Browsing by Author "BRENDA WANGUI MUCHIRI"

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    ARTIFICIAL INTELLIGENCE-BASED BUSINESS MODELS AND FINANCIAL PERFORMANCE OF LISTED FIRMS IN THE NAIROBI SECURITIES EXCHANGE
    (THE CATHOLIC UNIVERSITY OF EASTERN AFRICA, 2025-09) BRENDA WANGUI MUCHIRI
    AI enables a systematic mechanism which allows businesses to gather more valuable and updated data to carry out accurate evaluation of market environment and internal operations simultaneously. AI is thus advantageous to firms as it allows them to apply AI driven decision making on sales and credit forecast. However, despite the growth of opportunities associated with the use of AI, external factors and market volatility pose significant risks to the performance of firms listed at NSE. The investigation thus sought to determine the effect of AI-based business models on financial performance of listed entities in NSE. Specifically, the study determined the effect of AI-based predictive financial modelling, AI-based risk management, AI-based portfolio optimization and AI-based fraud detection on financial performance of listed firms in NSE. The investigation was anchored on diffusion of innovation theory, Technology-Organization-Environment and technology acceptance model. Positivism was employed with correlational research design as the study design. The target population of were the 17 financial firms listed at NSE. Listed firms were the unit of analysis while the unit of observation were the heads of marketing departments, business development department, human resource departments and operations department within the 17 financial firms listed at NSE. Since the target population is relatively small, the investigation conducted a census of all the respondents. Structured questionnaire was to collect primary data. SPSS software was used in the analysis of data. Data analyses involved both descriptive and inferential outcomes which were presented in form of tables and charts. Inferential analysis included correlation and multiple regression analysis. From the results, the investigation established that AI-Based predictive financial modelling showed a positive and significant effect on financial performance (0.321, 0.000<0.05), AI-Based risk management showed a positive and significant effect on financial performance (0.472, 0.000<0.05), AI-Based portfolio optimization showed a positive and significant effect on financial performance (0.420, 0.000<0.05) and AI-Based fraud detection showed a positive and significant effect on financial performance of firms listed at NSE (0.401<0.05). The investigation recommends that the firms listed at NSE ought to adopt AI-based predictive financial modelling as a strategic priority to enhance their financial performance as it improves the accuracy and timeliness of forecasting, budgeting and investment decisions. The listed firms under study should also prioritize the integration of AI-based risk management systems to strengthen their financial performance. The firms under study should also adopt AI-based portfolio optimization tools to enhance financial performance as it maximizes returns while effectively managing risk across diverse asset classes. The listed firms under investigation should implement AI-based fraud detection systems to strengthen financial performance. The study further recommends that ought to develop a supportive regulatory framework that encourages the adoption of AI-Business models by the listed firms under study to enhance performance.