PL

Sztuczna inteligencja; Uczenie maszynowe; Etyka; Bankowość; Banki komercyjne

• Czasopismo: Acta Universitatis Lodziensis. Folia Oeconomica
• Rocznik: 2023
• Numer: vol. 1, t. 362
• Strony: 63--98

Twórcy

autor

Adam Chwila

• University of Economics in Katowice, Poland

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Identyfikatory

DOI

https://doi.org/10.18778/0208-6018.362.04