oalib

OALib Journal期刊

ISSN: 2333-9721

费用：99美元

投稿

时间不限

( 2026 )

( 2025 )

( 2024 )

( 2023 )

自定义范围…

匹配条件： “Capital Solvency Ratio” ，找到相关结果约1000条。
列表显示的所有文章，均可免费获取
第1页/共1000条
每页显示 条
Artificial Intelligence and Capital Solvency Ratios: Theoretical Foundations, Empirical Evidence, and Systemic Implications  [PDF]
Marcello Forcellini
Technology and Investment (TI) , 2025, DOI: 10.4236/ti.2025.164011
Abstract: This paper investigates the interplay between artificial intelligence (AI) integration and capital solvency ratios within financial institutions, combining theoretical frameworks with empirical evidence to assess systemic implications. It explores how AI-driven decision-making and algorithmic trading influence capital adequacy, risk management, and market stability, highlighting potential feedback loops and regulatory challenges. The study underscores the necessity of harmonizing AI governance with prudential capital requirements to mitigate emerging systemic risks and enhance financial resilience in evolving market ecosystems.
THE CONSEQUENCES OF THE CAPITAL REGULATION IN CREDIT INSTITUTIONS ACCORDING TO THE BASEL I AGREEMENTS
Mariana VLAD,Mihaela TULVINSCHI
Annals of the Stefan cel Mare University of Suceava : Fascicle of the Faculty of Economics and Public Administration , 2009,
Abstract: Capital is one of the key factors to be considered when the safety and soundness activity of bank is evaluation.An adequate capital based serves as a safety network for a variety of ricks to which a bank is expose d in the course ofits business. He absorbs the possible losses and provided a basis for maintaining depositor confidence in bank. Also,the capital is the ultimate determinant of a bank’s lending capacity. A bank’s balance sheet cannot be expanded beyondthe level determined by its capital adequacy ratio. Therefore, the availability of capital consequently determines themaximum level of assets.
BENCHMARKING INCIDENCE OF DISTRESS IN THE NIGERIAN BANKING INDUSTRY ON ALTMAN SCALE
Oforegbunam Thaddeus Ebiringa
Serbian Journal of Management , 2011,
Abstract: This paper applied the Altman’s model in the prediction of distress in the Nigerian bankingindustry. Three banks (Union bank, Bank PHB and Intercontinental Bank) declared distress duringthe period of the study were used as case studies. Four years financial statistics prior to distress wasused to compute the most discriminating financial ratios that were substituted into the Altman’smodel. The result of the analysis shows that Altman’s model significantly predicted the distress stateof each of the bank at 0.001level. The implication being that Altman’s model can be validly appliedin the prediction of the health state of banks in Nigeria. The paper recommends for further researchon the domestication and adaptation of the model in order to improve its predictive ability.
Real Estate Enterprise Capital Structure Analysis and Optimization—The Case Study of Kaisa Group  [PDF]
Zhaohui Li
Modern Economy (ME) , 2015, DOI: 10.4236/me.2015.69092
Abstract: Real estate industry is one of the pillar industries of the national economy. As the real estate industry develops rapidly, this capital-intensive industry’s funds demand is soaring. Therefore, in order to guarantee the healthy development of the real estate industry, a reasonable structure of enterprise capital is very important. From the perspective of corporate capital structure, this article takes Kaisa as an example for analysis. Kaisa’s financing activities in recent years are combined to understand the overall financing situation, and then adopt relevant financial indicators to analyze Kaisa’s solvency comprehensively. After the defects of capital structures are identified, several suggestions in optimizing capital structure will be given.
Further Results about Calibration of Longevity Risk for the Insurance Business  [PDF]
Mariarosaria Coppola, Valeria D’Amato
Applied Mathematics (AM) , 2014, DOI: 10.4236/am.2014.54061
Abstract:


In life insurance business, longevity risk, i.e. the risk that the insured population lives longer than the expected, represents the heart of the risk assessment, having significant impact in terms of solvency capital requirements (SCRs) needed to front the firm obligations. The credit crisis has shown that systemic risk as longevity risk is relevant and that for many insurers it is actually the dominant risk. With the adoption of the Solvency II directive, a new area for insurance in terms of solvency regulation has been opened up. The international guidelines prescribe a market consistent valuation of balance sheets, where the solvency capital requirements to be set aside are calculated according to a modular structure. By mapping the main risk affecting the insurance portfolio, the capital amount able to cover the liabilities corresponds to each measured risk. In Solvency II, the longevity risk is included into underwriting risk module. In particular, the rules propose that companies use a standard model for measuring the SCRs. Nevertheless, the legislation under consideration allows designing tailor-made internal models. As regards the longevity risk assessment, the regulatory standard model leads to noteworthy inconsistencies. In this paper, we propose a stochastic volatility model combined with a so-called coherent risk measure as the expected shortfall for measuring the SCRs according to more realistic assumptions on future evolution of longevity trend. Finally empirical evidence is provided.


An Assessment of the Market Risk Solvency Capital Requirement Simplifications for Insurance Undertakings  [PDF]
Thomas Poufinas, Panagiota Tsitsika
Theoretical Economics Letters (TEL) , 2018, DOI: 10.4236/tel.2018.811153
Abstract: The Solvency II regulatory framework has been implemented as of January 1st, 2016 and among other things it introduced economic risk-based capital requirements across all EU Member States for the first time, applicable for insurance and reinsurance undertakings. Similar to Basel II whose scope is banks, the Solvency II directive provides a new regime based on three pillars for insurers and reinsurers: 1) pillar 1: harmonized valuation and risk based capital requirements, 2) pillar 2: harmonized governance and risk management requirements and 3) pillar 3: harmonized supervisory reporting and public disclosure. The Solvency Capital Requirement (SCR) should correspond to the Value-at-Risk of the basic own funds of an insurance or reinsurance undertaking subject to a confidence level of 99.5% over a one-year period. The Solvency II directive provides a range of methods to calculate the SCR. This allows insurance or reinsurance undertakings to choose a method that is proportionate to the nature, scale and complexity of the risk that is measured. In order to calculate the SCR, an insurance undertaking can use a fully internal model, the standard formula and a partial internal model, the standard formula with undertaking-specific parameters, the standard formula as it is or a simplification. When introducing a simplification, the SCR estimate could deviate from the calculation without the simplification. A simplification could lead in important/crucial information missing from the SCR calculation. In some occasions the SCR is overestimated and in some others it is underestimated. It is therefore of interest to find the range of this deviation, potential bounds—if any and the effect it can have on the required capital. In this paper we attempt to measure this deviation for simplifications pertaining to the interest rate risk for insurance companies.
Influence of the prudential supervision over the capitalization of the Romanian insurance market
Laura Elly NAGHI
Theoretical and Applied Economics , 2013,
Abstract: In a decade when all activities are globalized, including insurance, the recent focus of the supervisory authorities became the leveling of the legal framework concerning the solvency requirements of the companies acting on the market (as a consequence of the 2008 crisis, much more acute in USA than in Europe, where Basel Agreement decreased the fall of the banking sector). The present paper analyses the way in which the main solvency regimes applied at international level influence the equity of the insurance companies, especially the increase in the solvency capital required by the supervisors, taking into consideration the risk profile of the company. Moreover, the paper provides a blueprint of the methods to ensure the financial stability of the national industry, in order to respond adequately to systemic and systematic risks.
Corporate Financial Performance in the COVID-19 Pandemic  [PDF]
Annisa Wantri Fajriyanti, Wiyarni Wiyarni
American Journal of Industrial and Business Management (AJIBM) , 2022, DOI: 10.4236/ajibm.2022.121004
Abstract: The purpose of this study was to determine the condition of the company’s financial performance during the COVID-19 pandemic measured by the ratio of liquidity, solvency, profitability, and activity. The type of data used in this research is secondary data including financial reports in consumer goods companies in the food & beverage sub-sector, pharmaceutical companies, and telecommunications companies listed on the Indonesia Stock Exchange (IDX) in 2020. The financial report data is processed using the finance ratios including liquidity ratios (current ratio, quick ratio), solvency ratio (Debt to Assets Ratio, Debt to Equity Ratio), activity ratios (Fixed Assets Turnover, Total Assets Turnover Ratio), and profitability ratios (Gross Profit Margin, Return on Equity), Return on Investment). Then draw conclusions from that ratio analysis, and make further analyses. From the research results obtained by PT. Indofood CBP Sukses Makmur based on the liquidity ratio, the solvency ratio is declared good, the activity ratio and the profitability are declared less efficient and optimal, but the GPM is declared good. Then the financial performance of PT. Telekomunikasi Indonesia based on the liquidity ratio is stated to be not
Risk Aggregation by Using Copulas in Internal Models  [PDF]
Tristan Nguyen, Robert Danilo Molinari
Journal of Mathematical Finance (JMF) , 2011, DOI: 10.4236/jmf.2011.13007
Abstract: According to the Solvency II directive the Solvency Capital Requirement (SCR) corresponds to the economic capital needed to limit the probability of ruin to 0.5%. This implies that (re-)insurance undertakings will have to identify their overall loss distributions. The standard approach of the mentioned Solvency II directive proposes the use of a correlation matrix for the aggregation of the single so-called risk modules respectively sub-modules. In our paper we will analyze the method of risk aggregation via the proposed application of correlations. We will find serious weaknesses, particularly concerning the recognition of extreme events, e. g. natural disasters, terrorist attacks etc. Even though the concept of copulas is not explicitly mentioned in the directive, there is still a possibility of applying it. It is clear that modeling dependencies with copulas would incur significant costs for smaller companies that might outbalance the resulting more precise picture of the risk situation of the insurer. However, incentives for those companies who use copulas, e. g. reduced solvency capital requirements compared to those who do not use it, could push the deployment of copulas in risk modeling in general.
Insurance Companies’ Solvency Management within de Framework of Logistic Capital Management Theory
Edita JURKONYTE
European Journal of Interdisciplinary Studies , 2011,
Abstract: Various models of economic growth, addressing the growth trends of country's economy, production, population and other structural objects are focused on the mathematical description of growth rates, taking into account the initial state of the object. One of the solutions to the capital growth rate assessment problem is offered by logistic capital management theory, which is based on the assumption that under the real circumstances the capital usually cannot grow at the same pace for a long time. The article presents an insurance companies’ logistical solvency management model, prepared in accordance with provisions of the logistic capital management theory adjusted in the field of insurance. This model is structurally divided into three main elements: (a) the insurance company's solvency assessment, (2) logistical capital management decisions (3) provisions of the Solvency II project. Logistical insurance companies’ solvency management model shows capital management solutions’ implementation capabilities in the insurance sector, focusing on insurance solvency assessment. This model allows to determine the insurance company’s solvency in respect to the portfolio of an individual client, insurance type and all company, compared the estimated need for insurance benefits (discounted at the current value) with the factual capacity of the insurance company, i.e. available resources to ensure solvency. Also, this model allows planning the insurance activity by making insurance pricing, depending on the projected benefits and fees’ characteristics.
第1页/共1000条
每页显示 条


Home
Copyright © 2008-2020 Open Access Library. All rights reserved.