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IMPACT OF RAFIKI AS AN ARTIFICIAL INTELLIGENCE OF ECO BANK TOWARDS BANKING AND OPERATIONS IN NIGERIA

IMPACT OF RAFIKI AS AN ARTIFICIAL INTELLIGENCE OF ECO BANK TOWARDS BANKING AND OPERATIONS IN NIGERIA

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IMPACT OF RAFIKI AS AN ARTIFICIAL INTELLIGENCE OF ECO BANK TOWARDS BANKING AND OPERATIONS IN NIGERIA

Chapter one

INTRODUCTION

Background to the Study
Business performance is critical for anticipating, determining, and evaluating the pace or amount of growth and results in business organisations. A corporation’s performance, whether financial or otherwise, acts as a standard against which corporate stakeholders can evaluate the organization’s efficacy, efficiency, total productivity, and profitability.

Business-minded stakeholders have noticed an influx of sophisticated technologies, mechanisms, and inventions aimed at improving business performance, supplanting business operations with human deficiencies, and introducing new ways of doing things, which are embedded in current Artificial Intelligence issues, to stimulate and augment a firm’s performance.

Emerging technologies are considered to have the potential to revolutionise human lives and economic practices around the world. It is critical to investigate both the possibilities and limitations of machine intelligence, as well as the possible impact on human life, society, and industry. (Koopmans et al. 2018).

Though the term “artificial intelligence” is so broad that it is difficult to define simply, it typically refers to a set of modelling techniques that combine one or more of the following:

large data sets, unconventional (i.e., unstructured and changing) data, demonstrating complex relationships between variables, opaque (“black box”) models, and models with rapidly changing structures over time (Koopmans et al., 2018).

Banks are adopting AI models to better and accelerate decision-making, which will help them increase revenue or reduce costs. Financial institutions have built models in a variety of areas, including customer segmentation

fraud detection, price optimisation, compliance monitoring, and loss forecasting, using approaches such as clustering algorithms, deep neural networks, and sentiment analysis (Koopmans et al., 2018).

The Financial Stability Board (2017) defines financial technology as “technologically enabled financial innovations that may lead to new business models, applications, processes, or products with a material effect on financial markets and institutions, as well as the provision of financial services.”

This advancement in technology is also spurred by the vast number of data from customers and market participants, with the automation and digitization of fi Clearly, data explosion is the primary enabler (Koopmans et al. 2018).

The potential applications of AI in banking are immense, and we believe they will become more obvious in the coming years. According to International Data Corporation study, businesses will continue to invest extensively in AI solutions in the coming years, with a compound annual growth rate of 54.4% projected through 2020. (Ramdani, Marliani, and Rahman, 2019).

Artificial intelligence will enable financial services organisations to completely reinvent how they work, generate cutting-edge goods and services, and improve client experiences (Ramdani, Marliani, & Rahman, 2019).

As a result, these advancements have resulted in the development of artificial intelligence (AI). According to this viewpoint, businesses are very much a part of the technology and inventions that appear to be the fundamental factor driving a greater standard of life in the modern world.

They are not isolated, nor are they in a bubble. The scientific and technological discipline of artificial intelligence (AI) aims to produce computers that can think, see, hear, walk, talk, and, most intriguingly, feel like humans.

Artificial intelligence focuses on the development of computer abilities that are often associated with human intellect, such as thinking, learning, and problem-solving (Ramdani, Marliani, & Rahman, 2019).

Intriguing questions surround the potential existence of intelligent thinking computers. Alan Turing, a British AI pioneer, proposed a test to evaluate whether robots could think in 1950.

According to the Turing test, a computer can demonstrate intelligence if a human interviewer dealing with an unseen person and an unseen computer cannot discriminate between the two under the same conditions (Ramdani, Marliani, & Rahman, 2019).

Intelligent robots and cutting-edge technologies have radically altered business change. These machines are designed to perform operations that were previously only possible for humans with specialist knowledge, unique abilities, and extensive training.

Currently, the contemporary era and corporate world represent the most exciting period in human history. Inventions, ideas, and technological improvements are happening at a rapid pace.

Specialised security cameras, workplace robots, self-driving automobiles, commercial machines, and many more are rapidly becoming ubiquitous, ushering in some of the technological improvements enabled by the growth of artificial intelligence (Farhi, 2017).

Self-driving cars, specialised security cameras, workplace robots, and many other technological advancements made possible by the growth of artificial intelligence are gradually becoming commonplace (Farhi, 2017).

According to research, technological advancements can interact with labour to increase employment in some industries and vocations while decreasing it in others.

This reflects a significant advancement since the turn of the century (Adeyemi, Ola, and Oyewole, 2018). Although the main purpose of AI was to replace human labour and boost efficiency by lowering labour costs, the emphasis has shifted to increasing collaboration between humans and machines (Akkucuk & Teuman, 2019).

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