The most significant and rapidly expanding fintech services in Nepal are provided by several fintech firms. Customer satisfaction must be compared side by side even if every organization has made an effort to expand the usage of services. Many studies have concentrated on evaluating the impact of various factors on customer satisfaction, but significantly fewer studies have been conducted to explore the factors and focus of machine learning. Based on the planned behavioural theory (TPB), the study is concentrated on exploring and evaluating customer satisfaction on a different stimulus offered by F1 Soft (a fintech firm in nepal), customers’ loyalty and the compatibility they gain through the company’s services. By exploring various factors affecting customer satisfaction by using principal component analysis (PCA) and explainable AI (XAI), the study explored the eight factors (customer service, compatibility, ease of use, assurance, loyalty intention, technology perception, speed and firm’s innovativeness) which affect customer satisfaction individually. Furthermore, by using support vector machine (SVM) and logistic regression (LR), the major contributing factors are explained with local interpretable model-agnostic explanation (LIME) and Shapley additive explanations (SHAP). SVM holds the training accuracy of 89.13% whereas LR achieves 87.88%, and both algorithms show that compatibilty issues consider the major contributing factor for customer satisfaction. Contributing toward different dimensions, determinants, and the results of customer satisfaction in fintech, the study suggests how fintech companies must integrate factors affecting customer satisfaction in their system for further process development.

Capital structure is the combination of long term sources of funding i.e. preferred stock, common stock and long – term debt. Those are used to finance the firm. Capital structure analysis is the basis for analyzing the usefulness of accumulation from different sources of capital composition of capital is another factor, which affects the profitability. Loan capital dominant enterprises have less chance for prosperity despite of their huge profits.Capital structure decision is an important financial effect of capital on profitability and value of the firm. The present study will try to analyze and examine the capital structure of the commercial banks in Nepal. This article compares the capital structure of NIBL, NABIL, HBL, EBL and SBI five commercial banks which are currently operated as ‘A’ class banks in Nepal. It evaluates the capital structure and concludes that the total debt ratio of entire five banks is fluctuating. In order to compare the variables financial analysis, leverage analysis and correlation have been used as analytical tools. The conclusion is drawn on the basis of the total proportion of debt and equity capital of the institutions dealing with the problems in terms of capital formation and their overall effects and difficulties in its implementation.

Purpose- The objective of this study is to identify the factors that influence investors' perceptions and investment decisions by examining investment objectives (IO), Investment Returns (IR), investment structure (IS), and Investment Horizon (IH) on Investment Decisions (ID) for mutual fund investments in Nepal. This study seeks to provide valuable insights for fund managers, investors, and policymakers in the Nepalese mutual fund market. Design/Methodology/Approach- Data from 386 Nepalese mutual fund investors was collected quantitatively using a structured questionnaire. Analytical statistical approaches were utilized in structural equation modeling using AMOS. Path and mediation studies explored investment goals, returns, structure, horizon, and choices. Validity and reliability tests like Cronbach's Alpha protected constructs. The model fit was evaluated using RMSEA, CFI, CMIN/DF and SRMR. Findings- Results reveal that all four independent factors significantly influence investing choices and investment return is a major mediator. The largest direct influences on returns were those of investing goals and investment horizon, which then shaped choices. Strong internal consistency and dependability let the model show an excellent fit. Implications- Using these realizations, fund managers may create mutual funds that complement investor objectives, hence improving fund attractiveness and performance. Policymakers may regulate mutual funds to promote transparency and good judgment. Originality/Value- This research addresses Nepal's growing mutual fund market and meets a need for data on investing factors. A detailed strategy and robust methodology give informative research on developing financial market investment behavior. Int. J. Soc. Sc. Manage. Vol. 12, Issue-2: 89-98.