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

Adam Chwila

doi:10.18778/0208-6018.362.04

Autor

Adam Chwila University of Economics in Katowice, Katowice, Poland https://orcid.org/0000-0003-4671-4298

DOI:

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

Słowa kluczowe:

sztuczna inteligencja, uczenie maszynowe, etyka, bankowość, wyjaśnialność AI, regulacje

Abstrakt

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.

Pobrania

Brak dostępnych danych do wyświetlenia.

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