Software Technology / IT · REF. TA-5770
Design and Implementation of a Generative AI-Based Mobile Banking Applications
Abstract
This study investigates the subject matter outlined in the title above through a structured research design appropriate to its academic level. Using primary and/or secondary data collection methods, the research examines the underlying variables, tests relevant hypotheses, and presents findings with implications for practice and policy. This is placeholder abstract text generated for catalogue preview purposes; the full document contains a complete, topic-specific abstract, literature review, methodology, data analysis, and conclusion.
Chapter One — 1.1 Background to the Study
Organizations that depend on mobile banking applications are under increasing pressure to modernize, and Generative AI has emerged as one of the more promising avenues for doing so, given its demonstrated impact in related domains.
Despite this potential, many existing mobile banking applications were not originally designed with generative AI in mind, resulting in persistent gaps in predictive maintenance that limit their overall effectiveness. This study examines how Generative AI can be applied to help close that gap.
1.2 Statement of the Problem
Existing approaches to predictive maintenance within mobile banking applications remain largely reactive and fragmented, with little systematic use of generative AI despite its demonstrated value elsewhere. This study addresses the resulting gap by designing and evaluating a solution built specifically around generative AI.
1.3 Objectives of the Study
- To design and implement a generative AI-based approach to improving predictive maintenance in mobile banking applications.
- To evaluate the effectiveness of Generative AI in enhancing predictive maintenance within mobile banking applications.
- To identify the key requirements and constraints relevant to deploying generative AI in this context.
- To assess user and stakeholder perception of the resulting system.
1.4 Research Questions
- How can generative AI be applied to improve predictive maintenance in mobile banking applications?
- How effective is Generative AI at enhancing predictive maintenance within mobile banking applications?
- What requirements and constraints are relevant to deploying generative AI in this context?
- How do users and stakeholders perceive the resulting system?
1.5 Significance of the Study
Beyond its immediate technical contribution, this study offers value to organizations evaluating whether to invest in generative AI for their own mobile banking applications, and contributes to the broader literature on applied software technology / IT by documenting a concrete implementation and evaluation case.
1.6 Scope of the Study
The study is limited to the design, implementation, and evaluation of a generative AI-based approach to improving predictive maintenance within mobile banking applications. Reflecting its clearly defined scope, it does not extend to a full commercial rollout or long-term post-implementation review beyond the study period.
Chapters Two through Five, references and appendices are available for a one-time fee of ₦75,000.
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