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dc.contributor.authorKariuki, P.W
dc.contributor.authorNdichu Gitonga, Elizabeth
dc.contributor.authorKariuki, Samuel Nduati
dc.date.accessioned2024-02-13T14:23:18Z
dc.date.available2024-02-13T14:23:18Z
dc.date.issued2021-07-14
dc.identifier.urihttps://www.researchgate.net/
dc.identifier.urihttps://repository.kcau.ac.ke/handle/123456789/1504
dc.description.abstractPredictive analytics is concerned with the prediction of future trends and outcomes. The approaches used to conduct predictive analytics can be classified into machine learning techniques and regression techniques. This study dteremined the influence of fintech predictive modeling on performance of investment firms in Kenya. The study population was 57 investment firms. The study employed mixed method research design by incorporating descriptive and explanatory research designs. Data was collected using questionnaires and an in-depth interview guide. Coefficient of fintech predictive modeling has a positive and significant effect on performance of investment firms. The study concluded that fintech predictive modeling allows investment firms to forecast business growth and customer behaviour chnages. It is important for an investment firm to be able to understand business growth by accurately forecasting future growth and survival. Moreover, it is of vital necessity to understand changes in customer buying/consumption behavior so as to develop products and services that suit their needs and preferences. As a result, predictive modeling is required to project future business growth and changes in customer consumption pattern.en_US
dc.language.isoenen_US
dc.publisherWebologyen_US
dc.subjectFintech Predictive Modeling, Performance of Investment Firms, Kenyaen_US
dc.titleFintech Predictive Modeling and Performance of Investment Firms in Kenyaen_US
dc.typeArticleen_US


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