Output volatility in Nigeria : does financial development absorb trade-led shocks?

Abstract

Purpose: This paper is aimed to define Artificial Intelligence (AI), its related technologies, and its current and future applications in banking sector. It also focusses on how AI and machine learning will be the backbone of banking in the future. It is an important area of study because within the financial services sphere, established institutions are struggling to compete as legacy systems have become outdated, inflexible with reduced efficiency. Design/Methodology/Approach: This is a review paper and explores various trends that could pave way for furtherenace of technological interventions through the use of AI. Findings: Banks are trying to potentially harness the power of AI to streamline the existing processes and introduce new features that will improve the customer experience. A stage has been reached where it is potentially equipped to provide solutions to some of the existing problems in banking. It is being developed into a wide range of technologies, including robotic process automation (RPA), natural language processing (NLP), advanced data analytics, Big Data analytics and image analytics and their use will help banks improve front-office, mid-office and back-office processes. Practical Implications: These approaches will have a landmark impact on the nature of relationship management has with the employees and banks have with their customers. Originality/Value: There is a significant scope for application of various processes based on what has been found. It is an original content with proper references.