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1
Gökalp, Ebru, and Onur Demirörs. "Model based process assessment for public financial and physical resource management processes." Computer Standards & Interfaces 54 (November 2017): 186–93. http://dx.doi.org/10.1016/j.csi.2016.11.011.
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Xiuqiong Yang, Xiuqiong Yang. "Financial Risk Assessment Model Based on Fuzzy Logic." Journal of Electrical Systems 20, no. 1 (2024): 192–205. http://dx.doi.org/10.52783/jes.676.
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In the rapidly evolving landscape of business operations, establishing a robust security domain prevention system in the Middle Office is of utmost importance. To achieve this, the integration of Choquet expectation-based methodologies offers a powerful approach. The Middle Office acts as a critical hub for various business processes, including risk management, compliance, and data protection. With the implementation of Choquet expectation theory, which encompasses the combination of multiple criteria and preferences, businesses can effectively assess and optimize their security domain prevention system. The establishment and optimization of a security domain prevention system based on Choquet’s expectations provide businesses with a comprehensive and tailored approach to protect their critical assets, maintain operational continuity, and safeguard sensitive data from emerging threats in the Middle Office environment. This paper constructed a Fuzzy Optimization Membership Estimation (FOME) for the computation of the feature vector. The proposed FOME model uses the Flemingo Optimization model for the evaluation of the feature vector in the business middle office. The FOME model effectively computes the Choquet expectation features for the analysis of the risk management of the feature vector in the middle office. Through the membership estimation with the FOME model, the model significantly computes the different attacks in the middle office. The analysis of the proposed FOME is evaluated for the conventional CICIDS dataset for the attack analysis. The simulation analysis stated that the proposed FOME model achieves a higher classification accuracy of 99.89% for attack detection.
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Zarina, Poberezhna. "Comprehensive approach to the efficiency assessment of the business model of the aviation enterprise based on business process innovation." Eastern-European Journal of Enterprise Technologies 5, no. 13 (113) (2021): 44–57. https://doi.org/10.15587/1729-4061.2021.243118.
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The improvement of theoretical and methodological approaches to the formation of innovativeness of business processes of enterprises has been carried out. A model of innovativeness of business processes has been formed, which takes into account the principles, goals, methods of improving the management of business processes and the factors of influence on them. The main directions of the formation of an effective business model of an aviation enterprise based on the innovativeness of business processes are investigated and strategic directions of its provision are proposed. At the same time, the following aspects of enhancing the innovative activity of an aviation enterprise are highlighted as: the influence of the external and internal environment, innovative activity, analysis of the innovative potential and innovativeness of business processes. An integrated approach to assessing the effectiveness of the business model of an aviation enterprise based on the innovativeness of business processes has been formed. This approach allows to provide the necessary level of innovative flexibility of the aviation enterprise and independence in the application of innovative business processes. The author has carried out a practical implementation of the applied approach at aviation enterprises. The study made it possible to identify the most important business processes for aviation enterprises. These include: the level of support (provision) of innovation, the turnover ratio of current assets, the provision of material and technical resources. As a result of the assessment, these business processes have the highest scores (4.55; 4.43 and 4.26, respectively). The assessment of the financial stability of aviation enterprises in the market was carried out and the indicators of the assessment were calculated. An integral indicator of the financial stability of aviation enterprises has been determined, according to which the problems of the effective functioning of Ukrainian aviation enterprises have been identified. At the same time, small aviation enterprises suffer losses and are characterized by a low level of financial stability
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Ma'ruf, Aminudin, and Khairunnisa Nurul Fikri. "Ethical Dimensions of Islamic Finance: Lessons from the CSR Model of Indonesian Islamic Banks." Journal of Islamic Economics and Finance Studies 4, no. 1 (2023): 1–13. http://dx.doi.org/10.47700/jiefes.v4i1.5823.
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The Islamic financial system is regarded as a financial system that bases its operations on the valuesof Islam. However, the practice of the Islamic financial industry has been criticized as it deviates fromthe theory. This paper aims to explore and analyze the ethical values of Islamic finance and theirimplementation in Indonesian Islamic commercial banks. The study employs a qualitative researchmethod with the literature study approach and assessment of the annual reports of 14 IndonesianIslamic commercial banks. The literature study explores and analyses Islamic values embedded withinthe Islamic financial system. In contrast, the exploration and assessment of Indonesian Islamiccommercial banks’ annual reports provide the study with the practical implementation of the values.The paper found that Indonesian Islamic commercial banks have contributed to facing the currentsocial and environmental issues through some initiatives in their CSR implementations. All IndonesianIslamic commercial banks have been actively participating in CSR programs. However, a number ofIslamic banks need to enhance their CSR practices to tackle the ongoing environmental issues.Therefore, the paper comes with some limitations and policy recommendations.
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Olena, Bondarenko, Palyvoda Olena, and Kyrylenko Oksana. "DEVELOPMENT OF A MODEL FOR THE ESTIMATION OF FINANCIAL PROCESSES IN LOGISTIC SYSTEMS AT INDUSTRIAL ENTERPRISES." Eastern-European Journal of Enterprise Technologies 5, no. 1 (95) (2018): 6–16. https://doi.org/10.15587/1729-4061.2018.142628.
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The model and the method for assessment of the effectiveness of management of financial processes in logistic systems of industrial enterprises were substantiated. The model takes into consideration the parameters of financial flows and their cumulative effect on overall efficiency. The method was developed based on calculation of the integral index by the criteria of liquidity, balance, intensity, and sufficiency of financial flows, taking into consideration the structure of factor features. The groups of factors were generated based of the methods for data standardization and actualization, which determine the key criteria for the management of financial processes at industrial enterprises under conditions of logistication of economy. The economic content of correlation dependences between the latent factors and their variables was interpreted. The level of influence of the key criteria on the general state of management of financial processes in logistic systems was determined with the use of the methods of taxonomy. The formula of calculation of the integral index was proposed in order to ensure a reliable assessment of the final state of the management of financial processes (high, medium, low, rather low). The permissible limits of its fluctuations were established by the method of the Shewhart control charts. The application of the model provides the design of objective recommendations regarding decision-making on the regulation of the corresponding indicators in the context of the selected key criteria. The software IBM SPSS Statistics (Russia) was used for the calculations, which makes it possible to analyze the values of arrays of information and level the errors in justifying decisions. The proposed model can be useful for economic entities in the international format. It opens up additional possibilities for evaluation, taking into consideration the life cycle of an enterprise, industrial tendencies, the stage of logistication of the world economy
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Stehnei, Marianna, Inna Irtyshcheva, and Halyna Mykhalchynets. "DEVELOPMENT OF THE FINANCIAL MARKET: DESTABILIZING PROCESSES, THEIR ASSESSMENT, AND GLOBAL IMPACT." Baltic Journal of Economic Studies 8, no. 5 (2022): 176–83. http://dx.doi.org/10.30525/2256-0742/2022-8-5-176-183.
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The subject of the study is the process of destabilization of the financial market of Ukraine in modern conditions. Methodology. The research used general scientific methods, in particular: theoretical generalization, methods of positive and normative analysis, and statistical analysis. The goal is to assess the processes of destabilization of the financial market of Ukraine in modern conditions. Research conclusion. For the formation of command information oriented to the production of effects in current conditions, it is necessary to provide in mathematical logic: 1) a comprehensive study of static (permanent) characteristics of the financial market as a hierarchically ordered combinatorial system; 2) research of existing trends in the development of the financial market of Ukraine according to the elements of its combinatorial structure; 3) specification of critical problems and obstacles to the development of the financial market (according to the elements of its combinatorial structure), which may negatively affect the performance of the financial market. The financial market of Ukraine is a complex structure characterized by constant structural changes. Currently, the financial market of Ukraine is characterized by somewhat contradictory trends of its development, taking place against the background of increasing stochasticity of its environment. Naturally, it is necessary to create opportunities to estimate and forecast the flows of financial resources and changes in the financial market associated with these flows by building a complex of models that provide 1) forecasting possible behavioral reactions of the integrated performance of the financial market on the basis of existing trends in changes in the value characteristics of assets under the influence of various influencing factors in stochastic models; 2) step-by-step descriptive-numerical representation of data in dynamic programming models to identify possible changes in the structure of the financial market. It is this content of the models that is important because it not only determines the possible directions of strengthening, vulnerability and destabilization of the financial market, such a model basis increases the scientific validity of the developed strategic priorities aimed at preventing destabilization processes on the efficiency of the financial market in the future.
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Yang, Xibin. "The Application of Stochastic Processes in Financial Mathematics." Theoretical and Natural Science 79, no. 1 (2025): 54–58. https://doi.org/10.54254/2753-8818/2025.19942.
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Stochastic processes are crucial in financial mathematics, providing a framework to model the inherent uncertainties of financial markets. This paper explores stochastic process application across various financial domains, such as option pricing, risk management, and financial engineering. Through case studies, literature review, and case analysis, the study demonstrates the practical effectiveness of stochastic processes in finance. The findings highlight the adaptability and robustness of these models in capturing market dynamics and optimizing financial strategies. This research particularly focuses on the implementation of Brownian motion and Its processes in derivative pricing, revealing significant improvements in accuracy compared to traditional methods. Additionally, we examine the integration of machine learning techniques with stochastic models to enhance predictive capabilities in risk assessment. This study also addresses the challenges and limitations of current stochastic approaches, proposing innovative solutions for practical implementation. These insights contribute to both theoretical understanding and practical applications in quantitative finance, offering valuable guidance for practitioners and researchers in the field
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Rakesh Pandit, Sheetal Bawane, Jayesh Surana, Pankaj Malik, Ankita Chourasia,. "Credit Risk Assessment and Fraud Detection in Financial Transactions Using Machine Learning." Journal of Electrical Systems 20, no. 3s (2024): 2061–69. http://dx.doi.org/10.52783/jes.1807.
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Credit risk assessment and fraud detection are crucial tasks in the financial industry, vital to preserving financial organizations' legitimacy and sustainability. Traditional methods often fall short in accurately assessing risk and detecting fraudulent activities in a timely manner. In recent years, machine learning has emerged as a powerful tool for enhancing these processes, leveraging great dimensions of transactional statistics and superior algos for making more informed decisions. This research paper explores the usage of ML techniques in credit risk assessment and fraud detection within financial transactions.
 The paper begins with an overview of the importance of accurate risk assessment and fraud detection in financial transactions and introduces the role of machine learning in addressing these challenges. A comprehensive literature review is conducted to analyze existing methodologies, algorithms, and research trends in the field. Data acquisition and preprocessing techniques are discussed, emphasizing the importance of clean and relevant data for model training. Feature engineering strategies are explored to extract meaningful information from financial transaction data and enhance the predictive capabilities of machine learning models.
 Various machine learning algorithms suitable for credit risk assessment and fraud detection are examined, including LR, SVMs, RF, DTs and DNNs. The efficacy of these techniques is evaluated by discussing model metrics for assessment and ensemble approaches for boosting efficiency, with a focus on metrics such as accuracy, precision, recall, and ROC-AUC.
 The paper presents case studies and experimental results illustrating the application of machine learning models in real-world scenarios, highlighting their effectiveness in improving risk assessment and fraud detection processes. Additionally, difficulties such as imbalanced datasets, comprehensibility of the model and adherence to regulations are discussed, along with potential research directions and future trends in the field.
 In conclusion, this research emphasizes the transformative potential of machine learning in credit risk assessment and fraud detection within financial transactions. By leveraging advanced algorithms and data-driven approaches, financial institutions can enhance their decision-making processes, mitigate risks, and safeguard against fraudulent activities, ultimately contributing to a more secure and resilient financial ecosystem.
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Ali, Aijaz, Asif Saeed Naji, and Ubaid Ali. "Strategic Utilization and Factors Influencing Financial Derivatives in Pakistan's Financial Landscape." Journal of Entrepreneurship, Management, and Innovation 5, no. 3 (2023): 401–13. http://dx.doi.org/10.52633/jemi.v5i3.321.
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The purpose of this study was to investigate the derivatives usage available in Pakistan. The investigation encompassed an in-depth analysis of the diverse services offered by Pakistani financial institutions, with a focused assessment aimed at understanding the impact of these services on derivative usage. The data was gathered using a customized questionnaire. Several banks' statistical tools were used to examine the data after different users of derivatives filled out questionnaires. The study employed cross-sectional data, drawn from diverse demographic categories within a single locality, facilitating the potential replication of the model in other countries through longitudinal financial institution data. The study has several practical consequences for financial service providers that aim to grow the derivative market in Pakistan by providing high-quality services for derivatives. This research contributes to the existing literature by delineating the determinants and patterns of derivative usage in the Pakistani context, thereby establishing a cognitive motivation relationship. It uses a cognitive motivation relationship. This study is useful in the financial institutions/banking industry for a better understanding of this concept.
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Shandrivska, O., and N. Shynkarenko. "APPLIED RISK ASSESSMENT IN THE SYSTEM OF SOCIO-ECONOMIC PROCESSES IN CYBERSPACE." Journal of Lviv Polytechnic National University. Series of Economics and Management Issues 4, no. 2 (2020): 94–105. http://dx.doi.org/10.23939/semi2020.02.094.
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In the paper investigated safety of socio-economic processes in the virtual space. Studied the main trends influence on formation of preventive and adaptive mechanisms for ensuring information and cyber security enterprises. Key trends of the modern business and social environment include: globalization, informatization and individualization of consumer needs; mediatization, territorialization and universalization of social phenomena. Presented an original ensuring security model for the virtual information sphere. In this model was invented a conceptual scheme for identifying the information security system: given the identification sequence and risks assessment in cyberspace by stages; risk identification; a description of the threats it poses; identification of vulnerable market segments; analysis and assessment of the risk occurrence probability level; analysis and assessment of the risk manifestation consequences level; score determination of the general rick level; proposal to eliminate the development environment risks of the study object; net risk identification; risks in cyberspace have been identified and assessed in terms of security and financial flows. Among the dominant risks of the external and internal security environment in the information virtual Ukrainian space the following are highlighted: insufficient system security, processes and technologies, disinformation and information asymmetry; high sensitivity of financial flows to the processes of the implementation of shock macroeconomic phenomena (including almost unsignificant currencies devaluation against the pandemic background) in terms of the safety of financial flows; technical, technological and personal vulnerability growth in the information sphere, due to the increasing cybercrime in terms of the information flow security. Among the mitigation measures and neutralization of the general risk level, was proposed the creation of a single protection system. The single data protection system should be based on: data protection progressive principles, tasks to ensure security from information influences, information infrastructure security, information rights, open access to information, publicity of open information, etc.; organizational and right mechanism of data protection. This mechanism is based on the need to streamline the responsibilities of information marked actors; state control over data manipulation; data manipulation standards development; information systems certification for their processing. Construction of database registers, as well as registration of owners and/or data administrators, third parties to whom the data was transferred for further manipulation; an independent coordination center formation for the state policy implementation in terms of monitoring compliance with data protection requirements, etc.; increasing the financial flow transparency, namely risk-oriented monitoring in digital currency exchanges and licensing of transactions in virtual currencies requires support from the Financial Action Task Force on Money Laundering and the Financial Intelligence Unit.
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Maruddani, Di Asih I., Trimono Trimono, and Mas'ad Mas'ad. "IMPLEMENTATION OF STOCHASTIC MODEL FOR RISK ASSESSMENT ON INDONESIAN STOCK EXCHANGE." MEDIA STATISTIKA 15, no. 2 (2023): 151–62. http://dx.doi.org/10.14710/medstat.15.2.151-162.
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Currently, financial assets become an alternative choice for investors in Indonesia to get maximum profits. The Indonesia Stock Exchange is the official capital market in Indonesia which is a place for trading financial assets. Stocks are listed as the most preferred financial asset by investors. In reality, stock investment is not a risk-free investment. The main risk that investors should face is the loss risk. This kind of risk can occur at any time. From that problem, this study aims to do risk assessment on the Indonesian stock market. The evaluation will be started with stock price index prediction using the Stochastic model (Geometric Brownian Motion Model and Jump Diffusion). Then, the result from that processes will be used to get loss risk prediction through the Adjusted Expected Shortfall model. By using the historical price of JKSE index from 01/08/21 to 31/08/22, Jump Diffusion is the best model to predict the JKSE index with MAPE value is 1.08%. Then, at the 95% confidence level and 1-day holding period, the expected loss risk using Adjusted Expected Shortfall model on 09/01/2022 is -0.02978.
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Brezuleanu, S., Carmen Olguţa Brezuleanu, I. Brad, T. Iancu, and A. Ciani. "Performance Assessment in Business of Agricultural Companies using Balanced Scorecard Model." Cercetari Agronomice in Moldova 48, no. 2 (2015): 109–20. http://dx.doi.org/10.1515/cerce-2015-0035.
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AbstractThe performance management is a strategic and integrated approach for long-time success of the activity of agricultural companies, by improving the performance of the organization, teams and individuals. In search of success, the performance management uses a variety of models, techniques and methods, some taken from other systems and improved and others of its own, focusing on strategy and differentiating features that provide a strong competitive advantage. The Balanced Scorecard (BSC) model identifies several dimensions of the organization, representing areas where organizations need to achieve results at department, team or individual level. According to the type of the agricultural company, there can be esential financial aspect, customers, internal processes, knowledge and learning, service quality, market share etc. The company under study, S.C. Agrocomplex Lunca Paşcani S.A., is representative in terms of ownership, farm and profile of the agricultural production in Moldavia region. According to the methodology developed, starting from the strategy of S.C. Agrocomplex Lunca Paşcani S.A. we identified the strategic objectives for each situation and the level of reaching the objectives using several indicators. In the second stage of the BSC analysis, the indicators are defined according to the management priorities of S.C. Agrocomplex Lunca Paşcani S.A. in four categories, corresponding to the four dimensions of the classical model: customer perspective, perspective of processes within the company, employee perspective and financial perspective
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Poberezhna, Zarina. "Comprehensive approach to the efficiency assessment of the business model of the aviation enterprise based on business process innovation." Eastern-European Journal of Enterprise Technologies 5, no. 13 (113) (2021): 44–57. http://dx.doi.org/10.15587/1729-4061.2021.243118.
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The improvement of theoretical and methodological approaches to the formation of innovativeness of business processes of enterprises has been carried out. A model of innovativeness of business processes has been formed, which takes into account the principles, goals, methods of improving the management of business processes and the factors of influence on them. The main directions of the formation of an effective business model of an aviation enterprise based on the innovativeness of business processes are investigated and strategic directions of its provision are proposed. At the same time, the following aspects of enhancing the innovative activity of an aviation enterprise are highlighted as: the influence of the external and internal environment, innovative activity, analysis of the innovative potential and innovativeness of business processes. An integrated approach to assessing the effectiveness of the business model of an aviation enterprise based on the innovativeness of business processes has been formed. This approach allows to provide the necessary level of innovative flexibility of the aviation enterprise and independence in the application of innovative business processes. The author has carried out a practical implementation of the applied approach at aviation enterprises. The study made it possible to identify the most important business processes for aviation enterprises. These include: the level of support (provision) of innovation, the turnover ratio of current assets, the provision of material and technical resources. As a result of the assessment, these business processes have the highest scores (4.55; 4.43 and 4.26, respectively). The assessment of the financial stability of aviation enterprises in the market was carried out and the indicators of the assessment were calculated. An integral indicator of the financial stability of aviation enterprises has been determined, according to which the problems of the effective functioning of Ukrainian aviation enterprises have been identified. At the same time, small aviation enterprises suffer losses and are characterized by a low level of financial stability
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Ke, Xiong, Lin Li, Zeyu Wang, and Guanghe Cao. "A Dynamic Credit Risk Assessment Model Based on Deep Reinforcement Learning." Academic Journal of Natural Science 1, no. 1 (2024): 20–31. https://doi.org/10.5281/zenodo.13905241.
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This study presents a new credit risk assessment model based on deep learning (DRL), addressing the limitations of static models in adapting to financial changes. The model leverages the Deep Q-Network architecture developed with the importance of replication, DQN distribution, and ring noise to capture the correlations and non-linearities in the credit data and transition to financial reform. An analysis of the extensive data of 1,250,000 credit applications shows the best performance model, achieving an AUC-ROC of 0.92 and a 15% improvement in the ratio for state-of-the-art machine learning methods. The DRL model exhibits remarkable adaptability in simulated dynamic scenarios, maintaining an average AUC-ROC of 0.89 across various economic shocks and market shifts. An ablation study reveals the significant contributions of each model component, with prioritized experience replay emerging as the most impactful for adaptability. The proposed approach offers promising implications for enhancing credit risk management practices, potentially enabling more inclusive lending while mitigating default risks. However, challenges remain in model interpretability and potential bias perpetuation, necessitating further research into transparent and fair AI-driven credit assessment systems. This study contributes to the growing body of research applying advanced machine-learning techniques to critical financial decision-making processes.
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MYKHALCHYNETS, Halyna. "FINANCIAL MARKET AS A BASIS FOR EVALUATING TRANSFORMATION PROCESSES AND FORECASTING ITS EFFICIENCY THROUGH PERFORMANCE: CLASSIFICATION AND FORMS." Herald of Khmelnytskyi National University. Economic sciences 314, no. 1 (2023): 89–93. http://dx.doi.org/10.31891/2307-5740-2023-314-1-12.
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The financial market model should be formed taking into account a clearly defined subject area and its objects, which is ensured by their classification and adequate representation in form. The described processes are significant since the type and forms of expression of the financial market form the basis for launching evaluation methods and forecasting its effectiveness through performance. The financial market classification consists of supplementing its model with the location and organization of its interrelated elements. It should be noted that for this purpose, systems for dividing objects into groups according to predetermined characteristics should be applied, in particular: 1) division of the financial market according to information about it (into groups, subgroups according to a particular characteristic); 2) allocation of logical connections between groups and subgroups of the financial market. These object distribution systems are based on the identification/construction of structures forming a combinatorial financial market model. The purpose of the article is the process of research the classification and forms of presentation of the financial market as a basis for evaluating transformational processes and forecasting their effectiveness through effectiveness. The process of researching the classification and forms of presentation of the financial market as a basis for evaluating transformational processes and forecasting its effectiveness through effectiveness is revealed. The main approaches to the classification of the financial market are characterized (by generalized, syncretic, and LOD approaches). The structuring of the financial need based on the convergence of economic relations with the transfer of ownership and the specifics of the legislative regulation of this process is essential and provides the presentation of information in terms of such components as currency market, deposit market, credit market; Securities Market; derivatives market; real estate market. The outlined approach to structuring the financial market forms a conceptual understanding of its model as a system S, which reflects the basic structures necessary to determine the objects of assessment and directions of performance forecasting through performance. To ensure the practical applicability of the conceptual model, modeling procedures, methods and algorithms must be systematically characterized.
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Bukhtiarova, Alina, Andrii Semenog, Мila Razinkova, Nataliia Nebaba, and Józef Antoni Haber. "Assessment of financial monitoring efficiency in the banking system of Ukraine." Banks and Bank Systems 15, no. 1 (2020): 98–106. http://dx.doi.org/10.21511/bbs.15(1).2020.10.
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The transformation processes taking place in the global economy and the expansion of global business ties increase the overall vulnerability of the international banking system. One of the problems related to money laundering is the process of evaluating the efficiency of financial monitoring measures. The article discusses the issues of assessing the effectiveness of financial monitoring in the banking system of the country. For Ukraine, this problem is especially relevant, because there is a bank-centric model of the financial market (about 90% of assets go through the banking system) in the country. According to official data, 50% of economic activity in Ukraine ends with money laundering. The article presents the improved method that quantifies the level of financial monitoring system effectiveness at commercial banks of Ukraine based on calculations of the integral index. The index indicates the dynamics of the financial system protection degree from the money laundering threat based on the expediency and efficiency of financial monitoring in the banking system. As a result, more comprehensive conclusions about the level of financial security of the country are made. According to assessments, in 2017–2018 the efficiency of financial monitoring of the banking system of Ukraine was at the middle level (about 64%). The proposed method can be applied to evaluate the effectiveness of the financial monitoring system in any country and become the basis for improving the anti-money laundering system through the banking system. AcknowledgmentThe study was conducted as part of state budget research of Sumy State University – Formation of a Public Finance Transparency System as a Prerequisite for Combating Corruption in Ukraine (0118U003585) (in the context of evaluating the effectiveness of financial monitoring of the Ukrainian banking system) and Formation of Tools for the Ukrainian Economy Unshadowing Based on Causal Modeling of Interaction Trajectories of Financial Intermediaries (0120U100473) (in the context of substantiating the need and directions for improving the financial monitoring system in Ukrainian banks).
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Iakobiuk, Liubov, and Marina Vinogradova. "Econometric model of the effective activity of the enterprise." E3S Web of Conferences 381 (2023): 01028. http://dx.doi.org/10.1051/e3sconf/202338101028.
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In modern conditions of globalization and growing economic instability, many enterprises cannot withstand competition and find themselves in a state of crisis. In order to carry out successful trading activities, there is a growing demand for reliable information about the future development of the organization, and therefore the most urgent problem of any enterprise is its financial stability. Using the example of an enterprise with a registered form of a limited liability company, the authors considered the assessment and analysis of the stability of the enterprise's development in order to confirm the future prospects of its functioning in the Russian markets. With the help of basic methodological approaches and principles of using the apparatus of econometric modeling and analysis of economic phenomena and processes, an assessment of the state of efficiency of a limited liability company is considered and a forecast of the development of economic phenomena and processes is made, which is an urgent task. The problem at this point in time. As a result of our research, we have determined a linear model of the dependence of indicators such as profit and cost of sales, which is statistically significant with a probability of 95% and allows us to predict the profit of a limited liability company. A comprehensive assessment of the financial condition of the company allowed us to formulate conclusions and proposals to improve the efficiency of the company.
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Xu, Tianyou. "The Application of Monte Carlo Simulation for Risk and Behavior Analysis in Financial Markets." Highlights in Business, Economics and Management 45 (December 24, 2024): 19–24. https://doi.org/10.54097/djgy6809.
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This paper explores the potential of Monte Carlo simulation techniques for analyzing risk and behavior in financial markets. The paper commences by emphasizing the inherent complexity and uncertainty of financial markets, underscoring the necessity of quantitative assessment and thus highlighting the applicability of Monte Carlo simulation in this domain. Subsequently, the fundamental principles and implementation procedures of Monte Carlo simulation are elucidated, demonstrating its indispensable function in generating vast quantities of random data to emulate the dynamic processes of financial markets. The objective is to capture market volatility, the interdependence of asset prices, and the latent impact of risk factors. The model allows the author to simulate the performance of investment portfolios under a variety of market scenarios, thereby providing quantitative evidence to support risk management. In the empirical section, the author selects a number of representative financial products and applies the proposed evaluation model to conduct a case study analysis. The paper presents a detailed analysis of the simulation outcomes, demonstrating the substantial advantage of Monte Carlo simulation in identifying potential risks in financial markets, refining investment decision-making processes, and evaluating the resilience of financial instruments. The findings of the research indicate that the assessment approach based on Monte Carlo simulation is more accurate in forecasting the likelihood of extreme market events, thereby offering financial institutions and investors more precise risk alerts. In conclusion, the article substantiates the practicality and scientific rigour of Monte Carlo simulation in financial market assessment through a synthesis of theoretical principles and empirical evidence.
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DOTSENKO, INNA, and LESYA MATVIICHUK. "MODEL OF EVALUATION OF INVESTMENT ATTRACTIVENESS OF THE ENTERPRISE." MODELING THE DEVELOPMENT OF THE ECONOMIC SYSTEMS 2, no. 2 (2021): 6–11. http://dx.doi.org/10.31891/mdes/2021-2-1.
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In the modern financial and economic conditions of business entities, ensuring the investment attractiveness of the enterprise is the key to its profitability and long-term development. The article considers the essence of investment attractiveness of enterprises. Based on the analysis of literature sources, the concept of investment attractiveness of the enterprise is clarified, which can contribute to a more accurate and clear definition of the processes associated with this activity. Under the "investment attractiveness" as an economic category should be understood as the level of efficiency of the available financial and economic resources of the enterprise, the indicators of which allow potential investors to draw conclusions about the need and feasibility of investing in the enterprise. It is found that the main components of the formation of investment potential of the enterprise are indicators of profitability, liquidity and solvency, business activity, financial stability. In the process of analyzing the literature and conducting a theoretical study identified various methodological approaches to assessing the investment attractiveness of the enterprise, among which are such classic tools as the method of sum of coefficients, the method of complex assessment, the method of sum of places. Their critical analysis is carried out, the advantages and disadvantages are determined. It is proved that the most clear and substantiated assessment of the level of investment attractiveness of the enterprise is considered in the methods based on the definition of the integrated indicator of investment attractiveness of the enterprise. This is the simplest method of analyzing the level of investment attractiveness, which requires the least time, and also allows you to quickly track negative trends in the enterprise, based on the calculation of financial ratios. It is substantiated that the assessment of the level of investment attractiveness of the enterprise should be carried out through rapid assessment, which is based on the calculation of an integrated indicator and provides analysis of the effectiveness of the main coefficients of financial condition based on comparison of marginal (critical and normal) and actual values. The proposed model of rapid assessment allows you to get an objective picture of the financial condition and efficiency of the existing investment attractiveness of the enterprise.
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Macpepple, Eunice D., Celestine C. Egwuonwu, and Cyprian N. Tom. "Solid Waste Management Performance Assessment Model for Owerri Municipality." International Journal of Advances in Engineering and Management 6, no. 10 (2024): 13–28. http://dx.doi.org/10.35629/5252-06101328.
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In this research, a solid waste management performance model was developed for Owerri municipality. This was necessitated by the existing poor waste management and service provision in the area. The present system performance and ideal real time model expectations were investigated. The model was developed in line with the established balance score card (BSC) concept using MATLAB 2021a software. 30 performance indicators were identified from 4 component objectives enshrined in globally accepted solid waste management systems and processes, namely, customer perspective (CP), internal process perspective (IPP), learning and growth perspective (LGP) and financial perspective (FP). These indicators were used as building blocks for developing the model. Indicators for physical parameters included leachate temperature, total dissolved solids (TDS) and total suspended solids (TSS). Leachate analysis confirmed the presence of high concentrations of TDS (6723kg/m), TSS (5731kg/m), total ammonia (186kg/m), and high BOD (137kg/m) and COD (614kg/m) levels, respectively at the active official dumpsite in the study area. The corresponding model results showed an overall SWM performance of 37.5%. The FP scored 0%. Outcome showed that specific areas that needed improvement were in the areas of waste collection coverage, final disposal, environmental endurance, inclusivity, financial sustainability and recycling and treatment facilities. The study also disclosed a systematic method for assessment of performance of the integrated solid waste management system (ISWMS) in the municipalities.
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Fechete, Flavia, and Anisor Nedelcu. "Performance Management Assessment Model for Sustainable Development." Sustainability 11, no. 10 (2019): 2779. http://dx.doi.org/10.3390/su11102779.
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Achieving performance is the premise of an organization’s existence on the market. Performance may be achieved by optimal administration of resources, in order to ensure not only short-term but also long-term efficacy. In this sense, performance and sustainability have common support. A sustainable enterprise is, implicitly, a performing enterprise. To be performing or to be able to support sustainable development implies the concern for simultaneous achievement of three categories of objectives: Economic-financial, social and environmental. Therefore, performance measurement requires a global vision of what the entity’s performance means. Thus, the present paper has the major objective of determining the global performance within industrial systems, by indicators that are mainly used to assess the sustainability aspects of the manufacturing systems. Indicators, such as manufacturing costs, quality of manufacturing, energy consumption, personal motivation, and safety, were correlated by an advanced multicriterial analysis. The created model presents the novelty that it provides a total score for performance, allowing to highlight risk areas and to set up improvement measures. The model is an important tool for optimizing the planning processes in order to reduce the consumption of energy, materials or water.
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Alonge, Enoch Oluwabusayo, Nsisong Louis Eyo-Udo, Bright Chibunna Ubanadu, Andrew Ifesinachi Daraojimba, Emmanuel Damilare Balogun, and Kolade Olusola Ogunsola. "Developing an Advanced Machine Learning Decision-Making Model for Banking: Balancing Risk, Speed, and Precision in Credit Assessments." International Journal of Multidisciplinary Research and Growth Evaluation. 5, no. 1 (2024): 1567–81. https://doi.org/10.54660/.ijmrge.2024.5.1.1567-1581.
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The banking industry faces significant challenges in balancing risk, speed, and precision when assessing creditworthiness. Traditional credit assessment methods often rely on rigid scoring systems that fail to adapt to dynamic market conditions, resulting in inefficiencies and heightened risks. This study focuses on developing an advanced machine learning (ML) decision-making model tailored for credit assessments in banking. By leveraging ML algorithms, the proposed model aims to enhance predictive accuracy, optimize decision-making speed, and mitigate risks associated with loan approvals and defaults. The research introduces a hybrid framework that integrates supervised learning techniques, such as gradient boosting and neural networks, with unsupervised learning methods for anomaly detection and clustering. These approaches enable the model to analyze large volumes of structured and unstructured data, including financial records, transaction histories, and behavioral patterns, to generate precise credit risk assessments. The model also incorporates explainable AI (XAI) techniques to ensure transparency and regulatory compliance, addressing a critical barrier to ML adoption in banking. Key findings highlight the model’s superior performance compared to traditional methods, achieving higher predictive accuracy, faster processing times, and improved risk management. Case studies from pilot implementations demonstrate its effectiveness in reducing non-performing loans, identifying high-risk borrowers, and enhancing customer experience through personalized credit offers. Furthermore, the research underscores the importance of robust data governance, algorithmic fairness, and cybersecurity in ensuring the reliability and ethical use of ML in banking. The proposed model provides a scalable and adaptable solution for banks to meet the evolving demands of modern financial ecosystems. By integrating real-time analytics and advanced decision-making capabilities, the model not only enhances operational efficiency but also supports long-term financial stability. This study contributes to the growing body of knowledge on artificial intelligence in financial services, offering actionable insights for financial institutions aiming to modernize their credit assessment processes.
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Ivanov, Dmitry A. "Financial activity of an organization: approaches to assessment of methods." Vestnik of Samara University. Economics and Management 15, no. 3 (2024): 113–25. http://dx.doi.org/10.18287/2542-0461-2024-15-3-113-125.
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The article presents the practical implementation of the model for assessing the financial performance of an organization, systematizing and directing its functioning throughout their life cycle. It is noted that financial analytics of the organization’s performance indicators, determined by management technologies and factors affecting the external and internal environment, can be used to create and develop its financial strategy. It is shown that high competition, significant risks, crisis phenomena, geopolitical and socioeconomic processes on the world stage and in the state, additionally increase the relevance of developing a new methodological apparatus for managing the financial stability of organizations, as a basic resource for ensuring their development. It has been established that insufficiently studied methodological approaches and the lack of a unified approach to methods for analyzing the financial performance of an organization hinder the development and improvement of its financial strategy. The author notes that approaches to assessing methods for analyzing the financial performance of an organization’s optimization present additional opportunities and recommendations in business development, as well as the development of theoretical and practical proposals that reveal successful directions for building the entire system of strategic financial management of organizations.
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Gąsiorkiewicz, Lech. "The Process Approach in the Financial Management of Insurance Firms." Foundations of Management 12, no. 1 (2020): 7–18. http://dx.doi.org/10.2478/fman-2020-0001.
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AbstractThe significance of insurance activity is constantly growing, generating new problems and posing new challenges. One of these challenges is meeting the growing requirements and expectations of customers. This requires the efficient management of insurance companies, which means the necessity to resort to modern management concepts, particularly the concept of process management and its related instruments. The article presents the results of research carried out at the Faculty of Management of the Warsaw University of Technology regarding process management in insurance companies. The distinctness of insurance activity and its financial management is discussed and its following aspects presented: the identification of insurance activity processes encompassing the management of basic and auxiliary processes; the model of the financial management process of insurance companies; the relationship between the financial management process and other processes implemented in insurance companies; financial situation assessment measures for insurance companies, and the financial management process.
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Ahmed, S. El Touny, H. Ibrahim Ahmed, and I. Amer Mohmed. "Estimating Cost Contingency for Highway Construction Projects Using Analytic Hierarchy Processes." IJCSI International Journal of Computer Science Issues 11, no. 6 (2014): 73–84. https://doi.org/10.5281/zenodo.4762112.
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Winning a bid at a price that yields a profit, is one of the contractor's major goals from bidding. One of the significant components of markup is the risk allowance (contingencies). Therefore, contractors should be wise to consider the likelihood that a particular risk will occur, identify the potential financial impact, and determine the suitable contingency allowance if the risk was to be mitigated through contingencies. Based on previous research, usually, most of the contractors set a percentage of the cost as contingencies. This approach of setting the contingency percentage intuitively could either lead to losing the bid or leaving money on the table. Therefore, the objective of the presented research in this paper is to identify the financial impacts of the risk factors during the bidding stages that affect cost contingency and develop a fast and reliable model to estimate the expected cost contingency of highway construction projects. A survey was conducted on ninety construction companies and experts in Egypt. The data obtained from the survey was then processed using Analytic Hierarchy Processes (AHP) technique on the most important fourteen factors out of 175 ones that affect cost contingency. The developed model was tested using historical completed projects and results show that the predicted cost contingency matches with (96.31%) the average estimated contingency for real case projects. The developed cost contingency model showed robust results.
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Boritz, J. Efrim, Carla Carnaghan, and Paulo S. Alencar. "Business Modeling to Improve Auditor Risk Assessment: An Investigation of Alternative Representations." Journal of Information Systems 28, no. 2 (2014): 231–56. http://dx.doi.org/10.2308/isys-50809.
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ABSTRACT This study investigates the effects of alternative methods for documenting business models on audit risk assessment behavior. We consider tabular versus diagrammatic representations of the relationship between business model components such as environmental factors, strategic goals, internal processes and resources, and financial statement accounts. Multiple scenarios based on a real company were constructed and 24 participants, including audit partners, managers, and novice auditors performed a risk assessment for each scenario, presented in either a diagrammatic or a tabular format. The participants' verbal discussions as they performed the risk assessments were tape recorded, transcribed, and coded. A content analysis of the participants' coded verbal behavior indicates that the tabular presentation appears to elicit more frequent mention of accounts by the participants, while the diagram format leads to more mentions of other business model components. There is also some evidence of expertise effects. This study indicates that a tabular presentation can possess many of the benefits often associated with a diagrammatic representation. However, in our study, obtaining such benefits involved the deliberate structuring of the tabular presentation to organize the components of the business model and the links between them and financial statement accounts.
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Sergienko, Olena, Nataliia Volosnikova, Natalia Reshetniak, Maryna Mashchenko, and Valeria Baranova. "CONCEPT OF FINANCIAL FLOW MANAGEMENT OF ENTERPRISE CORPORATE SECURITY SYSTEM." Financial and credit activity problems of theory and practice 3, no. 44 (2022): 176–88. http://dx.doi.org/10.55643/fcaptp.3.44.2022.3736.
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The concept of financial flows management of enterprise corporate security system is developed and justified in the article. The approaches to the assessment and analysis of the financial flow are analyzed. It is determined that the financial flow of enterprises' corporate security system should be understood as financial resources purposeful movement, which is a dynamic set in time and space within the logistics of processes at enterprises.The paper proves that the time factor is an important criterion for the industrial enterprise resource security management effectiveness because the duration of the time of any task depends on many interdependent cycles and parameters.It is emphasized that the vector of strategic goals in the multi-purpose model of integrated logistics processes at enterprises in a particular time period is complexly determined on the basis of various coefficients which are formed by the internal and external institutional environment analysis.It is confirmed that modeling of financial resources of integrated logistics processes makes it possible not only to form the optimal vector of strategic goals of the multi-purpose model of integrated logistics processes but also to identify the interconnection between the composition and volume of incoming and outgoing financial flows of all enterprise integrated processes. Material flow management optimization as a key aspect of logistics activities is considered, which is achieved by attracting and allocating financial resources and realized in the financial flows of integrated logistics processes at enterprises. The urgency of the requirements of coherence of material, financial, informational, and other types of resource flows of integrated logistics processes at enterprises is determined.It is proved the topicality and relevance of algorithms implementation for finding and analyzing performance indicators and decision-making criteria, which form the basis of the decision-making system for effective management of industrial enterprises’ resource potential, including financial, in conditions of factors instability and significant changes in the micro and macroeconomic environment.
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Hanziuk, Svitlana, and Anzhela Popova. "IMPROVEMENT OF METHODOLOGICAL APPROACHES TO FINANCIAL ANALYSIS OF ENTERPRISE ACTIVITIES." ECONOMIC BULLETIN OF THE DNIPROVSK STATE TECHNICAL UNIVERSITY, no. 1(10) (June 16, 2025): 143–48. https://doi.org/10.31319/2709-2879.2025iss1(10).332739pp143-148.
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The article examines the methodological apparatus for conducting financial analysis of an enterprise's activities. The key tasks of applying traditional methods, techniques and methods of financial analysis are identified: primary processing of available analytical information; analysis of the state and dynamics of the development of the object of analysis; identification of the influence of factors on financial indicators and processes; assessment of realized and potential reserves for increasing the efficiency of financial resources; generalization of analytical conclusions, substantiation of management decisions, financial plans and forecasts. The application of abstract-logical, economic-logical and economic-mathematical methods of financial analysis is substantiated. The main classical methods of analyzing the efficiency of the enterprise's functioning are grouped (time analysis, structural, trend, analysis of financial ratios, comparative, marginal, factor, stochastic probabilistic). It is noted that today an integrated, comprehensive approach to the financial analysis of an enterprise's activities dominates, which includes a comprehensive study of the enterprise's potential, determination of its competitive positions in the market environment and identification of opportunities for improving financial indicators. The article proposes an improved methodology for analytical assessment of business entities’ activities taking into account modern conditions of uncertainty, which takes into account crisis factors, the level of threats and the stress resistance of the financial model. Crisis factors include assessment of supply chain disruptions, loss of sales markets, growth of receivables and inflation risks. Assessment of the level of threats takes into account physical risks to assets, personnel risks, logistical and geopolitical factors. Stress resistance of the financial model is defined as a key indicator of long-term business viability, which demonstrates the ability of the enterprise to maintain solvency and financial balance under the worst conditions. To assess the stress resistance of the enterprise’s financial model in war conditions, the study proposes to apply stress testing with the identification of key stages and indicators.
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Горбунов, Владимир, and Vladimir Gorbunov. "Risks of entrepreneurship and its security." Russian Journal of Management 1, no. 3 (2013): 165–82. http://dx.doi.org/10.12737/643.
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The author analizes various methods of risk assessment and describes the features of performance of financial calculations under innovative projects by means of a software package “AEProject”. The used likelihood model of business processes allowing more precisely defines the financial streams of the project, the account of risks concerning such features with their likelihood characteristics and possibility of designing of process taking into account real risk situations.
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Kalyanathaya, Krishna P., and Krishna Prasad K. "A framework for generating explanations of machine learning models in Fintech industry." Scientific Temper 15, no. 02 (2024): 2207–15. http://dx.doi.org/10.58414/scientifictemper.2024.15.2.33.
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Artificial Intelligence is making significant inroads into various aspects of business and life bringing the transformation in many ways. The convolution of technology in finance is often called FINTECH rapidly growing area of transformation. In the FINTECH industry, AI can automate several financial processes and services such as fraud detection, customer services, credit assessment, price predictions, customer churning, trading services, risk management, underwriting, market forecasting. These processes and services are critical to financial sectors such as banking, insurance, currency, stock and commodity markets, wealth management, payment clearing houses, payment regulators etc. Regulations control these processes and should be transparent in their operations. AI models are inherently opaque in their outcomes and unable to be fully plugged into the financial processes and services. Explainable AI is the key area of research that can help to provide transparency to enable these AI models as fully operational business models to automate financial products and services. In this paper we will broadly outline the framework of explainable artificial intelligence (XAI) in finance sectors and services. We then look into one use case of credit assessment and develop an XAI framework to provide transparent outcomes from the AI models.
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PARFENTSEVA, N., and H. HOLUBOVA. "Simulating Financial Risks on the Basis of Statistical Assessment Methods." Scientific Bulletin of the National Academy of Statistics, Accounting and Audit, no. 1-2 (June 1, 2022): 14–20. http://dx.doi.org/10.31767/nasoa.1-2-2022.02.
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Financial risks are summed up by type and form, macro- and micro-level. The importance of monitoring of financial risks in insurance, banking, monetary activities and various business processes is substantiated. It is emphasized that the sound assessment of risks constitutes an important tool in risk management. The essence, advantages and disadvantages of selected methods for financial risk assessment is shown: Value-at-Risk, Monte Carlo method, methods based on IRB approach, Shortfall, LDA, methods using Bayesian programming.
 The importance of statistical methods for the assessment of financial risks like non-parametric techniques of Kaplan – Meier and Cox proportional hazards model is substantiated. It is emphasized that the cumulative hazard function by Cox model reflects the cumulative level of bank losses, hence, its application in risk assessment is capable to protect and warn the bank about a potential threat. Kaplan – Meier method allows to assess the probability of risk occurrence and risk level in various client groups, which is a necessary component of risk monitoring. But its drawback is its incapability to account for several risks at the same time. In view of this, a sounder method for risk assessment is Cox proportional hazard regression. The input data for constructing this regression can include both categorical and continuous variables, thus enabling for accounting of a multiplicity of risk-related factors. 
 It is concluded that Kaplan – Meier method should be used with caution, because the survival function may overvalue the probability of occurrence of “critical” event, depending on the internal nature of data and their individual variances. Hence, applications of semiparametric techniques of Cox proportional hazards model should be an alternative approach to the survival analysis.
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Syahra, Yohanni, Yuni Franciska Br. Tarigan, Karina Andriani, Hevlie Winda Nazry S, and Roziyani Setik. "Decision Trees in Predicting Loan Default Risk in Customer Relationships within the Financial Sector." Sinkron 9, no. 2 (2025): 734–45. https://doi.org/10.33395/sinkron.v9i2.14672.
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Loan default prediction is an important aspect of risk management in financial institutions. Accurate prediction models enable banks and lending organizations to mitigate risks, allocate resources effectively, and optimize decision-making processes. This study investigates the application of decision tree algorithms in predicting loan default risk in the financial sector. Decision trees are renowned for their interpretability, adaptability to non-linear data, and ability to handle missing values, making them a valuable tool in credit risk analysis. Using a dataset consisting of borrower profiles, credit scores, income levels, and payment history, the model identifies key predictors that influence default outcomes. The study uses the C4.5 decision tree model, which will demonstrate that decision trees achieve high prediction accuracy and offer a transparent decision-making framework, enhancing their applicability in real-world scenarios. Furthermore, the paper highlights the implications of these findings for financial institutions, emphasizing the scalability and cost-effectiveness of the model. By integrating decision tree-based models into existing risk assessment systems, lenders can proactively manage loan portfolios and reduce default rates. Future research directions are proposed to explore hybrid approaches that combine decision trees with advanced combined methods to enhance predictive capabilities. The potential of decision tree algorithms in transforming credit risk assessment and supporting more accurate data-driven financial decision-making processes
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USIKOVA, Elena Mykolaivna. "ANALYTICAL ASSESSMENT OF ACCOUNTING FINANCIAL FLOWS BY AGRICULTURAL SUBJECTS." Ukrainian Journal of Applied Economics 4, no. 4 (2019): 16–22. http://dx.doi.org/10.36887/2415-8453-2019-4-2.
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The article deals with the theoretical and practical aspects of estimating accounting cash flows that directly generate cash flow, influence and are managed by various actors in the agribusiness and the entire agro-industrial environment. After all, in the country where the agribusiness is concentrated, there are a number of unresolved issues in the field of research of agro-industrial enterprises, which led to the need for generalization and development of accounting and analytical support for the assessment of data of agricultural enterprises within accounting approaches to analytical evaluation. An analytical evaluation of the effectiveness of financial flow management is provided, which assures the enterprises in the process of its strategic and current development. The processes of agribusiness financial flows management and decision-making processes that should ensure a smooth process are considered. The liquid cash flow characterizing the absolute value of cash is investigated. The conceptual model of accounting and analytical support of financial recovery was used, as well as the analysis of the results of the activity of agribusiness entities. The results of the study showed that financial flow as an accounting category is divided over time into a series of payments with positive and negative value – that is, cash flows and their equivalents. Therefore, it is necessary to have an adequate system of accounting information, which will allow to use all available resources with maximum efficiency for effective development of agribusiness in Ukraine. Therefore, analytical valuation is an integral part of today, because there is such a situation that many domestic enterprises are not able to provide effective cash flow management without properly organized accounting and analytical assessment of financial flows of agribusiness entities. Optimization of valuation will allow to determine the most effective forms and conditions of implementation of current operations, as well as rational directions of assets and profit placement. Only a comprehensive approach will allow to ensure transparency of the estimation process of financial flows of enterprises and will facilitate timely decision-making in the process of its activity. Key words: accounting and analytical support, agricultural enterprise, accounting approaches, cash flows, liquid cash flow, accounting system.
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Hajiani, Hadi, Mehran Hossein Afshari, and Mehdi Rezaei. "Identifying and Evaluating a Model for Enhancing the Assessment of Internal Controls and Accounting Systems." Business, Marketing, and Finance Open 1, no. 4 (2024): 14–24. https://doi.org/10.61838/bmfopen.1.4.2.
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The objective of this study is to identify and evaluate a model to enhance the assessment of internal controls and accounting systems. The study is categorized as an applied-developmental research project. Using purposive sampling, 20 experts in the fields of accounting, auditing, financial management, and organizational management were interviewed. In the quantitative phase, all active participants in the accounting domain, with an unlimited population, were considered, and based on Cochran's formula, the sample size was determined to be 384 individuals. Data analysis in the qualitative phase employed grounded theory using ATLAS.ti software, while structural equation modeling was used for validation via SMART-PLS software. Based on the designed model, several categories were identified. Causal factors include human resource management, personality traits of accountants, ethical values of accountants, managers' attitudes toward accountants, and accountants' specialized knowledge. Contextual conditions encompass financial discipline, laws and regulations, information transparency, receptiveness to criticism, accountability, and the state of accounting. Intervening conditions highlight the weakness of regulatory bodies, financial pressure, environmental conditions, negligence, and socio-cultural conditions. Strategies focus on education, infrastructure development, financial reporting targeting, policy-making, and information technology. Outcomes include improved organizational image, business growth, and economic productivity. To ensure the effectiveness of these systems, continuous monitoring and evaluation processes are essential. The results should be communicated to senior management for implementing corrective measures based on the findings.
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Otenko, I. P., R. P. Shkreben, and M. V. Harnam. "Formation of a Conceptual Model of Management of Financial and Economic Security of Business Processes of Enterprise." Business Inform 12, no. 515 (2020): 423–29. http://dx.doi.org/10.32983/2222-4459-2020-12-423-429.
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The key idea of the conceptual model of financial and economic security of business processes of enterprise is the viewpoint that economic security is an integral part of the management system of enterprise development and therefore covers the tasks of strategic management and those that are specific to the current management of business processes of enterprise. Economic security management in accordance with development goals is ensured by such principles as: adaptability, achieved by harmonization of interests and goals, reliability of organizational relations with partners, compliance with organizational structure; sustainability, which is created due to competitiveness and stable position in the market, financial and economic condition and efficiency of functional areas of activity; ecological and social responsibility implemented in compliance with social standards and minimization of harmful effects on the environment. The components of this model are the goals, tasks, functions and potential for ensuring the security-oriented development of enterprise. Restrictions on the protection of the enterprise from threats require the financial and economic security management system of the developed information and analytical provision to identify and prevent threats, assess their impact, changes in the financial and economic state of the enterprise, the sufficiency of its resource provision. The most relevant are the analytical methods for assessing possible threats and their consequences, identifying dangerous zones to maintain the sustainability of the financial and economic state of enterprise. Further development of an analytical instrumentarium for assessing economic security be carried out through the construction of more advanced indicators and criteria for quantitative assessment of the adequacy of the level of economic security in order to ensure the sustainable development of enterprise.
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Abhishek, Shivanna. "Explainable AI Models for Risk Assessment in Banking." Journal of Scientific and Engineering Research 9, no. 10 (2022): 95–102. https://doi.org/10.5281/zenodo.14273521.
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In the evolving landscape of banking, effective risk assessment has traditionally relied on linear models and tree-based models to analyze data and guide decision-making. However, as the complexity of financial data and the demand for more accurate predictions increase, banks are transitioning toward deep neural networks, which offer greater predictive power. This shift to deep learning has raised concerns about transparency, as these models often function as "black boxes," making it difficult to interpret their decisions. This paper explores the role of explainable deep learning models in modernizing risk assessment processes, bridging the gap between model complexity and the need for interpretability. By comparing traditional methods with deep neural networks, we highlight the importance of explainability in enhancing trust, regulatory compliance, and decision-making. Furthermore, we examine the challenges posed by black-box models and discuss how explainable deep learning can provide solutions to meet the stringent demands of regulators while ensuring fairness and accountability in risk assessments.
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Williams, Alvin J., and Ben Oumlil. "College student financial capability." International Journal of Bank Marketing 33, no. 5 (2015): 637–53. http://dx.doi.org/10.1108/ijbm-06-2014-0081.
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Purpose – The reviewed literature emphasized that the student loan debt issues have a lot of connections to the economy. This conclusion is in support with broader evidence that high student debt levels are a drag on economic growth. Additionally, disadvantaged and other vulnerable groups, including students, are more likely to be excluded from the formal, regulated financial sector and not be able to take advantage of mainstream financial service providers (e.g. lack access to credit, insurance, and other formal financial services). Among the primary reasons cited for this financial exclusion has to do with a lack of understanding or familiarity with traditional financial services. The aim of this paper is to look at alternate approaches in promoting financial literacy to manage the huge private debt burden facing this important segment of the population. The purpose of this paper is to advance a model of college students’ financial capabilities enhancement to partially alleviate some of the problems related to deficits in financial knowledge among this population. The integrative model provides a framework to be operationalized by institutional decision-makers and policymakers at all levels. The model can be adapted to fit unique institutional circumstances and culture. Successful implementation of the model has the potential to enhance the quality of financial health among college students and young adults. Design/methodology/approach – The manuscript’s aim is to advance a model of college students’ financial capabilities in an effort to prevent their financial exclusion. The proposed model provides a framework to be operationalized by institutional decision-making processes. The model offers six distinct, but inter-related components – antecedent variables, program design and implementation, delivery modalities, program content, behavioral outcomes, and measurement and assessment. Findings – The underlying raison d’etre for the model is to offer a comprehensive, inclusive, across-the-board roadmap to guide universities, and other organizations in conceptualizing, planning, organizing, implementing, and assessing financial education-related systems and processes designed to enhance the long-term financial choices and behaviors of students. Through careful consideration of each of the phases of the model, decision-makers at all levels and all types of organizations should have a stronger grasp of the depth and breadth of actions required to effect the desired changes in students’ financial behavior. Research limitations/implications – As with any paper there are limitations. The paper is conceptual and lacks data to test some of the linkages. Future research efforts should posit specific propositions to be tested based on the linkages offered in the model. Given the nature of the research theme, there is considerable benefit from taking a case-based approach to future research to offer more in-depth analyses of student financial literacy deficits across different situations and types, student markets, and educational institutions. The current research could also benefit from a stronger cross-cultural focus. While huge college student debt is probably more burdensome in the USA, it is helpful to get input from students in countries that lack a tradition of heavy borrowing to pay for college costs. Researching debt management trends across cultures should provide useful micro- and macro-economic data for policymakers and others. Practical implications – The paper introduces a model of college students’ financial capabilities enhancement and financial exclusion’s prevention that offers one avenue to partially remedy the direct and indirect ills perpetrated and perpetuated by insufficient financial knowledge among young adults, especially the college segment (i.e. to promote financial inclusion and financial exclusion’s prevention). The model provides a comprehensive and integrative path for college administrators and others to consider when designing programs to enhance the overall financial knowledge acumen and savvy of college students. Specifically, the model discusses antecedent variables, program design and implementation, delivery modalities, program content, behavioral outcomes, and measure and evaluation options. Social implications – There is considerable concern among students, parents, marketers, and public policymakers regarding deficiencies in financial knowledge and capabilities among the young adult population. Students have massive student loan debt, collectively, and there is a multifaceted clarion call to develop integrative solutions to this daunting scenario. The paper discusses the gravity and consequences of financial literacy deficits among college students and some associated solutions. Originality/value – The model offers six distinct, but inter-related components – antecedent variables, program design and implementation, delivery modalities, program content, behavioral outcomes, and measurement and assessment. The model is posited as an “intervention strategy” capable of strengthening the capacity of young college adults to make informed financial decisions, thus impacting their quality of life over the long run. In particular the model offers a form of empowerment to this consumer segment. As stated, the underlying raison d’etre for the model is to offer a comprehensive, inclusive, across-the-board roadmap to guide universities and other organizations in conceptualizing, planning, organizing, implementing, and assessing financial education-related systems and processes designed to enhance the long-term financial choices and behaviors of students. Through careful consideration of each of the phases of the model, decision-makers at all levels and all types of organizations should have a stronger grasp of the depth and breadth of actions required to effect the desired changes in students’ financial behavior.
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Korablev, A. V., M. V. Petrushova, E. V. Pogorelova, and A. G. Abrosimov. "Mathematical Model of Economical Assessment of Investments in Information Provision for the Management System of a Modern Company." SHS Web of Conferences 62 (2019): 11002. http://dx.doi.org/10.1051/shsconf/20196211002.
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Information provision for a company’s management system not only provides data for evaluating day-to-day operations but also is an efficient tool for improving the reliability of the entire management system. For purposes of efficiently managing projects for implementing modern information provision, the company should design a formalized model for assessing the relationship between project-related financial costs and the number of automated business processes in place at the company. This paper proposes using a mathematical model that contains financial indicators such as net present value, cash flows, and discount rates. Thanks to lower investment risks, the model will improve the economic efficiency of investment projects as part of implementing information provision at the company.
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Kozhukhivskyi, A. D., and O. A. Kozhukhivska. "DEVELOPING A FUZZY RISK ASSESSMENT MODEL FOR ERPSYSTEMS." Radio Electronics, Computer Science, Control, no. 1 (April 8, 2022): 106. http://dx.doi.org/10.15588/1607-3274-2022-1-12.
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Context. Because assessing information security risks is a complex and complete uncertainty process, and uncer-tainties are a major factor influencing valuation performance, it is advisable to use fuzzy methods and models that are adaptive to non-calculated data. The formation of vague assessments of risk factors is subjective, and risk assessment depends on the practical results obtained in the process of processing the risks of threats that have already arisen during the functioning of the organization and experience of information security professionals. Therefore, it will be advisable to use models that can adequately assess fuzzy factors and have the ability to adjust their impact on risk assessment. The greatest performance indicators for solving such problems are neuro-fuzzy models that combine methods of fuzzy logic and artificial neural networks and systems, i.e. “human-like” style of considerations of fuzzy systems with training and simulation of mental phenomena of neural networks. To build a model for calculating the risk assessment of information security, it is proposed to use a fuzzy product model. Fuzzy product models (Rule-Based Fuzzy Models/Systems) this is a common type of fuzzy models used to describe, analyze and simulate complex systems and processes that are poorly formalized.
 Objective. Development of the structure of a fuzzy model of quality of information security risk assessment and protection of ERP systems through the use of fuzzy neural models.
 Method. To build a model for calculating the risk assessment of information security, it is proposed to use a fuzzy product model. Fuzzy product models are a common kind of fuzzy models used to describe, analyze and model complex systems and processes that are poorly formalized.
 Results. Identified factors influencing risk assessment suggest the use of linguistic variables to describe them and use fuzzy variables to assess their qualities, as well as a system of qualitative assessments. The choice of parameters is substantiated and the structure of the fuzzy product model of risk assessment and the basis of the rules of fuzzy logical conclusion is developed. The use of fuzzy models for solving problems of information security risk assessment, as well as the concept and construction of ERP systems and analyzed problems of their security and vulnerabilities are considered.
 Conclusions. A fuzzy model has been developed risk assessment of the ERP system. Selected a list of factors affecting the risk of information security. Methods of risk assessment of information resources and ERP-systems in general, assessment of financial losses from the implementation of threats, determination of the type of risk according to its assessment for the formation of recommendations on their processing in order to maintain the level of protection of the ERP-system are proposed. The list of linguistic variables of the model is defined. The structure of the database of fuzzy product rules – MISO-structure is chosen. The structure of the fuzzy model was built. Fuzzy variable models have been identified.
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Чернявский, В. С., С. Д. Агарков, and Д. А. Хамитова. "Assessment of sectoral financial risks of entrepreneurial activity." Вестник МИРБИС, no. 2(34) (July 25, 2023): 195–202. http://dx.doi.org/10.25634/mirbis.2023.2.24.
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В условиях развития интеграционных процессов компаниям необходимо быстро реагировать на колебания рынка и формировать необходимые финансовые инструменты для повышения операционной эффективности и устойчивого развития. Управление рисками становится все более привычным, однако сложность создания полных баз данных по конкретным рисковым событиям и кризисным потокам затрудняют принятие решений и требуют дальнейшего развития механизмов управления рисками. Для оценки риска финансовых активов в данной работе воспользуемся моделью Шарпа (в качестве финансовых активов использовались акции крупнейших компаний Республики Казахстан). Исследование показало, что наиболее эффективным способом минимизации рисков является внедрение эффективной системы управления рисками, которая должна обеспечивать: внутренние регламенты, позволяющие своевременно выявлять и оценивать факторы риска; централизацию внутреннего и внешнего контроля; для принятия решений и текущей оценки деятельности обеспечить наличие надежной, точной, своевременной, доступной и полной информации; постоянное управление ключевыми рисками. In the conditions of development of integration processes, companies need to quickly respond to market fluctuations and form the necessary financial instruments to increase operational efficiency and sustainable development. Risk management is becoming increasingly familiar, but the difficulty of creating full databases on specific risky events and crisis flows makes it possible to make decision -making and require the further development of risk management mechanisms. To assess the risk of financial assets in this work, we will use the Sharpe model (shares of the largest companies in the Republic of Kazakhstan were used as financial assets). The study showed that the most effective way to minimize risks is to introduce an effective risk management system, which should provide: internal regulations that allow timely identify and evaluate risk factors; centralization of internal and external control; to make decisions and current assessment of the activities to ensure the availability of reliable, accurate, timely, affordable and complete information; Constant control of key risks.
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Masood, Fahad. "Impact of Artificial Intelligence on Financial Markets." International Journal of Emerging Multidisciplinaries: Social Science 3, no. 1 (2024): 8. http://dx.doi.org/10.54938/ijemdss.2024.03.1.359.
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Artificial Intelligence (AI) has rapidly transformed financial markets, enhancing efficiency, precision, and scalability in trading, risk management, fraud detection, and personalization. Through advanced machine learning models, AI has enabled high-frequency trading, predictive risk assessment, and robust compliance processes, which streamline operations and improve market responsiveness. However, the complexity and opacity of AI systems introduce ethical concerns and regulatory challenges, especially regarding model interpretability and potential biases. This paper examines the role of AI across financial functions, highlights both advantages and limitations compared to traditional methods, and discusses future directions for integrating hybrid models and adaptive trading strategies. While AI offers considerable benefits, addressing its ethical and regulatory implications will be essential to harnessing its full potential within financial markets.
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Jennifer, Muhindo, Mukasa Kevin, Kitakufe Doreen, and Kato Jimmy. "Advancing credit risk assessment and financial decision-making: Integrating modern techniques and insights." World Journal of Advanced Research and Reviews 23, no. 2 (2024): 2019–27. https://doi.org/10.5281/zenodo.14869154.
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Credit risk assessment and fraud detection are critical functions in the financial industry, necessary for ensuring the stability and integrity of financial institutions. Traditional approaches often struggle to accurately assess risk and detect fraudulent activities in a timely manner. However, the rise of machine learning has introduced powerful tools that leverage large datasets and advanced algorithms to improve these processes. This research paper investigates the application of machine learning techniques in credit risk assessment and fraud detection within financial transactions. The paper begins by emphasizing the importance of accurate risk assessment and fraud detection in the financial sector and introduces machine learning as a solution to the limitations of traditional methods. A thorough literature review examines existing methodologies, algorithms, and trends, highlighting the advancements in this field. The discussion covers data acquisition and preprocessing techniques, underscoring the necessity of clean and relevant data for effective model training. Additionally, feature engineering strategies are explored to extract valuable insights from financial transaction data, enhancing the predictive power of machine learning models. The research analyzes various machine learning algorithms, such as logistic regression, decision trees, random forests, support vector machines, and neural networks, as well as ensemble methods. Model evaluation metrics, including accuracy, precision, recall, and ROC-AUC, are employed to assess the performance of these algorithms. The paper presents case studies and experimental results to demonstrate the practical application of machine learning models in real-world scenarios, showcasing their effectiveness in improving credit risk assessment and fraud detection. Furthermore, the research explores challenges such as imbalanced datasets, model interpretability, and regulatory compliance, offering insights into potential solutions and future research directions. The integration of behavioral finance, Bayesian networks, and optimization methods is also discussed, highlighting how these modern approaches, combined with big data analytics, can enhance predictive accuracy and decision reliability. In conclusion, this research underscores the transformative potential of machine learning in credit risk assessment and fraud detection within financial transactions. By adopting advanced algorithms and data-driven approaches, financial institutions can significantly improve their risk management strategies, mitigate potential risks, and protect against fraudulent activities. This ultimately contributes to a more secure and resilient financial ecosystem, enabling institutions to maintain a competitive edge in an ever-evolving market.
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Rodgers, Waymond. "The Effects of Accounting Information on Individuals' Perceptual Processes." Journal of Accounting, Auditing & Finance 7, no. 1 (1992): 67–95. http://dx.doi.org/10.1177/0148558x9200700107.
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This research focuses on the influence of decision makers' perceptual processes on their decision choices when they are presented with financial accounting information. A conceptual model which depicted perceptual and judgmental processes was used to capture individuals' decision-making processes. A covariance structural model of the processes graduate students used to reach loan decisions was examined through measures designed to test the proposed conceptual model. Also, a multigroup analysis was used to compare whether individuals with a more data-driven perceptual approach would differ from those with a more conceptually driven perceptual approach when making loan decisions. The results indicated that their approaches caused different loan assessments of financial accounting information. The results also indicated that data-driven types outperformed the conceptually driven types. The relative usefulness of the conceptual model was discussed, and general suggestions for future research on perceptual processes and goal attainment were offered.
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Albezuirat, Malek Khalaf, Rosmaini Ahmad, Muhammad Iqbal Hussain, Falah Mustafa Al-Saraireh, and Asia Khalaf Albzeirat. "Employment of Set Operations to Improve LMP Assessments Design and Implementation." SEISENSE Journal of Management 2, no. 1 (2019): 33–46. http://dx.doi.org/10.33215/sjom.v2i1.56.
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Objective - This paper aims to provide a new mathematical model for the construction of assessment tools for Lean Manufacturing Practices (LMP) through the integration process with the set operations. This study also strives to develop key elements to enhance the effectiveness of LMP assessments and their impact through mathematical interrelationship. 
 Problem - Previous studies have shown a lack of clear mathematical methodology to carry out a rigorous assessment of the LMP effects on the firm’s operational and financial performance. Therefore, this paper tries to address this aspect by developing new equations. 
 Design - The methodology of this study is based on the conversion of the linguistic description (companies, processes, waste, practices) into numerical measurement model by integrating with set theory. 
 Finding - The results show a set of relationships and equations that can be applied to be a fundamental basis for ensuring the effectiveness of the assessment. This paper may contribute to the improvement of LMP’s design and development.
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Rogulenko, Tatyana, Evgeniy Vladimirovich Orlov, Oleg Alexandrovich Smolyakov, Anna Vladimirovna Bodiako, and Svetlana Valeryevna Ponomareva. "Analytical Methods to Assess Financial Capacity in Face of Innovation Projects Risks." Risks 9, no. 9 (2021): 171. http://dx.doi.org/10.3390/risks9090171.
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This paper aims to analyze the most relevant methods to determine the financial capacity of innovation projects and identify potential ways of their improvement. The research helped to propose an alternative methodology to assess the financial capacity of innovation projects by charting an alternative balance with a minimum scope of data (annual balance sheet data, project term). The authors drew a conclusion concerning the critical role of choices on the methods applied to analyze the financial capacity of innovation projects in the context of different scales and terms of project jobs in an analyzed project and the need for the proposed alternative (estimate or expertise-based) assessment of financial capacity as well as the relevant risks associated with the implementation of the new financial capacity assessment system and the overall risks of the innovation project. These specifically concern the choices of the methods of attribution of indirect costs in innovation projects, composition and scope of criteria to distinguish business processes to manage these processes and constituent operations, the form of a matrix of correspondence for a set of costs by the stages of an innovation project (event-based matrix accounting) and the information model of the objective-based methods of managing an innovation project as an object.
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Junus, Onong, and Julie Abdullah. "Hubungan Korelasional Antara Kompetensi Manajerial dan Sistem Kontrol Internal Terhadap Kinerja Keuangan Pemerintah Provinsi Gorontalo." Gorontalo Accounting Journal 1, no. 1 (2018): 68. http://dx.doi.org/10.32662/gaj.v1i1.83.
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This study aimed to analyze the correlation relationship between managerial competence and control systems to the financial performance of Gorontalo Provincial Government. A total of 648 employees of the finance department and samples taken as many as 247 respondents by formula Slovin. Data from the questionnaires were analyzed using Structural Equation Model using AMOS aid 18.The results found that the internal control system directly and not significant positive effect on financial performance. Means the internal control system has been implemented, but has not been able to achieve results that match the input, process, output, outcome, benefit and impact as an assessment of the organization's financial performance. Direct managerial competence dominant influence positive and significant impact on the financial performance of the organization. Means an employee-owned managerial competence are good and support the achievement of the work in the field of appropriate financial inputs, processes, outputs, outcomes, benefits and impact as well as the assessment of financial performance to the principles of management in the financial sector.
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Li, Runzhe. "Quantitative Finance and Fintech Research under Artificial Intelligence." International Journal of Computer Science and Information Technology 3, no. 3 (2024): 215–23. http://dx.doi.org/10.62051/ijcsit.v3n3.22.
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This paper examines the impact of artificial intelligence (AI) on quantitative finance and financial technology (fintech). It explores how AI techniques, including machine learning and deep learning, are transforming financial modeling, risk assessment, and decision-making processes. The study discusses key innovations in AI-driven fintech, such as robo-advisors and algorithmic trading. It also addresses critical challenges, including data quality issues, model interpretability, and regulatory concerns. The paper concludes by outlining future directions and ethical considerations for AI in finance, emphasizing the need for responsible development and deployment of these technologies in reshaping the financial landscape.
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Aiguzhinova, D., Zh Altaibayeva, and Sh Mutallyapova. "Creation of financial business models in beef cattle breeding: structure and stages." Problems of AgriMarket, no. 4 (December 15, 2023): 132–40. http://dx.doi.org/10.46666/2023-4.2708-9991.13.
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The goal is to develop an algorithm for financial modeling of business processes in beef cattle breeding. Methods – general scientific and empirical. The logical method was used to determine the structure of the study and identify cause-and-effect relationships. The collected material is systematized, summarized and analyzed taking into account the technological features of the industry, modern market conditions, regulatory requirements, financing criteria and government measures to support agricultural producers in the republic. Methods of synthesis, comparison, comparison, and mathematical calculations were also used. Results - the authors proposed financial business model that promotes flexibility in planning production program for keeping and raising livestock for meat. The advantages of financial model in cattle breeding for meat productivity are substantiated as an effective tool for information support, planning, analysis and management decision-making, consisting in the fact that the content of each component of the mathematical financial model allows you to study their components and collect information necessary for financial and economic calculations. The composition of the elements for constructing a financial strategy for breeding beef cattle has been determined, including initial data, analytical calculations, and resulting parameters. A step-by-step algorithm for financial business planning has been created, from initial parameters and assumptions to the calculation of technological and economic efficiency indicators. Conclusions - based on financial modeling of business processes, farmers will have the opportunity to preliminarily assess profitability, find savings reserves, and predict costs for intensive beef cattle farming. A comprehensive business analysis with a financial model and assessment of the market situation is necessary in order to obtain a loan, attract investment and prepare an investment project.
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Rajeev Reddy Chevuri. "The role of explainable AI in promoting transparency in financial decision-making." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 1294–301. https://doi.org/10.30574/wjarr.2025.26.1.1160.
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The integration of artificial intelligence in financial systems has revolutionized decision-making processes, particularly in credit scoring and risk assessment. However, this technological advancement brings forth crucial questions about transparency and accountability. This article examines how Explainable AI (XAI) addresses these concerns by providing interpretable insights into algorithmic decisions while maintaining model performance. Through analysis of various implementation frameworks, regulatory requirements, and case studies, this article demonstrates how financial institutions are successfully balancing the need for sophisticated AI systems with demands for transparency. The article explores both model-specific and model-agnostic techniques, evaluating their effectiveness in different financial applications while considering the challenges of implementation and compliance. Furthermore, it examines the evolution of regulatory frameworks across different jurisdictions and their impact on XAI adoption, providing insights into future directions for both technical innovation and regulatory standardization.
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Бобро, Наталія. "STRATEGIC MANAGEMENT OF THE UNIVERSITY'S ECONOMIC SUSTAINABILITY." Сталий розвиток економіки, no. 1 (52) (January 27, 2025): 34–41. https://doi.org/10.32782/2308-1988/2025-52-5.
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The article is devoted to the strategic management of universities' economic sustainability in the context of digital transformations. The study examines the main approaches to ensuring the economic sustainability of higher education institutions, which are particularly relevant in the era of globalization and technological change. The impact of digitalization on university management processes is analyzed, focusing on the integration of advanced technologies, resource optimization, and increased financial efficiency. The role of digital tools in reducing the costs of educational services, improving management processes, and enhancing the competitiveness of universities is explored. A comprehensive model of strategic management of economic sustainability is proposed, encompassing financial flow assessment, cost management, investment analysis in digital technologies, and their integration into university development strategies. The model aims to enhance resilience to economic challenges, ensure stability, and increase competitiveness in the educational services market.