Big Data Analytic Dynamics and Performance of Fintech Firms in Nairobi City County, Kenya
| dc.contributor.author | Ogutu, Anne Adhiambo | |
| dc.date.accessioned | 2024-08-05T08:27:39Z | |
| dc.date.available | 2024-08-05T08:27:39Z | |
| dc.date.issued | 2024-05 | |
| dc.description | A Research Project Submitted to the School of Business, Economics and Tourism in Partial Fulfilment for the Award of Degree in Master of Business Administration (Management Information Systems) of Kenyatta University. May, 2024 Supervisor David M. Nzuki | |
| dc.description.abstract | The rapid evolution and integration of big data analytics within financial technology (fintech) firms present both opportunities and challenges in optimizing performance and operational dynamics. While big data analytics has potential to enhance decisionmaking, customer personalization, risk management and operational efficiency, there is a lack of comprehensive understanding of how these technologies directly influence the overall performance metrics specifically, the revenues and return of investment. Additionally, regulatory compliance remains underexplored. This research seeks to address the gap by systematically analyzing the dynamics of big data analytics adoption and its performance implications within fintech firms. The objectives of the study were to determine the effect of big data characteristics dynamics, big data component dynamics, big data technologies dynamics and the moderation role of regulatory policies in the performance of Fintech firms in Nairobi Kenya. Technology acceptance theory, innovation diffusion theory, and resource-based view were used. Descriptive research design was applied. Managers of Fintech enterprises in Nairobi City County were the target population, with 64 Fintech firms serving as the unit of observation. The sample size was 55 Fintech firms operating in Nairobi City County as determined using Yamane’s formula. Primary data was used in the study which were collected using open ended and close ended questionnaire. The study established those big data characteristics dynamics significantly influenced Financial Performance (β=0.428; p=0.002). Big data components dynamics significantly contributed to Financial Performance of Fin tech firms (β=0.288; p=0.030). The study established a significant effect of Big Data technologies Dynamics on Financial Performance of Fin tech firms (β=0.239; p=0.034). Regulatory policies significantly influence Financial Performance of Fin tech firms. The study concludes that the dynamic nature of big data analytics enables businesses to collect and analyze volumes and variety of data at great velocities. This allows accurate outcome predictions, improve decision-making bringing significant improvement in revenues, profit and return of investment. Actionable insights are produced by the variety of big data that is the outcome of aggregation from numerous sources. Big data is gathered from social media, transactional data and machine data are used by the businesses to derive the value. Artificial intelligence has largely contributed significantly to automation, wise decision-making, and improved customer experience. The block chain technologies have significantly increased trust, security, transparency, and traceability of shared data across business networks and have brought new efficiencies with cost savings. Finally, the absence of a regulatory framework for fintech negatively impacts their performance. Performance of the fintech industry is significantly impacted by data privacy regulations. The study recommends that businesses need to leverage big data analytics dynamics to analyze the variety of big data from multiple sources and offer actionable insights to enhance performance and remain competitive. For organizations to generate value, it is advised that they collect data from social media, transactional data, and machine data. It is recommended that firms focus on artificial intelligence and block chain technologies in data mining. This provides a reliable insight into the current market and consumer characteristics. According to the report, regulatory bodies should ensure that FinTech firms operate on an equal playing field to achieve excellent organizational performance. It is important to establish a significant policy concern addressing legislative limitations and competitiveness. Big data analytics ecosystem is dynamic in propelling performance in FinTech firms. A study could be conducted to establish the effect of data security on Fintech performance since it was not part of the inputs of the study. | |
| dc.description.sponsorship | Kenyatta University | |
| dc.identifier.uri | https://ir-library.ku.ac.ke/handle/123456789/28586 | |
| dc.language.iso | en | |
| dc.publisher | Kenyatta University | |
| dc.title | Big Data Analytic Dynamics and Performance of Fintech Firms in Nairobi City County, Kenya | |
| dc.type | Thesis |