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    Fintech Predictive Modeling and Performance of Investment Firms in Kenya

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    Date
    2021-07-14
    Author
    Kariuki, P.W
    Ndichu Gitonga, Elizabeth
    Kariuki, Samuel Nduati
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    Abstract
    Predictive 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.
    URI
    https://www.researchgate.net/
    https://repository.kcau.ac.ke/handle/123456789/1504
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    • School of Graduate Studies and Research [15]

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