Advancing business performance through data-driven process automation: A case study of digital transformation in the banking sector

Adetumi Adewumi 1, *, Somto Emmanuel Ewim 2, Ngodoo Joy Sam-Bulya 3 and Olajumoke Bolatito Ajani 4

1 Independent Researcher, Chicago, Illinois, USA.
2 Independent Researcher; Lagos Nigeria.
3 Independent Researcher, Abuja, Nigeria.
4 Newcross Exploration and Production Limited, Nigeria.
 
Review
International Journal of Multidisciplinary Research Updates, 2024, 08(02), 012–022.
Article DOI: 10.53430/ijmru.2024.8.2.0049
Publication history: 
Received on 28 August 2024; revised on 05 October 2024; accepted on 08 October 2024
 
Abstract: 
This review paper examines the impact of data-driven process automation on business performance within the banking sector, emphasizing its role in enhancing operational efficiency, customer experience, and profitability. The paper explores how automation technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA) are transforming traditional banking processes by streamlining operations and enabling more personalized services. A comparative analysis highlights the advantages of automated systems over conventional methods. It acknowledges potential challenges, such as job displacement and cybersecurity risks. The paper concludes with strategic recommendations for banks seeking to adopt or enhance automation technologies. It suggests areas for future research, including the long-term effects of automation on the workforce and the integration of emerging technologies like blockchain.

 

Keywords: 
Data-Driven Process Automation; Banking Sector; Artificial Intelligence; Operational Efficiency; Customer Experience
 
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