Default Risk Research Articles

The Effect of AI-Enabled Credit Scoring on Financial Inclusion: Evidence from One Million Underserved Population

We studied the effect of adopting an AI-enabled credit scoring model by a major bank on financial inclusion as measured by changes to the approval rate, default rate, and utilization level of a personal loan product for the underserved population. The bank served over 50 million customers and used a traditional rule-based model to evaluate the default risk of each loan application. It recently developed an AI model with higher prediction accuracy of default risk and used the AI model and the traditional model together in assessing loan applications for one of its personal loan products. Although the AI model could be more accurate in estimating default risk, little is known about its impact on financial inclusion. We investigated this question using a difference-in-differences approach by comparing changes in financial inclusion of the personal loan product adopting the AI model to that of a similar personal loan product without adopting the AI model. We found that the AI model enhanced financial inclusion for the underserved population by simultaneously increasing the approval rate and reducing the default rate. Further analysis attributed the enhancement in financial inclusion to the use of weak signals (i.e., data not conventionally used to evaluate creditworthiness) by the AI model and its sophisticated machine learning algorithms. Our finding is consistent with the statistical discrimination theory, as the use of weak signals and sophisticated machine learning algorithms improves prediction accuracy at the individual level, thus reducing the reliance on group characteristics that often lead to financial exclusion. We elaborated on the development process of the AI model to illustrate how and why the AI model can better evaluate the underserved population. We also found the impacts of the AI model heterogeneous across subgroups, and those with missing weak signals saw smaller improvements in the approval rate. A simulation-based analysis showed that simplified AI models could still increase the approval rate and reduce the default rate of the underserved population. We further discussed the compliance and generalizability issues about using AI and privacy-sensitive data in credit scoring. Our findings provided rich theoretical and practical implications for social justice by documenting how an AI model designed for improving prediction accuracy can enhance financial inclusion.

The Role of the Biliary in the Implementation of Decisions on Applications for Execution of Property Security in Semarang District Court

In the implementation of credit in the community, there is a risk of default in repayment of credit. To anticipate default, creditors ask for collateral from debtors. The collateral can be in the form of material. If default still occurs, then one way to resolve it is through the courts. The process of resolving the default is decided by the Head of the District Court in each region, after which the Head of the District Court will assign a Bailiff to carry out the execution. The duties and functions of the Bailiff are not limited to carrying out the execution, but also the administrative duties of the court. In practice, the Functional Bailiff has been on duty in the field, but the guidelines for implementing the Bailiff's duties are still lacking. This then causes the Bailiff to also face obstacles. This research was written using a descriptive qualitative method with primary and secondary data sources as its supporters.

МЕТОДИ ОЦІНКИ РІВНЯ ІНВЕСТИЦІЙНОЇ ПРИВАБЛИВОСТІ ПІДПРИЄМСТВА В ПОВОЄННИЙ ПЕРІОД

The article examines and describes the methods of assessing the investment attractiveness of an enterprise, such as quantitative and qualitative. Each of the components of these methods is highlighted. The expediency of using a comprehensive approach that combines these methods is determined, and the need to use additional conditions, such as risk assessment, comparison of the dynamics of indicators and their comparison with the indicators of other companies in the same industry, is also indicated. Attention is focused on the properties of assessing the investment attractiveness of the enterprise in the post-war period, such as the level of destruction – the degree of damage to property and infrastructure can significantly affect the restoration of work and require significant investments. It is important to assess the scale of destruction, the terms and cost of restoration works; infrastructure restoration – availability of electricity, water, transport and other critical resources may be limited. It is necessary to take into account the risks of delays and additional costs associated with infrastructure restoration; government support – governments of countries affected by war often offer programs to help businesses. It is important to know about the available programs, their conditions and opportunities for receiving assistance; changing market environment – Consumer needs and expectations may change after the war. It is necessary to research new market trends and adapt your strategy to them; competition – war can lead to changes in the competitive environment. It is important to assess new competitors, their strengths and weaknesses; risks – political risks, risks of default, risks of changes in legislation may be higher in the post-war period. It is important to conduct a thorough analysis of risks and develop a plan to minimize them and uncertainty – the economic situation and political climate in the post-war period can be unstable. It is important to consider the factors of uncertainty and to respond flexibly to changes.

Prepayment and Default risk: A Review

Prepayment and Default risk: A Review

La gouvernance d’entreprise: Un déterminant du management du risque bancaire

The aim of our study is to propose ownership structure and board of directors as two innovative risk management criteria. Our mixed-method approach, combining a qualitative, exploratory study with 7 executives and a confirmatory quantitative study with 78 executives, aimed to assess the impact of these mechanisms on the risk of corporate failure. The results significantly demonstrate the influence of ownership structure and board of directors on default risk. Thus, examination of the interactions between the various players in the governance system reveals a relationship of support and complementarity rather than one of discipline. Our study confirms that the configuration of the ownership structure and the composition of the board of directors play a key role in preventing corporate credit risk. Thus, these results suggest that optimizing these mechanisms may not only reduce the risk of default, but also provide a perspective for a comprehensive and proactive approach to bank credit risk.

Unveiling the Nexus between Climate Change Performance, Default Risk, and Financial Stability in European Union Countries

Unveiling the Nexus between Climate Change Performance, Default Risk, and Financial Stability in European Union Countries

EFFECTS OF FINANCIAL MARKET DEVELOPMENT ON BANK CAPITALIZATION RATIO: EVIDENCE FROM COMMERCIAL AND NON-COMMERCIAL BANKS IN TANZANIA

Financial market development in many developing countries is a series of financial market reforms aimed at improving the market and the financial system in general. Theoretically, major reforms that improve the stock market are expected to increase bank performance by reducing bank risk of default by increasing the bank capitalization ratio. This results in stability in the financial market and banking sector. Nonetheless, empirical literature in addition shows that the quality of the financial market may be at high risk following the reforms process because of the integration effects of the markets across the countries or regions. A good example of this is the global financial crisis of 2007/2008. Based on this background, the present study investigates the extent to which the financial market development in Tanzania influences the bank's capitalization ratio (commercial and non-commercial banks). Employing a two-step system GMM technique in a dynamic panel dataset regression model for the investigation for a period of 2012 to 2021, while macroeconomic and bank-specific variables have been used as control variables. We proxy financial market development as stock market development. This study finds that stock market development in Tanzania measured in terms of stock market turnover ratio improves bank capitalization ratio with the goals of enhancing the financial market and maintaining stability in the banking sector.

The impact of ESG performance on the credit risk of listed companies in Shanghai and Shenzhen stock exchanges

<abstract> <p>A more precise and rigorous assessment of the impact of environmental, social, and governance (ESG) performance in business necessitates evaluating various firm characteristics. This study, focused on the ESG impact on enterprise credit risk, employed logistic models that incorporated the ESG rating index alongside other financial-related factors, including organizational structure, risk, and performance. The data were selected from all related listing companies in the Shanghai and Shenzhen stock exchanges. The results affirmed that (1) the risk of default decreased with improved ESG performance; (2) the return on assets, asset turnover ratio, leverage ratio, and operating income growth rate were the main financial factors affecting the default probability of enterprises; and (3) including ESG variables in the prediction model significantly improved the prediction accuracy of the model. The potential policy implications are presented in three perspectives. Businesses should prioritize developing good governance, fulfilling social obligations, and protecting the environment. Second, investors should integrate ESG ratings when making investment strategies. Third, the regulatory authorities are obligated to rapidly harmonize the ESG rating criteria and gradually develop the enterprise ESG information disclosure framework.</p> </abstract>

Climate Threats to Bank Default Risk and Financial Stability: Any Market Concern about the ECB 2022 Climate Risk Stress Test?

Climate Threats to Bank Default Risk and Financial Stability: Any Market Concern about the ECB 2022 Climate Risk Stress Test?

Regulatory Bank Stress Test Results: Do Scenario Characteristics and Time Horizons Affect the Market Valuation of Bank Default Risk?

Regulatory Bank Stress Test Results: Do Scenario Characteristics and Time Horizons Affect the Market Valuation of Bank Default Risk?

Estimation of default risk through Merton's distance to default model: an empirical study of four Indian Public Sector Banks

Estimation of default risk through Merton's distance to default model: an empirical study of four Indian Public Sector Banks

Early Warning Research on Bond Default Risk Based on KMV Model

Early Warning Research on Bond Default Risk Based on KMV Model

Decentralized Finance: Principles of Functioning, Infrastructure, Risks

The article analyzes the differences between centralized and decentralized exchanges in the cryptocurrency market. The author notes the impact of bankruptcies of centralized representatives who provided services in the cryptocurrency market on the interaction of users with decentralized finance instruments. The publication considers the key representatives of decentralized finance, their capitalization, available capital, and technological developments. It substantiates the advantages and risks of using decentralized finance instruments and studies the differences between centralized, decentralized, and algorithmic stablecoins. To assess the capitalization of decentralized finance instruments, the asset value indicator TVL (Total Value Locked) is used. TVL represents the amount of assets currently placed in a particular decentralized finance instrument or protocol. The RWA narrative is significant in the crypto space as it demonstrates increased interconnectedness. DeFi, previously isolated from TradFi, has now become an integral part of a more holistic financial ecosystem. Blockchain technology has demonstrated its potential for transformation through real-world use cases. Real-world assets (RWAs) are an attractive option due to the large traditional finance market. While they offer benefits such as portfolio diversification and enhanced returns, it is crucial to mitigate default risk. Platforms like Goldfinch have a proven track record. Tokenizing RWAs can increase market participation and financial inclusivity. The study's results indicate significant development of decentralized finance instruments over the past three years. This is evidenced by the amount of capital invested in these instruments and the number of users, despite the technological and regulatory risks associated with them. The study's conclusions indicate that despite the technological novelty, users are increasingly interested in interacting with decentralized finance instruments. However, users face difficulties in understanding how these instruments work and in gaining experience with these products. The comparative analysis by Saif Ahmed Abdulhakeem and Qiuling Hu titled "CeFi vs. DeFi — Comparing Centralized to Decentralized Finance" systematically contrasts Centralized Finance (CeFi) with Decentralized Finance (DeFi) across legal, economic, security, privacy, and market manipulation dimensions. It aims to provide a structured approach for distinguishing between CeFi and DeFi services, emphasizing DeFi's transparency and user control advantages. However, unresolved issues in decentralized finance, such as regulatory frameworks and risk assessment, necessitate further research. The study also underscores the importance of improving user experience design and overcoming adoption challenges for DeFi. In their academic discourse titled "Powered by Blockchain Technology, DeFi (Decentralized Finance) Strives to Increase Financial Inclusion of the Unbanked by Reshaping the World Financial System," Abdulhakeem and Hu analyze DeFi's potential to enhance financial inclusion for the unbanked. They highlight the pivotal role of blockchain, particularly Ethereum, in enabling DeFi. While acknowledging DeFi's decentralization benefits, the article suggests it as a complement rather than a replacement for traditional finance. It advocates for future research on integrating DeFi with global banking systems and improving user interface and security. Overall, while recognizing DeFi's transformative potential, the article underscores the need for ongoing research to address challenges and integrate DeFi into mainstream finance seamlessly.

EUROPEAN FINANCIAL MARKETS CONNECTEDNESS AND MONETARY POLICY COMMUNICATION STRATEGY:SPILLOVER EFFECTS FOR CENTRAL AND EASTERN EUROPE

This study evaluates the impact of unconventional policy announcements by the European Central Bank (ECB) on the interconnectedness of sovereign credit default swaps (SCDS) markets in the European Union (EU) from 2009 to 2014. The findings suggest that ECB's unconventional policy measures reduced sovereign default risk not only in Eurozone nations but also in Central and Eastern European countries. To investigate the transmission of monetary policy effects across European countries, we employ the Diebold & Yilmaz connectedness framework along with an event-study approach. Our analysis reveals robust evidence of substantial positive spillovers from ECB monetary policy measures to all EU countries, effectively shielding the SCDS market from adverse shocks. Among various policy tools, we observe that asset purchase programs enhance overall connectedness, while mixed policy measures bolster within-cluster connectedness. Furthermore, our results highlight the efficacy of specific monetary policy instruments, indicating that asset purchase programs and quantitative easing are particularly effective in reducing sovereign risk. Keywords: communication strategy, financial markets, monetary policy, sovereign risk, Central and Eastern Europe

Research on the Financial Credit Risk Management Model of Real Estate Supply Chain Based on GA-SVM Algorithm: A Comprehensive Evaluation of AI Model and Traditional Model

By combining machine learning AI model with traditional credit risk measurement model, this paper aims to more accurately measure the credit default risk of real estate enterprises. Through professional credit management knowledge, the integration of these two models can fill the gaps of traditional models outside of financial data, and use the research experience of traditional models in the financial field to provide guidance for machine learning. This paper focuses on the key issues of capital intensity, exploration of Supply Chain Finance Growth and Credit Risk Control within the Real Estate Sector. By combining qualitative and quantitative methods. Through literature research and empirical analysis, this paper develops a supply chain finance credit risk assessment index system tailored for small and medium-sized enterprises operating in China's real estate sector. The index system comprises 23 risk assessment indicators, and comprehensively considers many factors such as corporate financial status and market environment. Then, a credit risk assessment model for small and medium-sized real estate enterprises is developed from a supply chain finance perspective, utilizing genetic algorithm optimization for Support Vector Machine (GA-SVM)., and the advantages of this model compared with the traditional model in accuracy and generalization ability are verified through comparative analysis of experiments. The research results can help reduce the information asymmetry in the real estate industry, enhance the credit rating evaluation process for small and medium-sized enterprises, and furnish references to aid commercial banks in credit and credit risk management within the real estate supply chain finance sector.which has important theoretical and practical value.

Corporate social responsibility and forward default risk under firm and industry heterogeneity

Corporate social responsibility and forward default risk under firm and industry heterogeneity

To burn or not to burn: governance of wildfires in Australia.

Globally, wildfires are increasing in extent, frequency, and severity. Although global climate change is a major driver and large-scale governance interventions are essential, focusing on governance at smaller scales is of great importance for fostering resilience to wildfires. Inherent tensions in managing wildfire risk are evident at such scales, as objectives and mandates may conflict, and trade-offs and impacts vary across ecosystems and communities. Our study feeds into debates about how to manage wildfire risk to life and property in a way that does not undermine biodiversity and amenity values in social-ecological systems. Here, we describe a case study where features of adaptive governance emerged organically from a dedicated planning process for wildfire governance in Australia. We found that a governance process that is context specific, allows for dialogue about risk, benefits, and trade-offs, and allows for responsibility and risk to be distributed amongst many different actors, can provide the conditions needed to break down rigidity traps that constrain adaptation. The process enabled actors to question whether the default risk management option (in this case, prescribed burning) is aligned with place-based risks and values so they could make an informed choice, built from their participation in the governance process. Ultimately, the community supported a move away from prescribed burning in favor of other wildfire risk management strategies. We found that the emergent governance system has many features of adaptive governance, even though higher level governance has remained resistant to change. Our study offers positive insights for other governments around the world interested in pursuing alternative strategies to confronting wildfire risk.

In the Radiance of Enlightenment: The Influence of Nontheistic Religions on Corporate Default Risk

In the Radiance of Enlightenment: The Influence of Nontheistic Religions on Corporate Default Risk

Study on contagion of debt default risk of the secured party in the guarantee chain—From the perspective of small and medium-sized enterprises

Study on contagion of debt default risk of the secured party in the guarantee chain—From the perspective of small and medium-sized enterprises

Effects of Digital Credit on Small Business Performance in Obunga, Railways Ward, Kisumu County, Kenya.

Small and Micro Enterprises play an important role in economic development of any nation by harnessing human capital, use of raw materials and technology. They require enough funds to facilitate expansion of operations, develop new products, hire new staff and acquire new facilities. Lack of capital and financing conversely has been identified as a major factor affecting their performance leading to their failures. Innovations in financial technology in the form of digital credit have taken advantage of these financing gaps and have come up with powerful tools to mitigate financing barriers faced by small businesses. This study sought to address the effects of digital credit on small business performance in Obunga, Railways ward in Kisumu, Kenya. The business performance was determined through operating cash flow, Sales volume and Net profit margin. Asymmetric Information theory and Default Risk Theory of Credit were selected to anchor this study. The study adopted descriptive research design. The target population was 454 Small and Micro Enterprises while the sample size was 212 Small and Micro Enterprises. The study adopted both stratified and simple random sampling techniques. Primary data was collected using structured questionnaires and interviews. Secondary data was collected through reviewing available records regarding digital credit and small business performance. The study adopted content validity. The data collected was analyzed using the Statistical package for social sciences version 24.0. Data was analyzed using descriptive statistics. The study findings conclude that the performance of the SMEs could be seen from profit margins, sales when they access digital credit.The study in addition suggests that the fast growth of fintechs had increased the cost of borrowing to SMEs and their repayment problems even though they offer flexible loan contracts to SMEs who have the ability to determine their own preferred loan repayment schedule. The study recommends the managers and owners of SMEs in Obunga ward to adopt an entrepreneurial mind-set that would support their ability to better gain financial access from various financial institutions Based on the study findings, it is also recommended that the government mobile loan institutions should consider lowering the costs involved in lending the credit. Lastly, the study recommends the managers and owners of SMEs in Obunga ward to make use of available flexible repayment options to borrow what their businesses actually require.