Bad Loans Research Articles

Elucidating the Non-Performing Assets in Indian Banking Sector: Does Macroeconomic Factor Matter?*

Using the system generalized methods of moments on panel data set of 45 selected Indian commercial banks from 2005–2006 to 2019–2020, the study investigates the determinants of non-performing assets (NPAs), taking into account macroeconomic and bank-specific factors. The study finds evidence of a persistent effect in stressed assets. The profitability ratio, operational capacity, cost efficiency and aggressive lending negatively and significantly affect the NPAs. The negative impact of the profitability ratio implies that less efficient banks are more exposed to bad loans. While cost efficiency discourages the NPAs, on the other hand, higher credit deposit ratio (operational capacity) suggests that a well-diversified portfolio leads to lesser probability of loan defaults. The probability of loan default is high when more advances are released to the economy’s weaker and vulnerable sectors (high-priority sector lending). Small-sized banks are more efficient in NPAs management than large-sized banks. Various macroeconomic variables, such as lending rates and credit growth in the banking industry, significantly affect the NPAs. The higher lending rate adversely affects borrowers’ repayment capacity, leading to more stressed assets. Therefore, to maintain bad assets within a bearable limit, policymakers should take macroeconomic determinants into consideration.

Unintended consequences of the introduction of specialized bankruptcy courts: evidence from zombie lending

We examine the economic consequences of the introduction of specialized bankruptcy courts (SBCs) from the perspective of zombie lending, using a sample of Chinese listed zombie firms in the 2016–2021 period. We find that the introduction of SBCs unexpectedly and significantly increases zombie lending, given the perverse incentives for banks and the intervention of local governments. The mechanism is that the introduction of SBCs improves the firms' bankruptcy efficiency, which increases the exposure probability of banks' bad loans and regional unemployment. To conceal these bad loans and unemployment, banks and local governments have to dramatically increase zombie lending. Thus, while better bankruptcy procedures are typically assumed to discourage zombie lending, we show that the introduction of SBCs may instead encourage such lending by exacerbating conflicts among creditors and political-economic frictions.

Benefits for the Greek economy from resolving bad loans and zombie firms

We examine the type and magnitude of negative externalities stemming from “zombie” firms in the Greek economy, focusing on investment, employment and productivity. For this purpose, we use a panel dataset of Greek firms broken down by size and sector of economic activity for the period 2002-2021. A descriptive analysis reveals a high positive correlation in the trends between non-performing business loans and the number of zombie companies in the Greek economy over the last twenty years. Through quantitative analysis, significant direct and indirect effects emerge from the degree of density of zombie firms at the total economy and sectoral levels. First, healthy firms outperform zombie firms in terms of investment growth, employment growth and productivity levels. Second, a high concentration of capital in zombie firms negatively affects the rate of investment growth of healthy firms in specific sectors of economic activity. Third, a high concentration of capital in zombie firms forces healthy firms to increase their overall productivity in order to survive. Fourth, a high concentration of capital in zombie firms prevents the reallocation of capital to more productive investments across firms and sectors of activity. Finally, younger and larger companies generally perform better in terms of investment and employment growth, and productivity levels. Overall, a faster resolution of zombie firms and non-performing corporate loans, both on and off bank balance sheets, allows a more efficient allocation of resources and can boost investment, employment and growth rates in the Greek economy in the medium to long term.

Settlement of Bad Loans with Guarantee of Dependent Rights at Banks and Auction Houses Based on the Law on Dependent Rights No.4 of 1996 (Case Study: Decision No.550/Pdt/2019/PT MDN)

The interaction between economic development and the banking sector, particularly in the provision of credit, is crucial, with the resolution of non-performing loans (NPLs) being a significant issue. This study, titled "Resolution of Non-Performing Loans with Collateral Rights in Banks and Auction Houses," aims to investigate the mechanisms for resolving NPLs through the execution of collateral rights as stipulated by Law No. 4 of 1996. Utilizing Verdict No. 550/Pdt/2019/PT MDN as a case study, the research employs normative and legal analysis methods to explore the implementation of collateral rights in the auctioning of collateral assets when debtors default on their loans. The findings reveal the legal procedures and effectiveness of collateral execution in mitigating NPLs. The study concludes that the proper application of collateral rights laws can significantly aid in resolving NPLs, with implications for improving banking sector stability and credit recovery processes.

PENGARUH KREDIT BERMASALAH TERHADAP LIKUIDITAS DAN PROFITABILITAS PADA KOPERASI ARTA MAKMUR DI REJOSO NGANJUK

This research aims to examine the effect of non-performing loans consisting of substandard loans, doubtful loans and bad loans on liquidity and profitability. The sampling technique uses the quota sample method. Data was obtained from secondary data from the monthly report of the Arta Makmur Rejoso Nganjuk Cooperative with canonical correlation with the SPSS version 25 program. The canonical weight shows the highest variable results, namely bad credit 1.08872 and profitability 0.88710. The canonical loadings show the highest variable results, namely bad credit 0.95348; liquidity 0.94779 and profitability 0.99907. Canonical cross-loading shows the highest variable results, namely substandard credit 0.65801; bad debt 4.21658 and profitability 4.09189. The results of the hypothesis research show that the variable that has no influence is doubtful credit. From the results of canonical weights, canonical loadings and canonical cross-loading, it can be concluded that there is no significant influence between substandard credit and liquidity. There is no significant influence between doubtful credit and liquidity. There is a significant influence between bad credit and liquidity. There is a significant influence between substandard credit on profitability. There is no significant influence between doubtful credit on profitability. There is a significant influence between bad credit and profitability. There is a significant influence between non-performing loans on liquidity and profitability.

Analyzing Loan Default Trends and their Influence on Bank Profitability

Banks boost the e­conomy's growth. But, banks have major issues with overdue­, unpaid loans called Non-Performing Assets (NPAs). Many re­ports show NPAs are rising rapidly, showing the problem's se­riousness. Researche­rs study NPAs, looking at their status, causes, impacts, and effe­cts. On a large scale­, the rising bad debts hinder e­conomic growth and affect diverse pe­ople, businesses, and banks. This article­ gives a brief summary of banking, explains bad de­bts, and looks at possible reasons for their incre­ase. Our main goal is to clarify the major impacts of many bad debts on banks. We­ carefully study each potential e­ffect using existing rese­arch. Studies show NPAs hurt banks. Our re­search uses data already colle­cted to understand NPA problems in India. We­ carefully examined pape­rs and statistics. NPAs cause major issues for banks. Profits go down. Credit ratings worse­n. Banks cannot lend as much. Funding becomes more­ costly. We cite rese­arch to explain each effe­ct. This gives a full picture of how NPAs impact banks. To conclude, this pape­r combines the effe­cts of bad loans and suggests ways banks might take to fix this problem. It stre­sses how crucial immediate actions and smart plans are­ to get through this tough situation and protect the banking industry's stability and stre­ngth. KEY WORDS Banking sector, NPAs, economic growth, deterioration, financial stability, credit risk, crisis, research findings, bank profitability, credit rating.

Foreclosed Collateral as an Alternative for Bad Credit Settlement in Indonesia

Credit loans have the risk of not fulfilling payment obligations. Therefore it is necessary to bind collateral to get a repayment with collateral. if it cannot be anticipated anymore, then lousy credit will occur and must be resolved immediately, credit settlement usually uses the execution of mortgage rights. However, there are alternative settlements regulated in article 12 an of the law of the Republic of Indonesia number 10 of 1998 concerning banking law, namely foreclosed collateral in practice, there are problems regarding the implementation of foreclosed collateral by verdict number 183/pdt/2020/PT SMG and verdict number 24/pdt.g/2019/PN Pti. This study aimed to analyze the implementation of foreclosed collateral as a way to resolve the problem of bad loans. The research method used is normative, using secondary data obtained from library research, including primary, secondary and tertiary legal sources. Therefore, the implementation of the foreclosed collateral taken over by verdict Number 183/PDT/2020/PT Smg is valid because it is through a voluntary submission mechanism, and verdict Number 24/Pdt.G/2019/PN Pti is invalid because there is no agreement and has an impact on debtors and creditors feel harmed.

National Economic Stimulus Policy to Reduce Non-Performing Loan Risk on Msme Debtors Affected by Covid-19 Disturbing Banking Performance and National Financial System

Purpose: This study aims to analyze the effectiveness of stimulus policies implemented by The Financial Services Authority (OJK) in response to the current pandemic, specifically in aiding MSME debtors impacted by Covid-19 and mitigating the occurrence of bad credit. Method: The research adopts a normative approach combined with both statutory and empirical juridical methodologies to examine the implementation of stimulus policies by OJK, particularly focusing on the provisions outlined in POJK Number: 11/POJK.03/2020. Results and conclusion: The findings reveal that the economic stimulus policy introduced by the government has the potential to assist MSME debtors adversely affected by Covid-19 and alleviate the burden of bad loans. The extension of credit restructuring until March 2022 provided by this policy is identified as a key factor in facilitating increased lending activities and fostering accelerated national economic growth. Research implications: This study contributes to the understanding of the efficacy of stimulus measures in addressing economic challenges posed by the pandemic, particularly in the context of MSMEs. It underscores the importance of timely and targeted interventions in supporting vulnerable sectors and safeguarding financial stability. Originality/value: By combining normative and empirical juridical approaches, this research offers a comprehensive analysis of the implementation of stimulus policies by OJK and their impact on MSME debtors. The identification of specific provisions, such as credit restructuring extensions, provides valuable insights for policymakers, financial regulators, and stakeholders involved in formulating effective economic recovery strategies.

Machine Learning-Based Loan Default Prediction in Peer-to-Peer Lending

The peer-to-peer (P2P) lending market has recently undergone significant growth, transforming traditional lending practices. However, this evolution brings with it unique challenges, particularly in managing credit risk and ensuring the reliability of loan approvals. Accurate prediction of loan defaults remains a pivotal aspect of risk management in this sector. This study introduces a comprehensive approach to improve bad loan prediction in peer-to-peer (P2P) lending, sourcing Lending Club data. In the face of challenges posed by imbalanced datasets and risk management in the loan industry, our methodology significantly enhances prediction accuracy, particularly in identifying bad loans. The study implements a comprehensive process that includes data cleaning, feature engineering, feature selection, balancing the dataset and machine learning models, achieving a noteworthy accuracy rate over 92% and recall rate above 87%. This research advances academic understanding of loan prediction and generates real-world impact. The accurate models identifying explanatory provide a valuable framework for improving decision-making and strategic planning in P2P lending platforms.

Klasifikasi Menggunakan Algoritma K-Nearest Neighbor pada Imbalance Class Data dengan SMOTE. (Studi Kasus: Nasabah Bank Perkreditan Rakyat “X”)

<p class="AbstractEnglish">Rural Banks (Bank Perkreditan Rakyat/BPR) provide financial services to micro-businesses and low repayment communities, especially in rural areas. The main activity of the bank is lending. Customer credit classification is expected to assist BPR in anticipating potential bad loans. K-Nearest Neighbor classify current and potential bad credit status based on customer data from BPR “X” in Central Java in October 2022. K-Nearest Neighbor is effective against a large amount of training data and works based on the nearest neighbor. There is an imbalance class data which causes the classification process to focus more on the majority class. Imbalance class data is handled using Synthetic Minority Oversampling Technique (SMOTE) as an oversampling approach. Classification with the addition of SMOTE can improve the evaluation of classification accuracy, especially G-mean. G-mean is the most comprehensive measurement in term of accuracy, sensitivity and specificity in evaluating classification performance on imbalance class data. The results of this research were able to increase g-mean to 58.55% and sensitivity to 45.46% by implementing SMOTE. Based on the classification results, it is concluded that K-Nearest Neighbor with SMOTE at k = 19 and a proportion of training data to test data of 70:30 is a more appropriate classification model to use for customer credit status.</p><p class="AbstractEnglish"> </p><p><strong>Keywords: </strong>Credit Status; K-Nearest Neighbor; Imbalance Class Data; SMOTE</p>

Investigation of Bad Credit in P2P Lending Based on Personal Character in Indonesia

This research examines Indonesian P2P lending and bad loan management by analyzing borrower characteristics. The large value of problematic loans is a key signal for this investigation. The Big Five Personality Approach is used to survey P2P lending users. This study solely examines if the Big Five personality traits affect evaluation. On March 5–18, 2023, 17 P2P lending sites gathered data from 197 respondents for two weeks. Data validation continued until 11 respondents were pruned. The remaining 186 respondents' data was evaluated using SPSS. The management process yielded two hypothesis tests, the T-test and the F-test, which showed that the Big Five personality significantly affects present assessment activities. F-Test findings show the Big Five Personalities have a big impact concurrently. These two factors suggest that the Big Five Personalities may evaluate decision support systems for borrower recommendations.

Determinants of the Credit Cycle: A Flow Analysis of the Extensive Margin

AbstractExamining two decades of loan‐level data on Italian bank loans to households and businesses, we find that credit fluctuations primarily result from changes in the number of borrowers (extensive margin). Employing a flow approach, we decompose the extensive margin into inflows and outflows, revealing that borrower inflows significantly contribute to total borrower volatility. Moreover, borrower inflows exhibit greater volatility than outflows, are procyclical, and lead the business cycle. Utilizing a shift‐and‐share instrument derived from sectoral borrower inflows, our findings reveal that local markets experiencing increased credit demand exhibit a loosening of lending standards and a rise in bad loans. This sheds light on the intricate relationship between credit demand and financial instability at the local level.

Strategies for effective management of loans: A case study of keystone Bank plc

In this study, strategies for effective loans management using keystone bank plc as a case study was investigated. Survey research methodology was adopted via structured questionnaire containing both open and closed ended questions administered to 120 respondents who were management staff of Keystone bank at both head and corporate offices. Likert scale was used in the questionnaire formulation and Hypothesis was tested using chi square at 0.05 level of significance. The result revealed that corporate loan portfolio diversifications is the most effective technique of loan portfolio management. Also, preference function allows banks compare risky portfolios and rank them according to the degree of satisfaction. Problems encountered with management of loan portfolio were identified to include insider abuse, increased perception of risk regarding the solvency of other banks within the banking system and anticipated decline in the value of the collateral used by the banks to secure the loans. The result obtained indicated that there is significant relationship between loan portfolio management and productivity. It is recommended that Keystone bank should focus on exposure assessment involving the credit review and a valuation of the collateral based on the data provided by the credit applicant. Also, effective risk management based on the risk regarding the solvency of other banks within the banking system should be implemented. Adequate provisions for bad loans that have very little chance of being recovered should be provided. In conclusion, there is significant relationship between loan portfolio management and productivity.

Can Human Capital Explain Income-Based Disparities in Financial Services?

Abstract Research shows that access to high-quality financial services varies with local income and wealth. We study how financial firms’ internal allocation of human capital contributes to these disparities. Using a near-comprehensive panel of over 350,000 U.S. mortgage loan officers, we document large and persistent differences in productivity and performance. We find that firms’ hiring and promotion practices allocate workers with less experience or poor track records to branches serving low-income customers. Further, the consequences of poor performance differ by location: low sales, bad loans, and misconduct are more tolerated in low-income branches, exacerbating income-based disparities in financial services.

Non-Performing Assets - Content Analysis and Suggestions for Resolution

Non-performing assets also known as Bad Loans have played havoc with financials of Scheduled Commercial Banks (SCBs) in India from 2015 to 2022. The NPAs started piling up after an abnormal growth in advances of these banks in the developmental phase unleashed by the Government of India after the 2008 Global crises. The period witnessed a rise in manufacturing and infrastructure project financing imbued with over optimism of promoters for success and profitabilty. Banks vied with one another to share a piece of pie for opportunities in sectors like Iron and Steel, Mining, Aviation and Road Construction. The spurt in advances of banks also witnessed a simultaneous rise in their bad loans. NPAs have impacted negatively the financial performance of various Indian banks over the years (Sharma & Dhiman 2023). Though Non-Performing Assets cannot be wiped off completely from the advances portfolio of the banks yet it is important to control this critical parameter of financial performance of the banking sector. Management of NPAs is significant for bank profitability and growth of the economy. Bad debts or NPAs are not always created due to the fault of a bank. Though managements of different banks try their best to reduce NPAs but due to various macroeconomic, borrower related and at times bank related specific factors it is not possible to eliminate these altogether from the banking book. However prudent board policies, proper pre-sanction appraisal of borrowers and post sanction forensic audit of disbursements to large borrowers by the banks can go a long way in curbing the menace of bad loans.

ANALYZING NON-PERFORMING ASSETS: A COMPREHENSIVE STUDY OF THEIR IMPACTS ON PROFITABILITY OF SELECTED BANKS IN INDIA

The present study explores the complex domain of non-performing assets (NPAs) in a subset of Indian banks. The selected institutions are focal points for comprehending the complex dynamics around non-performing assets (NPAs), as they are representative of a range of sizes and policies. The research provides a comprehensive overview of the current NPA environment by not only estimating the NPAs but also closely examining their features, sectoral distribution, and emerging trends. The study assesses the complex relationship between non-performing assets (NPAs) and the profitability of the chosen banks concurrently, providing detailed insights into the mutually beneficial nature of these components. This in-depth analysis explores the complex world of non-performing assets (NPAs) in a few Indian banks. The selected institutions, which are representative of various sizes and approaches to operations, act as hubs for comprehending the complex dynamics related to non-performing assets. In addition to calculating the NPAs, the study examines their attributes, sectoral distribution, and written from a variety of angles, the study captures the opinions of several writers, each of whom adds a special perspective on non-performing assets. This diversity adds value to the research, generating insights that go beyond scholarly interest to have real-world ramifications for stakeholders, legislators, and bank executives.The research goes beyond conventional financial measures to navigate the difficulties presented by non-performing assets (NPAs), presenting these assets as dynamic obstacles requiring a comprehensive comprehension. The results are intended to help Indias banking industry become more robust and adaptable so that it can deal with the complexities of non-performing assets (NPAs) with skill and foresight. In the end, this study aims to be a symphony of viewpoints, providing a rich tapestry of insights that might help define a stable and sustainable future for Indias banking sector. KEYWORDS: Non-performing Assets, Indian Banking Sector, Profitability Analysis, Bad Loans, Financial Health, Credit Risk,Loan Portfolio, Financial Stabilty,Banking Operations, Risk Assessment, Banking Operations, NPA trends.

The criticality of credit recovery in banking system stability: A GMM estimation

This study examines the criticality of credit recovery on banking system stability in Nigeria using data from 2007 to 2020. The system generalized method of moments (SYS-GMM) was used to analyze the data and determine the presence of cointegrating relationships among the variables. The findings revealed that credit recovery positively and significantly influences banking system stability. It was discovered that the recovery rate positively and significantly impacts the banking system stability in the short and long terms. In contrast, recovery expense only negatively and significantly affects the banking system in the short term. This implies that credit recovery is critical in business endeavors and operations for banks. Hence, the longer the delay in recovering bad debts, the more banks lose the opportunity to earn income from substitute investments, and collateral may lose value. Therefore, this study recommends that banks' management aggressively pursue the repayment of bad loans and maintain favorable and minimal recovery expenses, particularly with external debt recovery agents, to ensure that the cost of recovery is not higher than the amount recovered.

Discovering the relationship between bad loans (NPAs) and the profitability of public sector banks in India: A panelanalysis

Discovering the relationship between bad loans (NPAs) and the profitability of public sector banks in India: A panelanalysis

Enhancing Financial Performance Assessment: A Fundamental Analysis of PT. Bank Syariah Indonesia, Tbk. in The Capital Market (2019-2023)

This study aims to provide an overview of the financial performance of PT. Bank Syariah Indonesia, Tbk. uses real data in the capital market based on fundamental analysis using descriptive quantitative research. This study uses secondary data, namely the financial statements with samples of 2019 before the merger until 2023 Quarter 3. This data was analyzed using fundamental analysis. The results found that PT. Bank Syariah Indonesia, Tbk. in these 2 years there has been an increase in free float by 4.92%, but this does not affect its share price, which experiences fluctuations, moving downward in 2022 to 2023, around the lowest price of IDR 1,200,-. Besides it, the fundamental matrix assessment shows the amount of revenue obtained by PT. Bank Syariah Indonesia, Tbk from the P/E ratio of 14.61 and the P/S ratio of 3.15. Meanwhile, the value (P/E) in 2022 has decreased dramatically to 11. Growth and profitability moved positively from 2018 to 2022 amounting to 22 trillion. Net margin, which had fallen in 2019, rose dramatically, especially in 2022, to 20% and routinely fulfilled its obligations to investors by distributing dividends in 2021 of 17,952 and 9,235 in 2022. PT. Bank Syariah Indonesia, Tbk. provides quite a lot of financing to customers with a ratio of 3: 1 compared to customer deposits. This needs to be considered, careful and pay attention to providing financing, especially in consumption financing which will result in bad loans or liquidity problems

Analisis Penyelesaian Kredit Macet di PNPM-Mandiri: Studi di Desa Mersam, Provinsi Jambi

Bad credit is a condition where the customer or debtor is unable to pay his debts at a predetermined time as promised at the beginning of the credit agreement. The problem that occurs is where the disbursed PNPM funds should be used for productive loans or business capital. However, in reality in Mersam Village, Kab. Batanghari Province. Jambi PNPM funds are used by some people for personal needs, causing bad credit, where customers are unable to pay installment payments every month because the funds borrowed are only used for personal needs. This study aims to find out: 1) How to settle bad loans at PNPM Mersam Village, Kab. Batanghari Province. Jambi; 2) How is the settlement of bad loans at PNPM Desa Mersam Kab. Batanghari Province. Jambi from the perspective of Sharia Economic Law. This research is a qualitative research type of empirical legal approach, the types and sources of data used are primary and secondary data. The collection of data used is interviews and documentation. Based on the research conducted, the results of the interviews and the conclusion were obtained that the resolution of bad loans was carried out by PNPM by means of family deliberations and giving an extension of time (rescheduling). In terms of Sharia Economic Law, efforts to settle bad loans in Mersam Village are not contrary to Islamic law, but instead they carry out Islamic law rules in dealing with bad loans that occur in Mersam Village.