Lending Strategy Research Articles

IMPACT OF CAPITAL ADEQUACY RATIO ON OPERATING PERFORMANCE, PROFITABILITY AND RETURN RATIO: A COMPARISON BETWEEN SELECTED PUBLIC AND PRIVATE SECTOR BANKS IN INDIA

The aim of the study was to understand impact of capital adequacy ratio on operating performance, profitability and return ratio and understand this as a comparison between select public sector banks and private sector banks. For the purpose of this study, panel data was collected from twelve sample Indian banks over a period of ten years (2014-2023). These banks included six public sector banks and six private sector banks. Descriptive analysis, independent sample t-test and simple regression were performed on the data. It was found that private sector banks perform better than public sector banks. The private sector banks demonstrate stronger financial performance, higher efficiency, better asset quality and more aggressive lending strategies compared to public sector banks. These differences highlight the need for public sector banks to adopt more efficient practices and improve their financial health to compete effectively with private sector banks.

Harnessing Soft Information to Promote Financial Inclusion: The Case of Business Lending by a Native CDFI

AbstractNative Community Development Financial Institutions (NCDFIs) promote financial inclusion in financially underserved Native communities by adopting innovative lending strategies, including designing their own soft-information-based measures of borrower risk. Drawing on business loan data from one prominent NCDFI, a nonprofit loan fund, we examine to what extent the NCDFI-generated borrower risk measures help explain the NCDFI's loan performance and pricing above and beyond the effect of the credit score, a conventional credit-bureau-produced, hard-information-based metric. All else equal, both loan delinquency hazard and loan interest rate are robustly predicted by one of the NCDFI's two proprietary soft-information-based measures, the character score, but do not vary with the other one, commitment to business score. The credit score is an important determinant of loan delinquency hazard but, all else equal, does not exhibit a detectable relationship with the loan interest rate. We do not find evidence of noteworthy interactions among the three NCDFI-used borrower risk measures. Our study offers evidence in support of the unique underwriting practices and relationship-based lending operations that characterize the NCDFI industry.

DMBs Credit Disbursements and Real Sector Financial Performance in Nigeria

he study examines the impact of DMBs credit disbursements and real sector financial performance in Nigeria over the period from 1994 to 2023. The credit sources considered were; commercial banks, though study extended its insights into merchant banks, microfinance banks, and development banks and how they influenced classified sectors like; the agricultural, industrial, and service sectors. The study employed secondary data gotten from the CBN statistical Bulletin. The study employed an Autoregressive Distributed Lag (ARDL) estimation. The findings reveal that the R-squared values vary significantly across models, indicating differing levels of predictive accuracy. The agricultural sector shows the highest R-squared value of 0.9981, suggesting that credit from these institutions has a substantial impact on this sector’s contribution to GDP. Conversely, the industrial sector exhibits the lowest R-squared value of 0.9907, indicating a lesser degree of predictability and impact from credit types. The service sector demonstrates an intermediate R-squared value of 0.9910, reflecting a moderate level of influence from financial credit. The findings indicate varied effects of different types of credit on sectoral contributions. Commercial banks’ credits did not significantly influence the agricultural sector but showed a significant positive impact on the service sector. In contrast, merchant banks’ credits had a significant effect on both the agricultural and service sectors, while their impact on the industrial sector was not significant. Microfinance banks’ credits demonstrated a marginally significant impact on the agricultural sector but had no significant influence on the industrial and service sectors. Development banks’ credits did not significantly affect the agricultural or industrial sectors but had a significant positive impact on the service sector. Based on these findings, the study recommends that commercial banks focus on increasing credit support to the service sector to sustain its contribution to GDP. Merchant banks should enhance their credit support to the agricultural sector to leverage its potential for economic growth. Microfinance banks are encouraged to refine their lending strategies to better impact the agricultural sector, possibly through targeted programs that address specific needs of small-scale farmers. Development banks are advised to continue their support to the service sector, ensuring that credit interventions are aligned with sectoral growth objectives. Keywords: DMBS, Commercial Bank Credits; Real sector; Nigeria.

Sustainable lending strategies: a framework for enhancing climate resilience in industrial loan portfolios

Sustainable lending strategies: a framework for enhancing climate resilience in industrial loan portfolios

Business Model and Strategy for Sustainable Lending of State-Owned Banks in Indonesia

Currently, banks are facing challenges in fulfilling the interests of stakeholders, not only from an economic point of view, but also in terms of environmental, social, and governance (ESG) aspects. This is due to the increasing concern for sustainability issues, including lending activities. Lending activities constitute the largest portion of bank assets and are the largest contributor to bank revenues. Thus, banks need certain business models and strategies to encourage sustainable lending growth; otherwise, it will be difficult for banks to fulfill stakeholder’s interests and support sustainable development goals. This study aimed to build a sustainable business model and select sustainable lending strategies in state-owned banks in Indonesia using a value chain approach. The development of a sustainable business model utilizing a triple-layer business model canvas (TLBMC) is based on the results of previous research and sustainability report data of the three state-owned banks. The formulation of strategy selection as the key driver of sustainable lending utilized the analytical hierarchy process (AHP) based on expert respondent data collected through questionnaires. This research showed that the lending distribution business model at state-owned banks in Indonesia, which was built using the TLBMC framework, can realize sustainability goals in the form of a sustainable lending business model. Furthermore, this sustainable business model can be used as a basis for selecting sustainable strategies. In addition, the AHP results yielded alternative strategies in the form of the market development and penetration of green loans and micro, small, and medium enterprises (MSMEs) as the key drivers of sustainable lending growth.

Enhancing Financial Decision-Making: Predictive Modeling for Personal Loan Eligibility with Gradient Boosting, XGBoost, and AdaBoost

This study aims to improve the prediction of personal loan eligibility through the application of advanced machine learning techniques. Accurate prediction of creditworthiness is crucial for financial institutions to mitigate risks and optimize their lending processes. We evaluated three algorithms: Gradient Boosting, XGBoost, and AdaBoost, using a comprehensive dataset containing demographic and banking information. Among these, XGBoost proved to be the most effective model, achieving an accuracy, precision, recall, and F1 score of 0.95. These results demonstrate XGBoost's superior ability to accurately identify individuals likely to repay loans, making it an invaluable tool for enhancing decision-making in loan approvals. By leveraging XGBoost, banks can reduce the risk of defaults, streamline their operations, and provide better customer service, ultimately leading to more efficient and reliable lending strategies.

Risk contagion in interbank lending networks: A multi-agent-based modeling and simulation perspective

The interbank lending network, while facilitating transactions, poses risk contagion in the banking system. To address challenges in existing research, this paper models the interbank lending network using a multi-agent approach and generates a dynamic network through a bidirectional matching mechanism(BiMM). Additionally, We divide banks into three categories based on realistic bank balance sheet data. Given the fact that banks of different categories exhibit different degrees of contagion, we propose the weighted DebtRank (W-DebtRank). Then, comprehensive simulation analysis is conducted on the risk contagion of heterogeneous banks in the dynamic network using W-DebtRank. The proposed method addresses four issues: the heterogeneity of banks, the dynamic nature of networks, the practicality of lending strategies, and the comprehensiveness of risk analysis. The model is validated using the SRISK metric and the Monte Carlo-based SYMBOL simulation model. Through multiple perspectives in simulation experiments, the risk contagion process among banks is deeply investigated in our paper.

FACTORS INFLUENCING SMALL AND MEDIUM ENTERPRISES' DECISION TO APPLY FOR BANK LOANS: A QUANTITATIVE ANALYSIS IN VIETNAM

This study investigates the determinants influencing the decision of Small and Medium Enterprises (SMEs) to apply for bank loans. Drawing upon a theoretical framework encompassing human capital, firm attributes, business strategy, and information asymmetry, we develop a model to predict SMEs' propensity to seek bank financing. Employing a quantitative methodology in Vietnam, we utilize a hypothetical-deductive testing approach on primary data collected through questionnaires focusing on loan applications. Our findings reveal several significant factors influencing SMEs' inclination towards bank loans. Contrary to expectations, the business experience of a firm's owner exhibits no significant correlation with the likelihood of applying for a bank loan. However, variables such as the educational background of the firm's owner, firm size, collateral availability, and interest rates on loans exhibit negative associations with loan application propensity. Conversely, factors including the presence of comprehensive business plans and establishment of relationships with bankers during start-up phases demonstrate positive relationships with SMEs' inclination to apply for bank loans. This study contributes to the understanding of SMEs' financing decisions and provides valuable insights for financial institutions in designing tailored lending strategies to meet the diverse needs of SMEs.

Chinese Loan to Africa in the lens of Pragmatism Economics

This paper examined the reasons behind China’s decision to provide loans to African states, a group that had been traditionally been considered not creditworthy by MDBs. Utilizing a descriptive-explorative research method, primary to secondary data ranged from 1999 to 2022, and the framework of economic pragmatism, this paper analyzed and found some pragmatic implications. The findings concluded that China’s lending strategy was mostly motivated by a pragmatic approach aimed at gaining early access to African markets, securing vital natural resources, assisting Chinese corporations, and creating economic dependence. China’s loans were used to fund infrastructure projects, reducing logistics costs for Chinese businesses and diversifying foreign exchange reserves. This paper posited that China’s policy was driven by empirical facts, adaptiveness to global economic conditions, and a focus on concrete economic benefits, such as increasing imports from China and gaining access to natural resources. Therefore, this paper describes China’s efforts to strengthen its influence and obtain tangible economic advantages through its lending practices in Africa Keywords: Africa, China, Development Loan, Economic Gains, Political-Economy

The spillover effect of bank distress: Evidence from the takeover of Baoshang Bank in China

The recent US regional banking crisis has gained considerable attention due to its potential for contagion and amplification of shocks. This paper employs the difference-in-differences method to examine the spillover effects of a regional bank failure on its peer institutions. By focusing on the bankruptcy case of Baoshang Bank in China, which serves as a natural experiment, we show that the bank's bankruptcy leads to a substantial increase in the riskiness of its peers’ loan portfolios. Specifically, our findings reveal a more pronounced impact on group-based loans, while digital credit remains unaffected. This study introduces a novel mechanism through which bank distress spillovers, providing valuable insights for financial institutions to optimize their lending strategies and for policymakers to make informed policy and regulatory decisions.

The Effect of Financial Development and MFI’s Characteristics on the Efficiency and Sustainability of Micro Financial Institutions

The Micro Financial Institutions (MFIs) have been touted as development strategies for Emerging Markets and Developing Economies (EMDEs) which merits research into the effect of financial development on the efficiency and sustainability of the MFIs. The Efficient and sustainable MFIs significantly paved the way for the economic development of a country particularly in developing countries. Surprisingly there are very rare studies that examine the nexus of financial development, MFIs efficiency, and sustainability. Also, these studies are confined to the impact of financial development either on the efficiency or sustainability of MFIs. Addressing this gap, the study attempts to explore the country-specific and MFIs-specific factors which significantly affect the efficiency and sustainability of the MFIs. For this purpose, the study first determines whether financial development contributes to the efficiency and sustainability of MFI. Secondly, the effect of MFIs’ specific characteristics such as credit risk, market risk, liquidity risk, lending strategy, Development Financial Institutions (DFIs) funds management, financial outreach, and poverty alleviation on the efficiency and sustainability of MFIs. The study has been conducted for Bangladesh, India, and Pakistan consisting of a panel data set of 12 MFIs over a period spanning from 2008–2018 using Stochastic Frontier Analysis and Cobb Douglas production function regression analysis. Overall empirical analysis reveals that financial development has significantly affected the efficiency and sustainability of the MFIs. While specific characteristics such as poverty alleviation and DFIs funds management have been shown to improve MFIs efficiency whereas an increase in credit risk, lending strategy, and market risk decrease MFIs sustainability and liquidity risk along with an increase in financial outreach leads to a decrease in MFIs efficiency. The directions and magnitudes of the findings suggest the stakeholders for all three countries for the significant direction leads to the efficiency and sustainability of MFIs. Moreover, future research could strive to understand the aspects of financial development which negatively correlate with the MFIs’ efficiency and sustainability such as stringent tax policies, creditor rights protection, and implementation of rules and regulations.

Do Financial Linkages Ease the Credit Rationing of Forest Rights Mortgage Loans? Evidence from Farm Households in Fujian Province, China

Affected by the small scale of forest farmers’ land and the imperfect development of the forest land transfer market, China’s forest rights mortgage loans have suffered from more serious credit rationing. The application of financial linkage theoretically has the effect of solving credit rationing. However, previous studies on financial linkages have focused on the field of credit lending, whereas the applied studies in the field of mortgage lending are mainly case studies on transaction models, and empirical tests on the application of financial linkages in mortgage lending are lacking. Therefore, to fill this gap, this study analyzed the effect of financial linkage on credit rationing for forestry mortgage loans and the mechanism of action through a study of farmers in Fujian, one of the key collective forestry areas in China, using the PSM method with 785 sample values. The results show the following: (1) Financial linkages have a significant mitigating effect on supply rationing, demand rationing, and the total rationing of forest rights mortgage loans. Compared to non-participation, financial linkages significantly reduced total rationing by 15.2%, with a 5% reduction in supply rationing and a 10.2% reduction in demand rationing. (2) The impact of financial linkage differs significantly among heterogeneous farmers. It has a significant mitigating effect on supply rationing for small-scale farmers, but not for large-scale farmers; meanwhile, it better mitigates demand rationing for large-scale farmers than for small-scale farmers. (3) In the mechanistic test, financial linkages were found to moderate the relationship between the value of collateral and supply rationing for small-scale farmers, and transaction costs play an intermediary role in the relationship between financial linkages and demand-based rationing. According to the study results, in order to promote the development of forest rights mortgage loans, it is necessary to develop different lending strategies for heterogeneous farmers, to further encourage small- and medium-sized farmers to participate in financial linkages, as well as to further reduce the related transaction costs.

China’s Monetary Policy and the Loan Market: How Strong is the Credit Channel in China?

AbstractWe study the macroeconomic relevance of credit supply effects in the transmission of Chinese monetary policy. Using combinations of zero and sign restrictions in a structural vector autoregressive framework, we simultaneously identify monetary policy shocks and supply dynamics in the loan market. Our results show that policy shocks which coincide with loan supply effects account for roughly 60% of the overall effects of policy induced output dynamics. Moreover, we find that it takes roughly one year that banks adjust their lending strategies and loan supply effects unfold completely. Overall, our results provide robust empirical evidence that the credit channel constitutes an important and economically relevant transmission channel for monetary policy in China.

Strategy selection of inventory financing based on overconfident retailer

<p style='text-indent:20px;'>Overconfidence of financing enterprises in market demand will have a significant impact on their business decision-making and banks' decision-making. This paper constructs the demand function based on the retailer's overconfidence and establishes the profit functions of the retailer and the bank respectively. Through Stackelberg game analysis, the influence of the retailer's overconfidence on each decision variable can be analyzed. The study has the following findings. Firstly, overconfidence makes decision-making deviate from rational decision-making. Secondly, the relationship between loan-to-value ratio and overconfidence is affected by different factors when the banks know the market or do not understand the market. Thirdly, the relationship between retailer's default probability and overconfidence is different when the bank doesn't know the market or knows the market. Fourthly, when the bank does not understand the market but listen to the overconfident retailer's market analysis, he should choose fixed loan-to-value ratio for financing. The overconfident retailer can ask the bank to give a higher loan-to-value ratio to reduce the capital pressure. Fifthly, when the bank conducts market research, the bank should choose the variable loan-to-value ratio contract for financing, while the retailer only needs to make decisions according to the bank's lending strategy.</p>

A study of bank credit strategy based on logistic model

This thesis is based on logistic model and multivariate linear programming, using MATLAB to study the lending strategies of banks to MSMEs. We first analyzed the factors that can affect the credit risk of enterprises, and studied the influence of four factors on the credit risk of enterprises, namely, profit, development potential, supply and demand, and credit rating, and then used the data to measure the above four factors, and predicted the default risk index of each enterprise through logistic model, and to make the results more intuitive, we introduced the credit score A=100 × (1 - default risk index), thus providing a quantitative analysis of the credit risk of the enterprise. Then, we determined the interest rates of bank loans to enterprises with different credit ratings, and finally, we determined the credit strategy by considering the credit score. At the same time, we considered the case where there is no credit rating of enterprises, and to develop credit strategies for different enterprises, we first need to derive the credit score of each enterprise using the logistic model above, and then adjust the credit strategy by dividing the rating of each enterprise according to the ratio of each credit rating and the credit score above. The loans given to the enterprises of grades A, B, and C are taken as unknowns, and the total number of 100 million and each enterprise can only lend 100~1 million yuan are taken as restrictions, and the maximum value of the profit is solved by using multivariate linear programming to derive the loan amount for each grade of enterprises. Finally, the credit strategy is determined by ranking the enterprises in terms of their development potential and credit score, and lending the loans to each enterprise in turn.

A Snapshot of Sales and Risk Relations at Hungarian Banks in 2022

Banks’ corporate lending strategy changes from time to time, but in any case, the implementation of that strategy requires cooperation between two functions, namely the business (corporate/project contact persons, sales) and the credit approval (risk management or risk) team. Smooth cooperation may foster optimised decision-making, and improve the efficiency of banks’ processes, employee satisfaction and commitment, which, in turn, may reduce employee turnover. The benefits on the client’s side are transparency, reliability and predictability, which may increase confidence in, and satisfaction with, the bank. Therefore, it is worthwhile to review periodically how the two functions get along. We have taken such a ‘snapshot’ in our exploratory study of 2021/2022. In this study, we collected answers from 16 respondents working at banks in Hungary through an anonymous questionnaire and written in-depth interviews. The results show that the relations under scrutiny ‘leave room for improvement’. Our survey also focused on how cooperation between the two functions could be made better and more efficient. Setting up transparent and well-regulated internal processes at banks and reinforcing risk-awareness in employees proved decisive in responding to the challenges of the future.

A sustainable lending strategy considering the impact of dispositive factors

The article analyses the factors of credit relations of an organisation under modern economic conditions. The purpose of the study is to find ways to ensure sustainable development and improve bank credit activities. The relevance is determined in connection with the rapid growth of the population's debts and the accumulation of multiple risks. As a result of the research ways of perfection of credit relations of the bank on the basis of consideration of dispositive factors, including creation of clear system of subordination and further development of service system and development of the bank, analysis and estimation of solvency of the client are presented.

Dynamics of Asset Liability Management in Indian Public Sector Banks: A Comprehensive Analysis of Deposit and Lending Practices

This research investigate into the complexity of Asset Liability Management (ALM) in the context of Indian Public Sector Banks (PSBs), with a focus on deposit and lending practices. The selected banks for deposit and lending analysis?SBI, Bank of Baroda (BOB), Canara Bank, Bank of India (BOI), and Punjab National Bank (PNB)?offer a diverse perspective due to variations in operations, size, government influence, risk management, innovation, market trends, and regulatory compliance. The research design outlines the objective, scope, methodology, variables, and significance of the study, spanning the years 2011-12 to 2019-20. The techniques employed include the crucial Loan-to-Deposit Ratio (LDR) analysis, providing a metric to assess liquidity and potential risks. Additionally, correlation analysis explores the relationship between deposit and lending growth. The data analysis section offers a detailed examination of the selected banks' performance, highlighting deposit and lending trends, CAGR, and LDR growth. Notably, the study identifies high correlations between deposits and loans, underscoring the banks' reliance on deposits for lending activities. The overall analysis indicates positive growth in deposits and advances for the chosen period, with State Bank of India and Canara Bank emerging as top performers. However, the slow LDR growth suggests cautious lending strategies, possibly influenced by concerns about asset quality and capital adequacy. The research concludes by acknowledging the challenges faced by Indian public sector banks but highlights their progress and essential role in the nation's economy. The findings have implications for policymakers, banking professionals, and researchers in the financial sector, contributing to a deeper understanding of deposit and lending practices in major public sector banks.

Fintech, Bigtech Credit and Economic Growth: A Bibliometric Review and Meta Analysis

The financial sector plays a vital role to improve economic performance. Development of innovative lending strategies is necessary since debt is the largest form of finance. FinTech and BigTech credit are such innovative ways in the new era of extreme technological advancements that help ensure the economy is inclusive and grows in a sustainable manner. This paper applies a bibliometric review and meta-analysis by utilizing the SCOPUS database to explore the academic research that has been conducted on FinTech/BigTech credit and economic growth. The VOSviewer software was utilized to construct and visualize the bibliometric networks from the extracted data. Our findings show a massive increase in documents published on this topic between 2019 and 2022. Bank concentration, bank minimum capital requirements, market inefficiencies, financial inclusion and regulation on technological innovation were identified as key factors to influence FinTech/BigTech credit adoption. The significance of the study is that we identify the research gaps from previous studies and demonstrate the importance of establishing the nexus between FinTech/BigTech credit and economic growth.

A New Credit and Loan Lending Strategy and Credit in Banking Systems: An Evolutionary Game Theory Approach

In this paper, authors offer one novel mathematical model of credit lending to customers based on evolutionary game theory, and the model presents an efficient and realistic approach. The purpose of the article is to examine the evolutionary game between banks and customers for granting facilities and credit. Authors assumed that customers are divided into two types. The first type of customers includes individuals or small and medium enterprises (SME), applying for microloans from the bank. The second type of customers includes corporate banking or large enterprises, applying for large loans from the bank. The relationship between the bank and the customers is a double-sided problem. Banks and customers may trust each other or want to behave opportunistically. The results show that the game has two equilibriums, and the optimal equilibrium, which is the best-case scenario, occurs when customers and bank players tending to keep “honest” and to “credit,” respectively. Authors used the evolutionary stable strategy to express the parameters that affect these interactions, and by adjusting some of these parameters, authors move the equilibrium towards the optimal solution of the game. Also, by adjusting these parameters, banks can gain more profitability.