2020
DOI: 10.4236/jcc.2020.811010
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Implications of Implementation of Artificial Intelligence in the Banking Business with Correlation to the Human Factor

Abstract: Banks daily interact with a vast number of customers and are still depending on a legacy system. With today's advances in technology, regarding lifting almost all processes to automation, from start of production to finish, there is a need for revolution in archaic monetary management institutes. By not being in tune with the contemporary trends and times, banks are losing on an opportunity to transform some of their business models and relieve humans of repetitive work, prevent frauds, make better decisions a… Show more

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Cited by 6 publications
(2 citation statements)
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“…The research conclusions were focused on how the banking sector expands on three key research areas in which AI algorithms are used: customer, strategy, and processes. Ris et al [31] present in their research the fact that with today's technological advances, with the automation of processes, banks must adapt to the evolution in order not to lose the opportunity to transform their business models and to prevent certain risks such as bank fraud. They concluded that the automation process in the banking sector, along with the use of AI algorithms, can improve the performance of the banking business process.…”
Section: The Stage Of Knowledge In the Fieldmentioning
confidence: 99%
“…The research conclusions were focused on how the banking sector expands on three key research areas in which AI algorithms are used: customer, strategy, and processes. Ris et al [31] present in their research the fact that with today's technological advances, with the automation of processes, banks must adapt to the evolution in order not to lose the opportunity to transform their business models and to prevent certain risks such as bank fraud. They concluded that the automation process in the banking sector, along with the use of AI algorithms, can improve the performance of the banking business process.…”
Section: The Stage Of Knowledge In the Fieldmentioning
confidence: 99%
“…Financial institutions should proactively deploy representative and diverse datasets while developing AI algorithms to handle bias issues. Regular assessments and audits of these algorithms are important for rectifying and identifying biases, thus promoting equitable authentication practices [29].…”
Section: • Potential Biases In Ai Algorithms For Biometric Authentica...mentioning
confidence: 99%