Background: Chhattisgarh's nominal gross state domestic product (GSDP) is estimated at ₹5.09 lakh crore (US$58 billion) in 2023–24, the 17th largest state economy in India. Chhattisgarh's success factors in achieving high growth rate are growth in agriculture and industrial production. Purpose: District Central Cooperative Banks (DCCBs) constitute a crucial component of India’s rural credit delivery system. This study evaluates the position and share of DCCBs in Chhattisgarh relative to All-India DCCBs across major financial and operational parameters. Methodology: The study is based on secondary data from NABARD, RBI, and official cooperative banking reports for March 2023. A cross-sectional comparative analysis was conducted using percentage analysis and comparative statistical techniques. Findings: Results indicate that DCCBs in Chhattisgarh maintain a significant share in membership, deposits, and investments relative to national totals, while their borrowing levels remain comparatively low. Individual deposits constitute the major portion of total deposits, demonstrating strong public trust in cooperative banking institutions. Policy Implications: Strengthening capital base, improving lending outreach, and enhancing reserve funds can further improve the performance of cooperative banks in the state.

Abstract— Stock Market prediction is a category of time series prediction which extremely challenging due to the dependence of stock prices on several financial, socio-economic and political parameters etc. Moreover, small inaccuracies in stock market price predictions may result in huge losses to firms which use stock market price prediction results for financial analysis and investments. Off late, artificial intelligence and machine learning based techniques are being used widely for stock market prediction due to relatively higher accuracy compared to conventional statistical techniques. The proposed work employs the steepest descent based algorithm along with the data pre-processing using the discrete wavelet transform (DWT) for stock market prediction. It has been shown that the proposed system attains lesser mean square percentage error compared to previously existing technique. Keywords—Stock Market Forecasting, Artificial Neural Network (ANN), Back Propagation, Discrete Wavelet Transform (DWT), Mean Absolute Percentage Error (MAPE).

Rural electrification in developing regions requires decentralized, sustainable energy systems that balance cost, reliability, and environmental performance. Hybrid renewable microgrids integrating solar, wind, and biomass have been studied extensively. However, existing methods frequently rely on generic component models and simplified operational methods, limiting their applicability to region-specific conditions. This study addresses these limitations through three novel contributions. (a) It develops Tamil Nadu-specific biomass feedstock modelling that incorporates seasonal agricultural residue availability and local gasification characteristics. (b) It implements integrated sizing and operation optimization using hourly dispatch decisions within the Non-dominated Sorting Genetic Algorithm II (NSGA-II). (c) It conducts a comprehensive 6-parameter sensitivity analysis to quantify model robustness under realistic uncertainty. The model optimizes hybrid microgrids integrating solar photovoltaic, wind turbine, biomass gasifier, and lithium-ion battery subsystems. Three conflicting objectives are minimized: Levelized Cost of Energy (LCOE), Loss of Power Supply Probability (LPSP), and carbon dioxide emissions. A case study of 350 rural households in Tamil Nadu validates the approach using hourly meteorological and load data with regionally calibrated techno-economic parameters. Results prove that hybrid configurations substantially outperform single-source systems across all metrics. Pareto-optimal solutions reveal critical trade-offs between economic, technical, and environmental objectives. Sensitivity analysis identifies demand growth, wind variability, and battery efficiency as dominant drivers of model robustness, while financial parameters primarily influence cost feasibility. The results validate region-specific hybrid microgrid optimization as a technically and economically viable pathway for sustainable rural electrification, providing policymakers with actionable insights on system sizing, resource management, and investment prioritization.

This research examines the impact of brand equity on corporate financial performance, utilizing a dataset of 135 international companies spanning the period from 2005 to 2024. We examine the impact of brand power on essential financial parameters, including operational income, EBITDA, and market capitalization, by merging brand value data from Brand Finance with financial metrics from Bloomberg Database. Our research reveals a robust positive association between brand value and turnover, profitability, and market valuation, indicating that organizations with elevated brand value experience superior financial results. Our econometric analysis demonstrates that a $1 increase in brand value correlates with a $1.76 gain in turnover and a $0.16 rise in net income, underscoring the tangible financial advantages of robust branding. Furthermore, we observe that brand value influences non-operating income, presumably via enhanced financing conditions and reduced interest expenses. Despite apprehensions regarding overvaluation, our findings indicate that although brand value enhances share prices, it does not result in an unsustainable rise in price-to-earnings ratios. These insights highlight the strategic significance of brand investments, indicating that companies should prioritize brand-building efforts to enhance long-term profitability and market competitiveness. Subsequent research ought to examine the impact of branding across various industries and organizational scales.

The subject of the study is the Unified Methodological Recommendations for Project Activities (UMR) as an element of methodological regulation of the project-related expenditures of the federal budget within the system of program-targeted planning of the Russian Federation. The article analyzes their legal nature, functional purpose, and actual regulatory impact on national projects, federal projects (both included and not included in national projects), and departmental projects. Special attention is given to identifying in the text of the UMR the prescriptive norms of prohibitive and mandatory nature that establish requirements for the structure of project passports, monitoring timelines and procedures, rules for making changes, and ensuring the consistency of financial parameters with federal budget execution data. The research aims to determine the place of UMR in the system of sources of financial law and to identify signs of quasi-normative regulation in the absence of a formal status as a normative legal act. It is argued that UMR operates as a tool of "soft imperative," exerting a systemic influence on budget planning, administration, and control of project expenditures. The work employs formal-legal, system-structural, and comparative-legal methods, as well as elements of doctrinal analysis of the concept of "soft law." The study is based on the analysis of normative and methodological acts in their interrelation with budgetary procedural institutions. The scientific novelty of the research lies in the comprehensive financial-legal interpretation of the Unified Methodological Recommendations for Project Activities as an element of quasi-normative regulation of the project-related expenditures of the federal budget. It is demonstrated that UMR is not limited to methodological support for project management but instead forms a system of prescriptive mandates of both mandatory and prohibitive nature, directly influencing the structure of project passports, the procedure for making changes, monitoring, and the comparability of budget parameters. For the first time, at the level of systemic analysis, the institutional relationship of UMR with the digital infrastructure "Electronic Budget" and their role in ensuring the consistency of federal budget execution data are shown. A conclusion is drawn about the existence of a "soft imperative" construct within program-targeted budgeting, where the methodological document effectively performs the functions of a normative regulator. The necessity of institutionalizing the existing methodological requirements in the form of a separate normative legal act at the departmental level is justified, which would eliminate legal uncertainty and ensure the systematic regulation of project expenditures.

Mergers and acquisitions are noteworthy corporate strategic measure that assists the merged entity in external growth and afford it competitive advantage. The study tries to evaluate methodically the consequence of merger of United Western Bank along with Industrial Development Bank of India in 2006 and subsequent merger of IDBI bank with LIC of India in 2019 on their financial performance in terms of different financial parameters for the period from 2004-05 to 2024-25 dividing the entire period into two phases. Most of the financial indicators of Industrial Development Bank of India (IDBI) after undergoing merger with United Western Bank (UWB) in 2006 and LIC of India in 2019 exhibit noteworthy progress in their outfitted performance during post-merger period. Post-merger regression analysis suggests that impact of management quality, capital adequacy and sensitivity to interest rate risk on profitability (ROA) parameter have improved much in comparison with entire study period’s regression analysis (both pre- and post-merger taken together) in both mergers. It can be inferred from the regression analysis that merger of these above two banks and subsequently with LIC has significant impact on earning capabilities of the Bidder Bank (IDBI) in terms of creating synergy through augmented managerial efficiency and subsequently by capital adequacy and non-interest income related sensitivity.© The Author(s) 2026. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.Article’s history: Received 22nd of December, 2025; Revised 17th of January, 2026; Accepted for publication 27th of January, 2026; Available online: 2nd of February, 2026; Published as article in Volume II, Issue 1(3), 2026.

The efficiency and management structure of airports play a crucial role in the global aviation industry, impacting financial sustainability, operational performance, and overall service quality. This study examines the differences between State-Owned and Build-Operate-Transfer (BOT) model airports, using a clustering analysis approach to categorize airports based on financial and operational parameters. Türkiye, a key player in global aviation, is selected as the case study related to analyzing 49 airports (43 state-owned and 6 BOT-operated) from 2018 to 2024. Using K-Means Clustering, airports are classified into four distinct categories based on passenger traffic, aircraft movements, navigational revenues, terminal service revenues, and business service revenue paameters. The findings indicate that BOT model airports demonstrate higher financial efficiency and operational sustainability compared to their state-owned counterparts. From a managerial perspective, the study highlights the need for adaptive financial models, efficient privatization strategies, and data-driven decision-making to enhance the economic sustainability of state-owned airports.

As with most Sub-Saharan African countries, Nigeria has a rising incidence of cancer, with disproportionate mortality rates. The financial burden of cancer care often results in catastrophic healthcare spending, leading to treatment refusal, disruption, and discontinuation. This is particularly significant in Nigeria, where nearly all patients are uninsured, and out-of-pocket costs often exceed households' ability to pay. Financial navigation programs (FNPs) have been shown to mitigate treatment-related financial toxicity in cancer care and reduce treatment abandonment, but there is a paucity of high-quality data on this intervention in resource-constrained settings. Here, we present a randomized controlled trial to evaluate the impact of a novel FNP in Nigeria. We designed the COST-FIN trial, a multi-site pragmatic single-blinded randomized controlled trial of newly diagnosed (<6weeks from diagnosis) adults (≥18years) with breast, colorectal, or prostate cancer at two tertiary cancer centers in Nigeria. Participants (n = 200) will be randomized (1:1) to either the intervention (FNP) or the control arm and followed for 12months. Data on key individual, treatment, and financial parameters will be collected via structured interviews and chart abstraction at baseline, 3-, 6-, and 12-month follow-up. In addition, participants randomized to the FNP will receive a tailored financial literacy assessment, financial planning support, and enhanced access to resources by trained financial navigators. Primary and secondary outcomes are financial catastrophe (FC) and financial distress (FD), respectively. Exploratory outcomes will include cost-related non-adherence and cost-effectiveness of the program. An interim analysis will be conducted when 50% of the estimated accruals reach 6months of follow-up, with crossover if compelling evidence of benefit is demonstrated at that time point. All participants will be followed for 12months from recruitment. This first-of-its-kind study will provide evidence on the role of FNP in potentially eliminating financial barriers to cancer care in Nigeria. Given the country's renewed interest in cancer control through the passage of the National Cancer Control Plan, findings from this study have the potential to influence policy reform and set the stage for further studies to evaluate the scalability and implementation of similar interventions in resource-limited settings. ClinicalTrials.gov NCT06630962 . Registered on Oct 8, 2024.

Background:As with most Sub-Saharan African countries, Nigeria has a rising incidence of cancer, with disproportionate mortality rates. The financial burden of cancer care often results in catastrophic healthcare spending, leading to treatment refusal, disruption, and discontinuation. This is particularly significant in Nigeria, where nearly all patients are uninsured, and out-of-pocket costs often exceed households’ ability to pay. Financial Navigation Programs (FNPs) have been shown to mitigate treatment-related financial toxicity in cancer care and reduce treatment abandonment, but there is a paucity of high-quality data on this intervention in resource-constrained settings. Here, we present a randomized controlled trial to evaluate the impact of a novel FNP in Nigeria.Methods:We designed the COST-FIN trial, a multi-site pragmatic single-blinded randomized controlled trial of newly diagnosed (<6 weeks from diagnosis) adults (≥18 years) with breast, colorectal, or prostate cancer at two tertiary cancer centers in Nigeria. Participants (n=200) will be randomized (1:1) to either the intervention (FNP) or the control arm and followed for 12 months. Data on key individual, treatment, and financial parameters will be collected via structured interviews and chart abstraction at baseline, 3, 6, and 12-month follow-up. In addition, participants randomized to the FNP will receive a tailored financial literacy assessment, financial planning support, and enhanced access to resources by trained financial navigators. Primary and secondary outcomes are Financial Catastrophe (FC) and Financial Distress (FD), respectively. Exploratory outcomes will include cost-related non-adherence and cost-effectiveness of the program. An interim analysis will be conducted when 50% of the estimated accruals reach 6 months of follow-up, with crossover if compelling evidence of benefit is demonstrated at that time point. All participants will be followed for 12 months from recruitment.Discussion:This first-of-its-kind study will provide evidence on the role of FNP in potentially eliminating financial barriers to cancer care in Nigeria. Given the country’s renewed interest in cancer control through the passage of the National Cancer Control Plan, findings from this study have the potential to influence policy reform and set the stage for further studies to evaluate the scalability and implementation of similar interventions in resource-limited settings.Trial registration:ClinicalTrials.govNCT06630962. Oct 8, 2024 (https://clinicaltrials.gov/study/NCT06630962)

Problem Statement. The modern turbulent environment is characterized by high dynamics, uncertainty, and increasing risks, rendering traditional enterprise financial security systems – oriented towards retrospective analysis and manual procedures –ineffective. Their reactive nature leads to significant delays in identifying liquidity and solvency threats, which is critically dangerous under martial law, cyber threats, and global supply chains. The purpose of the article is to develop a conceptual framework for building a transformed enterprise financial security system based on the principles of digital controlling and continuous dynamic planning. Methods used in the study: theoretical and methodological analysis, synthesis of scientific approaches, comparative analysis, and systems modeling. The hypothesis of the study was the assumption that the deep integration of strategic digital controlling tools, advanced analytical technologies (AI/ML, Big Data), and dynamic planning into a single information-analytical loop enables a transition from a reactive to a proactive model of financial security, enhancing its adaptability and antifragility. Summary of the main material. The evolution of financial control from elementary supervision to strategic digital controlling is explored. A three-level system architecture is substantiated, including: 1) the data and integration level (forming a single source of truth); 2) the analytics and modeling level (diagnostics, prediction, prescription); 3) the decision-making and automation level (KRI, automated actions). It is demonstrated how integration with the dynamic planning process forms mechanisms for anticipatory response. Comparative tables illustrate the transformation of information-analytical support characteristics and the positive impact of the proposed system on key financial security parameters. Conclusions. The transformation of the financial security system based on digital controlling is a strategic imperative. It transforms the financial function from an administrative-accounting unit into a strategic partner capable of proactive risk management. The proposed model ensures a transition from response to prevention, forming enterprise resilience and viability. The main implementation challenges are investments in IT infrastructure, development of digital competencies, and ensuring cybersecurity. Further research should be directed towards: 1) developing more complex autonomous AI algorithms for risk management; 2) researching the integration of blockchain technologies to enhance transparency and audit efficiency; 3) developing industry standards and framework models for digital financial security.

This study conducted a statistical evaluation of the impact of measuring employee productivity in Nigerian corporate organizations, with Fidson Healthcare Plc as the case study. The primary objective was to employ statistical tools to assess the influence of employee productivity measurement on various financial parameters. The evaluation primarily explored the relationship between performance appraisal results, mean appraisal scores (MAS), and financial variables including Net Profit, Total Revenue, and Net Current Assets. Data for this research was sourced from the company's Finance and Human Resource Department. Statistical techniques including Analysis of Variance (ANOVA), Correlation, and Regression were utilized for analysis, with data analyzed using Statistical Package for Social Sciences (SPSS) version 20 and Microsoft Excel. The findings suggested that there was no strong correlation between employee productivity measurement and organizational performance. However, it was concluded that improved alignment of the performance appraisal process with corporate goals could enhance the predictive value of employee productivity measurement using performance appraisals for organizational performance.

Being universal approximators, neural network based methods form the backbone of modern scientific computing by providing techniques to approximate solutions of mathematical problems where analytical solutions are either difficult or impossible to derive. These methods transform continuous models, such as differential or integral equations, into a machine learning model, which can be trained up to the desired accuracy level. In the current study, we investigated the dynamics of a nonlinear fractional financial chaotic model. Chaotic characteristics of the underlying system are explored through a feedforward neural network trained in an autoregressive manner. Chaos is captured successfully for various fractional orders and for multiple settings of the system’s parameters. It is also validated through the benchmark properties of chaos, such as Lyapunov exponents and the Kaplan–Yorke dimension. The trained model is also tested qualitatively through the 2D and 3D attractors for each combination of fractional and financial parameters. Existence and uniqueness of the solutions are also proved. The memory-dependent behavior of the model is successfully emulated by the proposed feedforward neural network framework. Furthermore, a detailed stability analysis is performed for selected fractional orders. To regulate chaotic oscillations, a feedback gain matrix control strategy is implemented. This approach effectively suppresses chaos and guides the trajectories toward desired equilibria. Finally, a stability analysis of the controlled system is conducted to confirm convergence and robustness of the proposed control strategy.

The article explores a methodological approach to the strategic structuring of business directions in a motor transport enterprise (MTE) under martial law and post-war recovery. Problem statement. The study focuses on Strategic Business Units (SBUs), which enable the evaluation of transport service efficiency and the optimization of managerial decisions. The main issue addressed is the absence of adapted methodologies capable of assessing internal business group positions in unstable transport markets. Unresolved aspects of the problem. Traditional approaches, particularly the BCG matrix, overlook enterprise-specific dynamics, the weight of product groups in sales, variations in transport revenues, and market turbulence, limiting their accuracy and applicability. Purpose of the article. The study aims to develop and justify a methodological approach to structuring MTE business directions through SBU identification, enabling effective management under high uncertainty caused by wartime and recovery conditions. Presentation of the main material. A stepwise SBU evaluation method is proposed, based on analyzing sales revenues, their change trends (K and T indicators), and internal financial and production parameters. For each group, the relative share in total sales and revenue change rate are calculated to classify business directions by strategic relevance: development, investment, support, optimization, or transformation. The methodology ensures an objective assessment of internal business group positions, facilitates balanced SBU portfolio formation, considers potential risks, and substantiates managerial decisions on investment, development, or optimization. Its practical significance lies in creating a strategic planning tool adaptable to enterprise resources, industry features, and organizational forms, ensuring effective operation under uncertainty. Conclusions. Further research will focus on digital models for automated SBU monitoring to enhance managerial responsiveness, strategic flexibility, and financial resilience, thereby ensuring the universality and reliability of the proposed methodology in diverse practical contexts.

The purpose of the article is to substantiate and model a competency-oriented management system for private medical institutions based on the synergy of managerial competence, digital transformation, and organizational security. The research methodology relies on a combination of a systemic synergetic approach, economic and mathematical modeling, and scenario analysis. The empirical base consists of the financial indicators of leading private medical institutions in Ukraine for 2020–2024 (40 observations). To quantitatively assess the impact of managerial factors on performance, the least squares method was applied, and a regression model with a determination coefficient of 0.82 was constructed, confirming its strong explanatory power. Within the synergetic approach, an integrated efficiency model is proposed. Scenario modeling (Scenario A: increased managerial competence; Scenario B: enhanced digital transformation; Scenario C: higher organizational security; Scenario D: combined growth of the three subsystems) showed that the greatest impact on management efficiency is achieved under Scenario B, where a 20 percent increase in the business-leadership and digital-maturity subsystems raises the integrated efficiency indicator by 8.7 percent. Meanwhile, the combined Scenario D ensures a projected increase in return on assets to 31.5 percent in 2026. The scientific novelty lies in the formalization of a competency-oriented synergetic management model for private medical institutions, which integrates quantitative financial parameters and intangible managerial factors into a single system. The practical significance of the results lies in the possibility of applying the model for strategic planning, evaluating the effectiveness of digital transformation, and strengthening the financial resilience of medical organizations. The findings confirm that optimal managerial synergy is achieved when managerial competencies, business leadership, and security mechanisms evolve in a balanced manner.

Investor decision-making is often shaped by research of a range of financial and non-financial parameters of the investee company for predicting investment profitability, understanding future risks and challenges associated with the product or market as a whole, creating a mental image/profile of the company with its advantages and disadvantages. Psychological research from the 1970s and on allowed us to conceptualize real-world decision-making (DM), understand the limitations of human information processing and the influence of personal cognitive, emotional features bounding our rationality, yet allowing us to make optimal decisions. The research gave us an understanding of cognitive mechanisms of heuristics and biases, which somewhat simplify the complex informational flow and optimize the process of mental analysis, yet can create some systematic errors or skewed perceptions of the situation or a sense of overconfidence. This study explores how ethical considerations function as heuristics in guiding investment behavior, particularly in the context of ESG (Environmental, Social, and Governance) performance. Drawing from behavioral finance theory, we hypothesize that ethical reputation acts as a cue that influences perceived trustworthiness, and depending on the intentions of the investor (fast gain or slow grow) can affect their decisions differently. Using a sample of 37 investors, we conducted a mixed-methods study combining decision-making and mental heuristics profile and personal DM factors with the self-perceived effectiveness of investment behavior and proneness to consider ESG metrics. The results demonstrate that long-term investors systematically utilize ESG data and, through the lens of heuristics and biases (the interconnection yet to be researched), impact DM. Ye,t considering ESG metrics important, the investors did not necessarily perform ESG information-seeking behavior. These findings highlight the intersection between ethics and cognitive processing in financial contexts. Ethical cues appear to serve as intuitive filters in investment judgments, suggesting that proper ESG reporting and communication may significantly shape market behavior through psychological channels.

Introduction. A temporary decline in incidence and mortality caused by influenza and acute respiratory viral infection (ARVI) during the COVID-19 pandemic did not decrease their significance for population health. Despite a well-known regulation role that belongs to social and environmental conditions in phase transformations of an epidemic process, there are scarce studies in research literature that focus on investigating complex effects produced by environmental factors on the clinical course of the analyzed infections.The aim of this study. To identify social-and hygienic determinants of influenza and ARVI incidence.Materials and methods. The study results were obtained by using open data published by Rosstat and departmental materials of Rospotrebnadzor over the period between 2010 and 2022. Overall, 232 indicators were used in the study; they described hygienic and epidemiological aspects, peculiar climatic conditions, financial and social parameters as well as people’s habits and healthcare infrastructure in Russian regions taken on the annual basis.Results. The study found several key factors affecting influenza and ARVI incidence. They included the following indicators: volumes of pollutant emissions into ambient air (r=0.12 and r=0.23 respectively); proportion of workers exposed to working conditions not conforming to safe standards (r=0.13–0.29); UVB, average monthly horizontal radiation and average precipitation volumes (r=0.12–0.7); the proportion of urban population (r=0.13 and r=0.59); volumes of alcohol sales (r=0.27–0.53); gross regional product (r=0.08–0.42); the number of middle-level healthcare workers (r=0.14; r=0.36); capacity of polyclinics (r=0.41) and others.Limitations. The study limitations are related to the analyzed dataset (selected indicators and time period).Conclusion. The identified peculiar effects produced by these factors as well as lifestyles can be used for substantiating medical and preventive activities aimed at improving the sanitary-epidemiological situations in the country.Compliance with ethical standards. The study did not require the conclusion of a biomedical ethics committee or other documents (the study was performed using publicly available official statistics).Contributions: Zaitseva N.V. — research concept and design, editing the text; Kleyn S.V., Kiryanov D.A. — writing and editing the text; Glukhikh M.V. — data collection and statistical analysis, writing the test. All authors are responsible for the integrity of all parts of the manuscript and approval of the manuscript final version.Conflict of interest. The authors declare no conflict of interest.Funding. The study had no sponsorship.Received: August 1, 2025 / Accepted: November 3, 2025 / Published: December 19, 2025

In this paper, innovative strategic trends in the gold mining industry are identified and analyzed. Based on the analysis, such an innovative strategic priority as the dewatering of gold mining tailings is justified. The reasons for the insufficient implementation of relevant technologies have been identified, for example, such as incomplete cost accounting, high expected implementation costs, and pricing of water resources. The strategic interests of the parties have been identified, and the basis for their coordination has been proposed. The international experience is studied, in particular the experience of state regulation of water consumption in mining in Chile. The application of a fair price to fully account for the cost of water resources is justified. An overview of research on the economic aspects of tailings dewatering is given, and the specifics of calculating the financial parameters of projects in determining the net present value of projects and the internal rate of return are revealed. The stages of the project’s life in gold mining, including those after the mine closure, are analyzed. The periods of income and expenses, classified by object, are highlighted. The role of introducing tailings dewatering technologies to reduce project uncertainty is substantiated. The results of the study can be applied in practice by enterprises of the gold mining industry, in the development of industry and corporate strategies, as well as in further research.

Aim . To use the case of one of the ELECTRE methods to identify and demonstrate the applicability of the development of indexes for pairwise comparison of alternatives (RIPSA) for selecting automated information systems (AIS) taking into account criteria associated with AIS cybersecurity and cyber risk insurance. Methods . The paper uses the ELECTRE I method that is well-described in well-known publications. The ELECTRE group of methods belongs to the RIPSA approach that aims to compare multi-criteria alternatives. One of the Russian pioneers of this approach was the RAS member Larichev O.I. The introduced criterion called the “three-digit majority criterion of AIS cybersecurity taking into account insurance” uses elements of three-digit majority logic. Results . The paper shows the applicability of the RIPSA approach, ELECTRE I specifically, for selecting AIS as regards the examined criteria associated with AIS cybersecurity, taking into account cyber risk insurance. A modified criterion has been developed that is new as regards cyber security in the context of cyber liability insurance and is based on a three-digit majority logic. Specifically, it allows expressing and taking into account in a logical and mathematical form some features of AIS insurance protection given the inherent cyber risks, as well as the ability of AIS to independently withstand the three categories of cyber attacks. Conclusion . The three-digit majority logic-based technical and economic quality criterion is applicable to not only technological and organisational parameters or characteristics of AIS cyber security, but the financial and economic parameters or security characteristics of insured AIS as well. The ELECTRE methods of developing pairwise alternative comparison indexes are applicable both in the analysis, organisational and technological measures to reduce various AIS-related cyber risks, and in associated insurance protection. The paper shows that the developed integral criterion, namely the three-digit majority logic for multi-criteria alternatives, allows using the ELECTRE methods with two criteria less.

This article emphasizes that financial security is a derivative of a company's financial condition, which in turn depends on the results of its business operations. The full-scale war has led to a decline in production levels across key economic sectors and a reduction in corporate revenues. Given that the war has created an operating environment with heightened threats and risks, it is crucial to ensure a financial condition that guarantees financial security. The article identifies the factors negatively affecting the financial condition and security of enterprises and provides recommendations for their improvement. The study presents analytical data reflecting the financial consequences of the war on businesses in 2022 and quantifies the indirect losses incurred by core economic sectors. The authors calculated and analyzed key financial indicators for large and medium-sized enterprises across various economic activities, including the equity ratio, current liquidity ratio, working capital, and the share of stable funding sources. Operational and overall performance indicators were also examined, allowing for an assessment of potential threats to financial security. Considering that the normative values for financial indicators are relaxed during wartime, the financial condition of most enterprises can be considered satisfactory. However, the low equity ratio, which averages 0.32 across the economy and poses a significant threat to financial security, is a particular concern for companies in all industries. The best financial performance as of the first quarter of 2025 was demonstrated by enterprises in the processing industry, while the worst was seen in the temporary accommodation and food service sectors. Among large and medium-sized industrial enterprises, pharmaceutical manufacturers showed the strongest financial parameters, while chemical and chemical product manufacturers had the weakest. From the perspective of ensuring financial security, special attention is required for those enterprises whose financial indicators are significantly below normative levels.

This study aims to assess the effect of PSAK 57 implementation on the quality of financial statements in Indonesian public companies. PSAK 57 is significant because it facilitates the presentation of uncertain liabilities and assets in an honest, relevant, and transparent manner, which ultimately strengthens stakeholder confidence in these financial statements. This study applies a descriptive quantitative approach using secondary data, namely annual reports and financial statements from public companies listed on the Indonesia Stock Exchange (IDX) within a certain period. The evaluation was conducted to measure the degree of compliance with PSAK 57 and its relationship with financial statement quality parameters, such as relevance, reliability, and comparability. The research findings indicate that the implementation of PSAK 57 has a positive impact on the quality of financial statements, as entities that consistently adopt this standard demonstrate higher levels of transparency and accountability. This conclusion conveys a crucial message to practitioners and regulators to continue to deepen their understanding and implementation of PSAK 57 in order to strengthen the quality and integrity of financial reporting in Indonesia.