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1
Jericevic, Sandra Lynne. "Loan contracting and the credit cycle /." Connect to thesis, 2002. http://eprints.unimelb.edu.au/archive/00000737.
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Aguilera, Nelson A. "Credit rationing and loan default in formal rural credit markets." Connect to resource, 1990. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1232115721.
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Shan, Chenyu, and 陜晨煜. "Credit default swaps (CDS) and loan financing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B5089965X.
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As evidenced by its market size, credit default swaps (CDSs) has been the cornerstone product of the credit derivatives market. The central question that I attempt to answer in this thesis is: why and how does the introduction of CDS market affect bank loan financing? Theoretical works predict some potential effects from CDS market, but empirical evidence is still rare.
This dissertation empirically examines the effects of CDS trading on bank loan financing. In chapter one, I find that banks increase average loan amount and charge higher loan spread after the onset of CDS trading on the borrower’s debt. Also, credit quality of the borrower deteriorates for those with active CDS trading. These findings suggest that banks tend to take on more credit risk by issuing larger loans and by lending to riskier firms that could not obtain bank loan in the absence of CDS. The risk-taking by banks ultimately transmitted to higher bank-level risk profile.
The second chapter is the first empirical study of CDS’ role in determining loan syndicate structure. I find larger lead bank share when CDS is in place. Moreover, participation of credit derivatives trading by lead banks is much larger than by the participants, suggesting that lead banks have better chance to use CDS to their own advantage. Further analysis shows that lead banks retain an even larger share when it is more experienced dealing with the borrower and when information asymmetry between the lender and the borrower is less severe. Different from conventional wisdom about moral hazard in syndicated lending, our findings suggest that the lead bank likely takes on more credit risk voluntarily due to its increased financing capacity.
The third chapter focuses on the effects of CDS on debt contracting. Given that current evidence does not show CDS reduces average cost of debt, we conjecture that the diversification benefit is reflected by relaxation of restrictions imposed on borrowers. Consistent with our hypothesis, we find the marginal effect from CDS trading on covenant strictness measure is 16.8% on average. One standard deviation increase in the number of outstanding CDS contracts loosens net worth covenants by approximately 8.9%. Using various endogeneity controls, we are able to show the loosening of covenants is due to the reduced level of debtholder-shareholder conflict. Furthermore, the loosening effect is stronger when the expected renegotiation cost is larger, consistent with the view that CDS mitigates contracting friction and improves contracting efficiency.
Overall, this dissertation attempts to provide first empirical evidence on how CDS affects bank loan financing. We focus the analysis on loan issuance, syndicate structure and contracting. The findings suggest that banks lend to riskier borrowers in the presence of CDS. On a positive note, banks tend to impose less restrictive covenants on its borrower, which may mitigate frictions in lending market in terms of ex ante bargaining and ex post renegotiation cost.<br>published_or_final_version<br>Economics and Finance<br>Doctoral<br>Doctor of Philosophy
4
Martinez, John Brett. "Credit card credit scoring and risk based lending at XYZ Credit Union." CSUSB ScholarWorks, 2000. https://scholarworks.lib.csusb.edu/etd-project/1752.
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Untalan, Teodoro S. "Borrower Behavior and Loan Repayment in Group Credit /." The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487933245536146.
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Papin, Timothée. "Pricing of Corporate Loan : Credit Risk and Liquidity cost." Phd thesis, Université Paris Dauphine - Paris IX, 2013. http://tel.archives-ouvertes.fr/tel-00937278.
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This PhD thesis investigates the pricing of a corporate loan according to the credit risk, the liquidity cost and the embedded prepayment option. A loan contract issued by a bank for its corporate clients is a financial agreement that often comes with more flexibility than a retail loan contract. These options are designed to meet clients' expectations and can include e.g., a prepayment option (which entitles the client, if he desires so, to pay all or a fraction of its loan earlier than the maturity). The prepayment is the main option and it will be study in this thesis. In order to decide whether the exercise of the option is worthwhile the borrower compares the remaining payments with the outstanding amount of the loan. If the remaining payments exceed the nominal value then it is optimal for the borrower to refinance his debt at a lower rate. For a bank, the prepayment option is essentially a reinvestment risk, i.e. the risk that the borrower decides to repay earlier his/her loan and that the bank cannot reinvest his/her excess of cash in a new loan with same characteristics.The valuation problem of the prepayment option can be modelled as an embedded compound American option on a risky debt owned by the borrower. We choose in this thesis to price a loan and its prepayment option by resolving the associated PDE instead of binomial trees (time-consuming) or Monte Carlo techniques (slow to converge).
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Leow, Mindy. "Credit risk models for mortgage loan loss given default." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/170515/.
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Arguably, the credit risk models reported in the literature for the retail lending sector have so far been less developed than those for the corporate sector, mainly due to the lack of publicly available data. Having been given access to a dataset on defaulted mortgages kindly provided by a major UK bank, this work first investigates the Loss Given Default (LGD) of mortgage loans with the development of two separate component models, the Probability of Repossession (given default) Model and the Haircut (given repossession) Model. They are then combined into an expected loss percentage. Performance-wise, this two-stage LGD model is shown to do better than a single-stage LGD model (which directly models LGD from loan and collateral characteristics), as it achieves a better Rsquare value, and it more accurately matches the distribution of observed LGD. We next investigate the possibility of including macroeconomic variables into either or both component models to improve LGD prediction. Indicators relating to net lending, gross domestic product, national default rates and interest rates are considered and the interest rate is found to be most beneficial to both component models. Finally, we develop a competing risk survival analysis model to predict the time taken for a defaulted mortgage loan to reach some outcome (i.e. repossession or non-repossession). This allows for a more accurate prediction of (discounted) loss as these periods could vary from months to years depending on the health of the economy. Besides loan- or collateral-related characteristics, we incorporate a time-dependent macroeconomic variable based on the house price index (HPI) to investigate its impact on repossession risk. We find that observations of different loan-to-value ratios at default and different security type are affected differently by the economy. This model is then used for stress test purposes by applying a Monte Carlo simulation, and by varying the HPI forecast, to get different loss distributions for different economic outlooks.
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Karakozis, Pantelis. "Valuation and optimal allocation of loan guarantees." Thesis, Imperial College London, 1997. http://hdl.handle.net/10044/1/8061.
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Han, Dahye. "Effect of Abnormal Loan Growth on U.S. Credit Union Performance." Thesis, North Dakota State University, 2016. https://hdl.handle.net/10365/28147.
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This study examined the relationship between abnormally rapid loan growth and its impacts on U.S. credit union performance during 2007 ? 2013. Three hypotheses were developed to test whether and how abnormal loan growth affects default risk, profitability, and solvency in credit unions. This study found that 1) rapidly loaning credit unions had larger average loan loss, smaller average profitability and solvency than normally loaning credit unions; 2) market concentration exhibited a negative and significant impact on default risk, profitability, and solvency; and 3) A size of credit union also exhibited a negative and significant impact on profitability and solvency. These results suggest that supervisors and boards of directors of credit unions should consider rapid loan growth as an early warning sign of risk.
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Ferreros, Esguerra Emmanuel. "Credit tying as a collateral substitute in informal loan contracts /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487841548272612.
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Shariff, Mohd Noor Mohd. "An evaluation of government-backed loan scheme in Malaysia." Thesis, Loughborough University, 2000. https://dspace.lboro.ac.uk/2134/7183.
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SMEs are considered to be an engine for growth in both developed and developing countries, by generating employment opportunities, strengthening industrial linkages, securing home markets and earning valuable export revenue. Government-backed loan schemes play a major role in many countries, by enabling small and medium-sized enterprises (SMEs) to access credit facilities. The Credit Guarantee Corporation in Malaysia has been charged with this key role in assisting SMEs, and its main financing instrument is the New Principal Guarantee Scheme (NPGS). The overall aim of this thesis is to examine the extent to which the NPGS is appropriate to the financing needs of Malaysian SMEs. The primary objective is to identify the factors that determine the utilisation of the NPGS; utilisation depends upon a number of demand and supply factors, as well as the characteristics of firms and owner-managers (OMs). An important secondary objective is to investigate the effectiveness of the NPGS, by exploring the generation of finance and economic additionality, as well as the net cost of the Scheme to the Treasury. After a literature review, and the development of theoretical frameworks, a number of hypotheses are put forward. The methodological approach combines a questionnaire survey with case studies based on interviews with borrowers and financiers, and interviews with key informants. The questionnaire is principally concerned with the factors that affect the utilisation of the NPGS, whereas the case studies and interviews focus on the three elements of effectiveness. The questionnaire data are derived from a sample of firms from the CGC's database. The sample includes firms involved in a variety of activities, from the manufacture of high-technology goods to the processing of resource-based products. Firms were randomly selected to adequately represent racial composition, legal structure and loan size within the CGC's portfolio. The questionnaire data were supplemented by 15 in-depth case studies. Two major findings emerge from this study. First, a number of independent variables did have a significant relationship on the utilisation of the NPGS: the amount of security or collateral; limited company status; manufacturing sector; size of firm; use of external advisers for fund raising; and the existence of written business plans. However, the majority of the hypotheses relating to the characteristics of OMs were rejected; the researcher offers some explanations for this apparent anomaly. Second, the case studies demonstrate that NPGS has achieved finance additionality comparable with achieved in guarantee schemes elsewhere, as well as a significant degree of economic additionality. The net cost of the Scheme was difficult to determine with any degree of precision. On the basis of the research findings, the researcher is able to put forward a series of recommendations to improve the operations of the CGC.
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Osborn, Matthew Gordon. "Essays on Credit Markets and Corporate Finance." Thesis, Boston College, 2015. http://hdl.handle.net/2345/bc-ir:104368.
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Thesis advisor: Philip Strahan<br>In my first essay, I study how the rise of non-bank loan investment from CLOs, mutual funds, and hedge funds influenced contracting relationships between firms and their senior lenders. Contrary to common perception that non-bank investors diluted the incentive for banks to monitor firms, I find evidence that bank underwriters embraced tighter contracts to mitigate agency and holdout problems associated with less-informed and dispersed non-bank investors. While recent studies show that non-bank loan investors lowered the cost and expanded the availability of capital ex ante, I conclude that tighter contracts also assigned stronger control rights to lenders and imposed higher renegotiation costs to firms ex post. In my second essay, we examine the drivers of M&A activity in bankruptcy. M&A in bankruptcy is counter-cyclical, and is more likely when the costs of financing a reorganization are greater than financing costs to a potential acquirer. Consistent with a senior creditor liquidation bias, the greater use of secured debt leads to more sales in bankruptcy - but, this result holds only for sales that preserve going concern value. We also show that overall creditor recovery rates are higher, and unsecured creditor recoveries and post-bankruptcy survival rates are not different, when bankrupt firms sell businesses as going concerns. Finally, in my third essay, we examine whether corporate credit rating analysts are rewarded based on ratings accuracy or bias. Overall, accurate analysts are more likely to be promoted. However, analysts who disproportionately downgrade firms compared to the corresponding S&P rating are less likely to be promoted despite being more accurate than analysts who disproportionately upgrade firms. Further, analysts whose rating decisions lead to significantly negative announcement returns are also less likely to be promoted. We conclude that Moody's rewards accurate analysts but punishes analysts for negative bias<br>Thesis (PhD) — Boston College, 2015<br>Submitted to: Boston College. Carroll School of Management<br>Discipline: Finance
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Bramma, Keith Michael. "AN EVALUATION OF BANK CREDIT POLICIES FOR FARM LOAN PORTFOLIOS USING THE SIMULATION APPROACH." University of Sydney, Department of Agricultural Economics, 1999. http://hdl.handle.net/2123/400.
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The aim of this study is to evaluate the risk-return efficiency of credit policies for managing portfolio credit risk of banking institutions. The focus of the empirical analysis is on the impact of risk pricing and problem loan restructuring on bank risk and returns using a simulation model that represents an operating environment of lenders servicing the Australian farm sector. Insurance theory principles and agency relationships between a borrower and a lender are integrated into the portfolio theory framework. The portfolio theory framework is then couched in terms of the capital budgeting approach to generate a portfolio return distribution function for a particular credit policy regime. Borrowers are segmented by region, industry, loan maturity and credit risk class. Each credit risk class defines risk constraints on which a stochastic simulation model may be developed for credit scoring an average borrower in a portfolio segment. The stochastic simulation method is then used to generate loan security returns for a particular credit policy regime through time with loan return outcomes weighted by the number of borrowers in a segment to give measures of portfolio performance. Stochastic dominance efficiency criteria are used to choose between distributions of NPV of bank returns measured for a number of credit policy alternatives. The findings suggest that banks servicing the Australian farm sector will earn more profit without additional portfolio risk if the maximum limit to which pricing accounts for default risk in loan reviews is positively linked to volatility of gross incomes of farm business borrowers. Importantly, credit-underwriting standards must also be formulated so as to procure farm business borrowers of above average productivity with loans that are fully secured using fixed assets. The results of simulations also suggest that restructuring loans in event of borrower default provide for large benefits compared to a �no restructuring� option.
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Mwembe, Yolam [Verfasser]. "Credit management and loan portfolio performance in Pride Microfinance Ltd / Yolam Mwembe." München : GRIN Verlag, 2019. http://d-nb.info/118803037X/34.
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Banhalmi-Zakar, Zsuzsa. "Understanding the Role of Environment in Project Lending: How Environmental Issues were Addressed in the Lending Practices of Two Commercial Banks." Thesis, Griffith University, 2014. http://hdl.handle.net/10072/365716.
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Since the mid-1990s, banks’ concern about the environment in their lending practices has been interpreted in terms of financial risks and opportunities. The majority of research has concentrated on (a) understanding what these risks are and (b) benchmarking institutions in terms of the measures they employ to control them. These studies painted a picture of a bank sector that perceives the environment primarily as a risk rather than an opportunity and where banks tend to deal with the environment within their existing risk (credit) management practices. While our understanding of the type of risks that the environment can represent in lending is well established, it is still not clear how specific environmental issues, such as the potential negative or positive impacts of proposed projects, transform into financial implications; how they are handled by banks and the extent to which they ultimately influence banks’ decision to finance projects. The purpose of this study was to enhance understanding in this area by investigating how environmental issues were handled in the project lending practices of two commercial banks. A qualitative case-study was conducted in a Hungarian bank in 2006 and an Australian bank in 2007. The Hungarian bank belonged to a Group that has signed the UNEP FI Statement, while the Australian institution has not signed this, or any similar voluntary environmental initiative. Interviews were conducted with staff members who were directly involved in the project lending process. A wide range of internal and external (publicly accessible) documents (such as credit policies, guidelines, forms, reports, case-studies, websites and Annual Reports) that provided insight into the day-to-day practices of the two banks were also examined.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>Griffith School of Environment<br>Science, Environment, Engineering and Technology<br>Full Text
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Lindgren, Jonathan. "Modeling credit risk for an SME loan portfolio: An Error Correction Model approach." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136176.
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Sedan den globala finanskrisen 2008 har flera stora regelverk införts för att säkerställa att banker hanterar risker på sunt sätt. Bland dessa regelverk är Basel II som infört kapitalkrav för kreditrisk som baseras på Sannolikhet för Fallissemang och Förlust Givet Fallissemang. Basel II Advanced Internal-Based Approach ger banker möjligheten att skatta dessa riskmått för enskilda portföljer och göra interna kreditriskvärderingar. I överensstämmelse med Advanced Internal-Based-rating undersöker denna uppsats användningen av en Error Correction Model för modellering av Sannolikhet för Fallissemang. En modell som visat sin styrka inom stresstestning. Vidare implementeras en funktion för Förlust Givet Fallissemang som binder samman Sannolikhet för Fallissemang och Förlust Givet Fallissemang med systematisk risk. Error Correction Modellen modellerar Sannolikhet för Fallissemang av en SME-portfölj från en av de "fyra stora" bankerna i Sverige. Modellen utvärderas och stresstestas med Europeiska Bankmyndighetens stresstestscenario 2016 och analyseras, med lovande resultat.<br>Since the global financial crisis of 2008, several big regulations have been implemented to assure that banks follow sound risk management. Among these are the Basel II Accords that implement capital requirements for credit risk. The core measures of credit risk evaluation are the Probability of Default and Loss Given Default. The Basel II Advanced Internal-Based-Rating Approach allows banks to model these measures for individual portfolios and make their own evaluations. This thesis, in compliance with the Advanced Internal-Based-rating approach, evaluates the use of an Error Correction Model when modeling the Probability of Default. A model proven to be strong in stress testing. Furthermore, a Loss Given Default function is implemented that ties Probability of Default and Loss Given Default to systematic risk. The Error Correction Model is implemented on an SME portfolio from one of the "big four" banks in Sweden. The model is evaluated and stress tested with the European Banking Authority's 2016 stress test scenario and analyzed, with promising results.
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Kim, Juno. "A credit risk model for agricultural loan portfolios under the new Basel Capital Accord." Texas A&M University, 2003. http://hdl.handle.net/1969.1/2276.
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The New Basel Capital Accord (Basel II) provides added emphasis to the
development of portfolio credit risk models. An important regulatory change in Basel II
is the differentiated treatment in measuring capital requirements for the corporate
exposures and retail exposures. Basel II allows agricultural loans to be categorized and
treated as the retail exposures. However, portfolio credit risk model for agricultural loans
is still in their infancy. Most portfolio credit risk models being used have been developed
for corporate exposures, and are not generally applicable to agricultural loan portfolio.
The objective of this study is to develop a credit risk model for agricultural loan
portfolios. The model developed in this study reflects characteristics of the agricultural
sector, loans and borrowers and designed to be consistent with Basel II, including
consideration given to forecasting accuracy and model applicability. This study
conceptualizes a theory of loan default for farm borrowers. A theoretical model is
developed based on the default theory with several assumptions to simplify the model.
An annual default model is specified using FDIC state level data over the 1985 to
2003. Five state models covering Iowa, Illinois, Indiana, Kansas, and Nebraska areestimated as a logistic function. Explanatory variables for the model are a three-year
moving average of net cash income per acre from crops, net cash income per cwt from
livestock, government payments per acre, the unemployment rate, and a trend. Net cash
income generated by state reflects the five major commodities: corn, soybeans, wheat,
fed cattle, and hogs. A simulation model is developed to generate the stochastic default
rates by state over the 2004 to 2007 period, providing the probability of default and the
loan loss distribution in a pro forma context that facilitates proactive decision making.
The model also generates expected loan loss, VaR, and capital requirements.
This study suggests two key conclusions helpful to future credit risk modeling
efforts for agricultural loan portfolios: (1) net cash income is a significant leading
indicator to default, and (2) the credit risk model should be segmented by commodity
and geographical location.
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Meder, Anthony Alan. "SFAS 115, Bank Balance Sheet Liquidity and Loan Growth." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1312309973.
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Maksimenko, Tatiana. "Lending relationships and liquidity insurance value of bank credit lines| Evidence from loan spreads." Thesis, City University of New York, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3601933.
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<p>Bank lending processes and lending relationships involve two aspects, the provision of liquidity via lines of credit and the production of information via monitoring. To access the existing credit line, a borrower must be in compliance with financial covenants. When violations occur, access becomes conditional upon the bank’s willingness to accommodate the customer. The bank values its reputation as an accommodating lender and views a decision regarding credit line access restrictions as a trade-off between reputational and financial capital. Since imposing restrictions on a more loyal borrower causes greater reputational damage, a bank’s “willingness” to accommodate increases in the strength of the relationship with its borrower. This is the first channel through which relationships have effect. To the extent that lending also involves monitoring, relationships allow a bank to build an exploitable information advantage. This is the second channel. Most credit lines are monitored, making it difficult to isolate the effects of these two channels. I identify commercial paper backup lines of credit as loans that provide liquidity, but do not involve information production and use them to construct two measures of relationship strength that capture the extent of bank’s willingness to provide liquidity (<i>T-intensity </i>) and the bank’s information advantage (<i>I-intensity </i>). To make sharper inferences concerning the effect of willingness, I control for a bank’s reliance on core deposits as a measure of “ability” to provide liquidity. I find that loan spreads decrease in <i>T-intensity </i> for firms without public equity. Thus, for such firms, credit lines have liquidity insurance value and it increases with relationship strength. I also find that loan spreads increase in <i>I-intensity</i> for all firms, suggesting that banks are successful at exploiting their information advantage (i.e. “holding up” borrowers). My findings imply that for relatively opaque borrowers, relationships have value even in the absence of private information production. </p>
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Sustersic, Jennifer Lynn. "Do traded credit default swaps impact lenders' monitoring activities? Evidence from private loan agreements." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1339512002.
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Ahiabor, Frederick S. "Determinants of project finance loan terms." Thesis, Loughborough University, 2018. https://dspace.lboro.ac.uk/2134/36313.
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Project finance has become a vital financing vehicle for undertaking capital-intensive and infrastructure investments. In 2017 alone, the value of deals signed using project finance was estimated at approximately $229 billion. Despite its increasing importance, little is known regarding the impact of project-level, and country characteristics on the loan terms. This thesis proceeds in examining these determinants along three empirical essays. The first essay (Chapter 3) focuses on how domestic lead arrangers certification (in emerging markets) impact the pricing of project finance loans. Using a sample 1270 project finance loan tranches signed between 1998 and 2011, and worth over $300 billion, the chapter posits that domestic lead arrangers certification reduce search and information cost, which in turn, reduces the financing cost. The results, after controlling for endogeneity of certification decision, indicate a reduction of 47 basis points in the spread offered on PF loans. The magnitude of this reduction differs across industries, geographic region, and income classification of the project countries. The second essay (Chapter 4) examines the relationship between PF contractual structures and loan outcomes, using a sample of 5872 project finance loan tranches signed between 1998 and 2013, and worth approximately $1.2 trillion. The chapter hypothesises that (i) non financial contracts (NFCs) (that is, contracts used to manage the various project functions), reduces overall project risk, (ii) the involvement of project sponsors as key counterparties to the non-financial contracts is an additional signal of project s potential worth, and (iii) the effects observed in (i and ii) are stronger, if sponsor counterparties have verifiable credit ratings. After matching loan tranches with NFCs to those without, the results indicate that the use of NFCs reduce both the loan spreads and leverage ratios. This impact is higher if the sponsor counterparties are credit-rated. The results are also stronger for developing countries. The third essay examines the impact of country-level institutions on project finance loan spread and leverage ratio, using a sample of 3,362 loan tranches signed between the year 1998 - 2012. The chapter investigates whether political and legal institutions are substitutes (or complements), that is, if improvement in one absorbs the weakness of the other, and vice versa. Further, the essay examines if project finance network of contracts substitutes for these institutions. The results indicate that political and legal institutions are substitutes. Specifically, improvements in political institutions lead to a reduction in both the loan spread and leverage ratio for countries with weak legal and governance institutions. The chapter also finds that where NFCs are included in PF, the impact of political institutions on loan spread reduces. On the other hand, the impact of political institutions on leverage ratio is higher when NFCs are used. The findings from the three research chapters provide interesting insights on how lenders and sponsors create value through contract design.
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Bedane, Bizuayehu Getachew. "Rural Credit Markets in Ethiopia: Coexistence, Persistence, and Demand." OpenSIUC, 2016. https://opensiuc.lib.siu.edu/dissertations/1176.
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This study examines empirically the transition, persistence, and loan demand in the rural credit market using panel data. The data was collected for seven rounds (1994-2009) from 15 villages in Ethiopia. The sample size is about 1500 households for each round. . Chapter one examines the determinants of simultaneous borrowing and lending. We also investigate why some households in rural Ethiopia simultaneously borrow and lend. Who are these households? Panel logit model is estimated for the sub-sample of borrowers and lenders. The result suggests that households that simultaneously borrows and lends are relatively better-off households. The probability of being a simultaneous borrower and lender is higher for households with strong village level networks. Moreover, households that are affected by common shock are more likely to be a simultaneous borrower and lender. Chapter two examines the dynamics and persistence in the rural credit markets in Ethiopia. It also examines the determinants of dynamics and persistence in borrowing and lending. Duration, dynamic probit, and dynamic multinomial logit models are estimated. We control for unobserved heterogeneity and initial condition. The result reveals the existence of positive duration dependence in both only borrowing households and simultaneously lending and borrowing households. The longer the duration as a borrower, the more likely to exit from borrowing. The longer the duration out of borrowing, the more likely to re-enter to borrowing. Off-farm work, fertilizer use, household size, and storing crop are an important determinant of the probability of exit from borrowing. There is also true state dependence in lending, borrowing, and simultaneously borrowing and lending households. This means the probability of being a borrower in the current period is highly correlated with being in the same state in the previous period. Poverty status, flood, labor sharing, membership in mutual help association, total oxen owned, storing crop, off-farm activities, and fertilizer use are an important determinant of the probability of being a borrower. Chapter three examines the determinants of demand for credit in rural Ethiopia. Bias due to data truncation, variation of the interest rate, and using loan data from a single source are the challenges in estimating demand for credit in the context of rural credit market. This study captures data truncation by estimating a panel Tobit model. The variation in the interest rate is also controlled by using village dummies and their interaction with the source of the loan. Total loan obtained from multiple sources is used as a dependent variable. The result reveals that initial endowment proxied by the value of assets, household size, the age of the head of the households, transitory income, and real per capita consumption are the most important determinants of demand for credit.
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Chuang, Wen-Hsin, and 莊雯伈. "Study on Automatic Small Amount Credit Loan -A Case Study of S Bank." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/93bh82.
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碩士<br>淡江大學<br>財務金融學系碩士在職專班<br>106<br>In the process of banks moving to Bank 3.0, the characteristics of science and technology are actually the key. In the era of Bank2.0, the passive behavior of allowing customers to search for their trading status and passively conduct trading activities is a non-synchronized behavior. However, Bank3.0 can prompt customers to control their own trading situation, and even through Big Data''s calculations, they can actively provide customer-specific trading products. S Bank launched an online application service for microfinance. People only need to input data at home and simulate lending sums and interest through big data calculations. Direct online loans will save the troublesome loan process, but current banks can only do online. Application, can not be automated online loan, still have to use artificial loans after lending, so the main study of this article is to establish a self-nuclear loan system, contiguous starting the overall operation of online loans, and at the same time can further explore the automatic loan Differences from artificial nuclear loans; it is hoped that through the results of this study, it will be useful for practical applications and allow banks to respond to changes in digital finance.
This study collected data from January 3, 2017 to June 30, 2017, a total of 15,480 data were used, and after pairing the variables discussed, a logit regression model and other measurement methods were used to establish an empirical model. Data and model analysis and other methods are used to verify and integrate, use algorithms to calculate, find the closest approach to artificial nuclear loans, establish an automatic credit mechanism, connect the whole process of online loans, and theefficiency of the automatic audit mechanism is better than the traditional manual audit. Improve the operating mode of S Bank, streamline the manual operation time, eliminate the operating costs, labor costs, and explore the key factors of overdue loans, and include gender, education, income, and service institutions as important factors affecting the overdue loans.
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Chen, Tsung-Hao, and 陳宗豪. "The credit risk research of consumer credit loan." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/72696047950490555281.
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碩士<br>國立中山大學<br>人力資源管理研究所<br>88<br>Abstract
According to a survey conducted by Rock (1984), the major factors of influenced credit risk are (1) the relationship with other creditor, (2) income, (3) loan-income ration, (4) profession, (5) immovable property, (6) check & deposit account. And, the sure way to score with lenders are (1) rules of thumb & subjective judgment, (2) credit rating system, (3) credit scoring system, and (4) expert system.
The purpose of the present study is to examine the relationships between sex, age, income, profession, assets, the purpose of loan, employment information, credit references, credit limit, total installment loan account by the consumer, total number of inquiries and the consumer’s payment records.
The results of this search indicate that:
1. The previous stereo type thinking of banking industry always treat the military officials as wall as police officials are risky groups to consumer credit loan. However, this study found the contrary result. The payment over due rate is comparatively lower than that of other customer groups. The conclusion is that military officials and police officials are potentially good customers to banking system in terms of profit margin against risk.
2. From the credit scoring system of banking industry. That the customers are between 35 to 50s should be better than those age between 20 to 30s. However, this study demonstrates the other direction that customers with age below 35years old always better than those who over 35years old to the banking creditability actual performance.
3. The banking industry assume the married people will be a better group compared with non-married group on the money collect of the loan they made. However this study proves that creditability performance in sequence is (i) age below 35 and singer is the best. (ii) those married is the second while.(iii)age over 35 and non- married group is the worst one.
4. Most of people think those who have consumer credit loan from bank and would not want their family to be aware of their personal loan may have higher chance of payment over due. However, the statistics study from bank branch A indicates that this kind of customers (don’t want family member know about loan) are the best group on payment over due (only 5.5%). While those who agree to let family member aware are the second (7.5%), and others with no comment are the worst.
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Ho, Chun-Yi, and 何俊億. "Constructing Credit Loan Forecasting Model By Using Credit Card Database." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/02785724926430168264.
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碩士<br>國立臺灣大學<br>國際企業學研究所<br>101<br>The main purpose of this study is to construct credit loan forecasting model based on the database of customer transaction history, it could help banks to execute timely marketing approach to those who are highly demanding of credit loan. Through interaction with customers, we can find out the target customers to launch marketing mix to improve profit margins. And the types of data contain customer demographic variables and credit card transaction records. We analyze customer value through two indices by past transactions and assume different customer transaction behavioral variables to fit the model to see which variable does really have a significant influence of credit loan applying.
Therefore, the purpose of this study is to identify the potential reasons why customer would apply credit loan. In the choice of constructing probability forecasting model, we use logistic and probit model and thus compare the credit loan hit rate of both.
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Chang, Su-Yen, and 張素燕. "A Study on the Credit Evaluation Model of Consumer Credit Loan." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/88588023783387227913.
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碩士<br>國立中興大學<br>應用經濟學系所<br>97<br>This study discusses the effectiveness and improvement of the current credit score table for domestic commercial banks on credit-granting loan with the performance of credit evaluation. Logistic Regression Model is adopted to analyze if the risk of breaching contact happened.
After considering other variables from current tables, three stages of models, the one with current evaluation criteria, the one with arranged criteria, and the one with best performance, are performed and compared. 422 borrowers for short-term consumer loan data from some commercial bank during October, 2005 to September, 2007 are considered. Major empirical results are as follows：
1.According to this study, the current credit score table or the evaluation base on accuracy of short-term consumer loan can be improved with the information on the given table.
2.By retaining five important variables on individual small-amount loans credit score table and introducing other five items, the accuracy of credit evaluation prediction model increases form 61.8％ to 70.6％. The accuracy of prediction is 71.1％ for normal cases and 70.1％ for bad-loan cases, this implies that the prediction performance can be improved by variable implementing and rearranging.
3.Credit evaluation prediction model includes seven significant variables which are consistent with the expected signs. With the 5-P criteria on crediting, there are five items in people dimension, included 「gender」,「age」,「education」,「numbers of bank inquiry」and 「Loan payment」.
4.Considering the practical situation on loan evaluation, this study suggests that the background of debtor, payment consideration and obligation protection should take into evaluation on credit prediction. Therefore, without intruding extra variables, this study suggests that the crediting performance for commercial bank can be improved by including the following factors：「gender」, 「age」, 「education」, 「number of bank inquiry」, 「loan payment」, 「main debt」, 「application rate on interest」,「working years」,「annual income」and「sponsor or vice collateral condition」.
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張維仁. "The study of credit evaluation form model to consumer credit loan." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/62151188414237061833.
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Hsu, Yu-Fang, and 許瑜芳. "Credit Risk Measurement of Bank Loan Portfolios." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/81746323897966080911.
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碩士<br>輔仁大學<br>金融研究所<br>95<br>In order to adapt to the fast change of the financial environment, the Financial Supervisory Commission, Executive Yuan urges local banks to improve their risk management ability. However, most local banks are still in the initial stage of getting familiarized with credit risk models. Therefore, local banks are advised to take in the experience from the advanced credit risk models already developed by internationally acclaimed financial institutions in order to develop credit risk models suitable to their operations.
The dissertation examines small and medium-sized enterprises obligors in a certain local bank. It is attempted to calculate the default rate of every obligor by Logistic regression model and subjectively group the obligors into five ratings. Then, the mean default rate and default rate volatility of each rating are estimated before referring to the historical value of the recovery rate of the sample bank. Furthermore, the expected and unexpected losses of the loan portfolio are calculated after establishing the loss distribution according to the CreditRisk+ model developed by Credit Suisse First Boston. Finally, the credit risk of the loan portfolio is managed by using the risk contributions. The empirical results are as follows:
(1)The article used Logit model to estimate the means and standard deviations of the default rate of each credit rating. When the credit rating is 1, the mean of the default rate is 0.31% and its standard deviation is 0.0034; when the credit rating is 2, the mean of the default rate is 4.33% and its standard deviation is 0.0258; when the credit rating is 3, the mean of default rate is 19.20% and its standard deviation is 0.0528; when the credit rating is 4, the mean of default rate is 42.64 and its standard deviation is 0.0929; when the credit rating is 5, the mean of default rate is 89.66% and its standard deviation is 0.1396. As a result, it can be concluded that the worse the credit rating of a company, the bigger the default risk as well as the volatility.
(2)The portfolio loss distribution is established according to the CreditRisk+ model and the loss percentiles are procured to set up a loss control mechanism. In order to handle the expected loss of the portfolio which might happen in the future, an annual credit provision for 2,040,388 thousand dollars (7.08% of the loan amount approved) is required; in order to deal with the impact of the unexpected loss we need to raise an extra capital of 4,450,526 thousand dollars (15.44% of the loan amount approved). This is so-called “economic capital.”
(3)When eliminating the obligor with the biggest risk contribution from the portfolio, the expected loss decreased by 4.15%; the 99th percentile level diminished by 16.7%; the economic capital needed is significantly reduced by 18.3%. Lower economic capital requirements reflect lower risk of the new portfolio and wider diversification.
(4)Finally, a sensitivity analysis is conducted by inserting four different input parameters according to the CreditRisk+ model. The outcome shows that the sensitivity of credit exposure is the highest, followed by the default rate volatility. Therefore, potential unnecessary exposure can be avoided and the risk of the loan portfolio can be diversified by introducing rating exposure limits.
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Wu, Mon-Feng, and 吳孟芳. "Positioning and Promotion of Credit Cooperation’ Loan." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/68011104685363597629.
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碩士<br>銘傳大學<br>管理科學研究所碩士在職專班<br>91<br>In April 1990, the government (of the Republic of China) lifted the ban on the establishment of financial institutions. Sixteen banks have been set up to join the severe competition. Since the government’s financial policy has been internationalized and liberalized, local financial institutions, especially credit cooperation, are facing severer competition. To survive, credit cooperation has to put more efforts on financial and personnel management on one hand, and reorganize the company and adjust the marketing strategy on the other hand.
Throughout the interview and data analysis, The conclusions and suggestions of the Study. Credit cooperation should concentrate on their current business instead of vying for news customers. Also, guarantee should not be the only proof of the loan. Debtors’ credit and their source of payment ought to be put into concerned as well. (Abiding by the “5P” loan principles). Those aged between 31 and 50, graduated from senior high schools, might be the main target of credit cooperation’s real estate loan market.
Instead of spending five to seven times the costs and energy to look for a new customer, credit cooperation ought to try its best to keep a good one. No matter how small a credit cooperation is, it may survive as long as it runs current business well.
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HONG, ZHEN-WEI, and 洪振瑋. "Equipment Loan Credit Evaluation：Case of H Company." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9rbqkf.
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碩士<br>開南大學<br>商學院碩士在職專班<br>107<br>Because of the impact of external environmental factors on the equipment financing industry in recent years, the related financing industry has increased significantly, but the proportion of bad debts that cannot be recovered due to financing has also increased. The purpose of this study is to explore equipment loan credit evaluation and analyze different background influences are different from the cognitive differences of credit evaluation projects, in order to assist operators to establish standardized evaluation procedures and reduce bad debts and risks in the financing industry. Based on the purpose of this study, two research questions were derived: What is the credit evaluation project for cognitive equipment financing in this study? And are there different differences in the perceptions of respondents from different background factors?
This study adopts the expert interview method to design the equipment loan credit evaluation questionnaire. The research object is a equipment financing company. The number of population is 290, and the effective questionnaire totals 244. Share. Based on the results of the factor analysis, the respondents considered that the loan credit evaluation for equipment financing included “repayment ability facet”, “operational status and corporate outlook facet”, and “non-financial risk facet”, a total of 24 items. According to the results of t-test and single-factor variance analysis, there were significant differences in the perceptions of the respondents' different evaluations.
Keywords：equipment loan、credit evaluation、factor analysis
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Wang, Mei-Chiuch, and 王梅雀. "A Study of Evaluating Mortgage Loan Credit Risk." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/65fa43.
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碩士<br>國立嘉義大學<br>管理學院碩士在職專班<br>96<br>The main purpose of this study is to find the factors which affect consumers default by mortgage risk scoring model. Consumer mortgage is the primary income of banks, and the quality of it results in the banks’ permanent operation. Recently, due to international economic depression, Taiwanese Banks have experienced the “Credit Storm” under the over-expansion of consumer mortgage. The consequence of this fact is the rapid soar of default debt ratio, which is a great loss of profit. Moreover, this occurrence have created a severe damage in the financial market, and also procured the banks’ reduction on non-assurance loans and the rise on mortgage. Therefore, to control the credit risks has become a demand of great urgency. As consumers’ mortgage increases, accuracy and efficiency of credit approved are required during the process of investigation.
This study regards 324 samples of consumer mortgage in a domestic bank from year 1999 to 2004. By doing actual evaluation and applying the ordinal probit model, the apparent features that affect the risks of consumers default the mortgage under their credit are discussed. These features could help establish future basis for consumers’ credit evaluation model of mortgage. It could also become a reference for future mortgage approved, mortgage limits, and interest rate. As for the selection of samples, they are separated into different layers based on personal economic ability, mortgage approvals, and collateral type. Of these three, the collateral type is least discussed, and yet this is the greatest difference between this study and others. Based on the experimental results, we have discovered the following phenomena:
On demographic variables: Gender and personal income have apparent affections and differences on credibility, and appears to be negative correlation. Under the credit assessment of the bank, the mortgage percentage, approved loan interest rate, and interest compartmentalization are consistent with our predicted results. In the collateral type, the region of the collateral are related to the credibility default in a negative correlation, which agrees with the predictions. This indicates that local collaterals are less likely to default, while collaterals from other regions have a higher probability of default. The dominion, contact information, and address don’t have large affection on the results. The common ways to rate credibility is to adopt the market comparison, rating members can easily handle the market price, currency, the original value, and the future development of the collateral. This study’s results have proven the apparent affection to credibility related to the region of collaterals. From our knowledge, this is the first written research to prove this result. The finding of this result is to hope that bank operators could take the regions of collaterals into consideration and place it as their first priority of consideration, so as to prevent the occurrence of risks.
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Wong, Yi-Chao, and 翁翊超. "Credit Risk of Loan Portfolio and Capital Requirement." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/65000683499042542304.
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碩士<br>逢甲大學<br>財務金融學所<br>97<br>The 2008 global financial disaster are mainly contributed to banks taking too much credit risk and inadequate bank regulations. In many countries, regulators pay more attentions on bank management especially on credit risk. In order to charge sufficient capital associated to the credit risk faced by banks, the Bank for International Settlements stipulates the new Basel Accord in 2002. In the meantime, there are many studies intend to develop models that can measure the bank’s credit risk much accurately. In this study, we extend the work of KulKarni (2008) to measure the credit risk of a bank when it makes loans to the 27 firms which have been rated by the Taiwan Ratings. We estimate the capital requirements for the bank under the standardized approach, fundament internal rating based approach, and advanced internal rating approach suggested by the Basel II. We also estimate the economic capital based on the expected shortfall faced by the bank. Finally, we compare the capital charges estimated under the alternative approaches with the capital charge computed under the standardized.
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Yeh, Cheng-ching, and 葉正青. "Information Asymmetry and Credit Spread of Bank Loan." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/67660662123797199853.
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碩士<br>國立高雄第一科技大學<br>金融所<br>98<br>This study explores the relationship between asymmetric information of corporate and credit spreads of bank loans by using the data of firms listed on the Taiwan stock Exchange. The result shows that the degree of information asymmetry is positively related to credit spread of bank loans. The credit spreads caused by information asymmetry are especially large for the short-term loans. In addition, firms with higher equity risk, lower liquidity ratio, smaller size, and poor credit rating have larger credit spreads of bank loans.
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Sun, Jui-tai, and 孫瑞黛. "Unsecured loan default model：Structure change after credit crunch？." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/58739308509490036044.
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碩士<br>世新大學<br>財務金融學研究所(含碩專班)<br>97<br>The consumer financial markets are rising after the 1997 Asian Financial Crisis, especially the unsecured personal loans grow rapidly due to high user demand. In 1999 Cosmos Bank is the first bank to launch cash card product and make a big boom. The cash card boom attract all the Taiwan banks launch their products and lastly reach the peak in 2003, and finally cause credit crunch (double-card debt storm). After that, due to our government’s strictly financial supervision and the banks’ self-disciplined, credit crunch are temporarily settled down. But how to control the incident, has become our government’s and the banks most important lesson.
Our research study on a Taiwan bank’s unsecured personal loans which loaned two years before and after 2005 credit crunch. We choose 4 most representative samples of small credit and cash card products to explore the impact of customer default risk factors by SPSS statistical software package. 13 covariates include sex (X1), age (X2), education (X3), marital status (X4), home ownership patterns (X5), residence time (X6 ), seniority (X7), the number of dependents (X8), annual income (X9), pieces of credit card (X10), number of recent bank queries (X11), other bank loans (X12), the total number of bank loans (X13) are analyzed for Logistic Regression analysis. From the study analysis result, we find that the 3 common significant covariates of all 4 samples are education (X3), pieces of credit card (X10), number of recent bank queries (X11). We also found that the significant effects of variables of basic customer attributes (X1 ~ X8) are the same. About the cash card sample before credit crunch, all the variables except education (X3) are insignificant, which is different from small credit, but the cash card sample’s trend go in line with the small credit after the credit crunch.
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Su, Yu-Li, and 蘇玉里. "Exploration on credit risk factors of home mortgage loan." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/18781346220226640563.
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碩士<br>國立屏東商業技術學院<br>國際企業所<br>98<br>The study is to evaluate the factors of default in home mortgage credit assessment model. Credit business is the important operation of banks, and interest is the main revenue-source for the bank. Therefore, the quality of credit assets would seriously influence a bank’s sustaining operation. As the depression of global financial business and the impact of sub-prime mortgage, the conditions of home mortgage loan and its credit assessment model were knocked. So it is imperative and emergent to do risk management well.
The study would take the customers of certain domestic bank’s home mortgage loan as sample data for authentication, and find out the crucial factors of late payment among the customers. The author used some models to explore the main characteristic reasons that influence the risk of mortgage credit default and took it as the evaluative base for building a better method of risk management and the reference for bankers to accept or reject home mortgage loan, as well as deciding how large the credit line and the interest would be in the future.
The research would base on the main concepts of customer’s 5P: people (who get the credit), purpose (of the capital), payment (resource), protection (of the claims) and prospects (of the credit), to explore the relationships between those 5P factors and the probability of late payment, so as to produce the probability model of late payment and default in home mortgage loan. The study found out the characteristic factors that influence credit risk of home mortgage loan while applied simple Regression Analysis Model to evaluate 8 variables. The author found there were 5 variables (gender, vocation, title, purpose of capital and lending rate) that presented significant influence. Among them, the gender, purpose of the capital and lending rate showed positive correlation with the possibility of late payment and default, while the relationships between vocation, title and the possibility of late payment, default were negative. As using logistic Regression Analysis Model, the characteristic factors that influence credit risk of home mortgage loan were found. It was also found that personal revenue and loan ratio showed significant influence. While the later variable presented positive relationship with the possibility of late payment and default, the former showed negative relationship. It is expected that the results of the empirical research would provide bankers reference for setting up credit policy.
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Liang, Chih-yung, and 梁智勇. "On Bank's credit quality : Evidence from post-loan performance." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/40504528589139422772.
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碩士<br>世新大學<br>財務金融學研究所(含碩專班)<br>97<br>The small and medium enterprises often play the role in Taiwanese society as stabilizing people's livelihood and stability in the job market, and they are often given credits for the overall economic growth. In particular their uniqueness in operational flexibility and division of labor is one of the competitive advantages in Taiwan's industial development. However, due to SME are generally confined by their own limitation in operational scale, they are less likely to implement a diversification of funding similar to large-scale corporations, therefore bank financing becomes a relatively important source of funding for them.
Nonetheless, due to our domestic small and medium enterprises are strongly dominated by “rule of huamen,” in addition to an incomplete accounting system resulting in a low transparency and the financial reporting information unable to fully reveal the actual performance of the enterprisese, therefore under the financial asymmetric information between the bank and the loaning enterprises, the factors of non-financial considerations further increase in significance.
The study aims at the case of the credit customers of small and medium enterprises from a domestical commercial bank between May 2005 and May 2006, and with emphasis on the following four aspects: 1. legal representative attributes; 2. business between legal representative and the bank; 3. enterprise attributes; 4. business tranasaction between the enterprise and the bank. A total of 16 factors for bank credit consideration are used as explanatory variables to primarily conduct descriptive statistics in order to understand the basic characteristics of information, followed by two stastistical analysis of variance to comprehend the relevant factors influencing credit quality. Finally, Logistic Regression model is applied to explore the possible factors affecting credit quality from the non-financial factors taken into account the SME loaning by the bank.
The results of statistics show that the "number of bank inquiries from the legal representative in recent 3 months," "spouse of legal representative," "number of cashcards used by legal representative,"number of credit cards with full payment by legal representative in recent 3 month," and number of bank inquiries from the enterprise in recent 3 months" have signifinicant correlation with credit quality from the bank.
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Lin, Che-hui, and 林哲輝. "The Case Study of the House Loan Credit Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/37137500949528699707.
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碩士<br>國立高雄第一科技大學<br>財務管理所<br>95<br>Many new banks were established in Taiwan from 1991. The finance industry entered the Warring States time, the bank service although gradually hastens the diversification, the house loans still is the origin of the bank mainly earning profits for the long term. Not only without the various blue sea strategy innovation between those banks to accept a challenge,but also to cut prices by the red sea strategy to compete with the opponents , the malignant competition result reduces the advantage difference between the deposit and the grant loans gradually. Besides,it also creates the bad quality of credit assessment day by day. Then following with it is the increase of grant loans behind time.When the bank pursues profit,it must take into consideration to control the credit assessment risk. To accept too many cases could not make a high profit. It must coordinate the lower overdue grant loans rate simultaneously. Then we could enjoy the high profit by the many accepting cases. For reducing the overdue grant loan and controlling the quality of house loan credit assessment,at the beginning of checking credit,the bank should establish one of the best and the most effective credit assessment model.
This research takes two branch offices of one bank in the south Taiwan as the research object. I extract 300 cases from the normal and 30 cases from the overdue grant loans as examples between 2005-2006 period. There are total 330 cases, 16 variables and make the regression analysis by the LR model.To establish the most effective pattern of the house loans credit assessment.
The goal of this research is for discussing the risk factors which will affect the house loans credit assessment,the LR model II proved there is quite obvious difference of the only one variable that is the education level. It is 100 correct percentage to forcast whether it will become the normal case,and 0% to become the overdue case in the future. The average reach to 90.9% for the whole forecast. This credit assessment model still can provide bank to teach letter to examine in the most short time, the personnel judges whether loan allows to refute or not.
Bank should do lending rate to adopt a difference list price towards accepting. Have to achieve a balance point between the risk and the guerdon. Avoid causing because of the false list price an operation crisis, and develop the problem of many societies and economy.
Keyword：house loan, overdue grant loan, credit assessment , logistic regression (LR).
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Chun-Hsien, Chou, and 周俊賢. "An Analysis in Evaluating the Credit of House Loan." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/03311763307135164785.
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碩士<br>國立高雄第一科技大學<br>財務管理所<br>91<br>In Taiwan, the economy has been slumping from the peak in September 2000 up to now. The ratio of non-performance loans (NPL) among the interbanks has been increasing up to a high position. Total amount of NPL was seen reaching at the historical climax. An increment of NPL was mainly caused by the default on the house loans. The financial institutions in Taiwan are usually accustomed to intend of the value of gage. To decide the credit line of the house loan, it was found, however, those institutions pay little consideration in the future repayment ability of the borrowers. Of course, it is understood that the NPL would be generally increased if the economic fluctuations turn out to be a recession.
Drawing on the past literatures for the house mortgage loans, it is found that there are a lot of variables, and some of them were not suitable in material for the bank’s demand on the house loan operation. This study is requested to take all samples from the actual cases during the research period. Neither random sampling nor questionnaire was used. At the first stage, it was taking only two variables, the occupation of the borrower couples and the couple’s repayment ability to the income ratio. The result was found as follows, the total accuracy of prediction through Logistic Regression is 96.90%, including the accuracy of prediction for the normal loans is 98.40% and for the bad loans is 92.20%. Then, it were added furthermore two more factors into the model, i.e. loan-to-value ratio and the couple’s disposal of the net income. The research result showed that the total accuracy of prediction rose up to 97.60%, i.e. the accuracy of prediction for the normal loans is 99.10% and for bad loans 93.20%. In accordance with the pool of this model, the house loan credit scoring form was established. From the result of crossing analysis, it is suggested that the banks may agree to accept the house loan if the borrower’s credit scoring is over 60% and further it would be almost no risk to accept such house loan if the borrower’s credit scoring is over 70%.
This study wishes to establish an analysis model in evaluating the credit of house loans through some simple, demanded variables. It is further to wish to correct a bias on the research in house loans and is hoping one of the models could be available by banks in order to minimize the risk of loans and/or to increase the quality of the assets in house loans.
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Wong, Chia-Chun, and 翁家君. "CREDIT SCORING MODEL ON MORTGAGE LOAN AND RISK MANAGEMENT." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/31845886519870142460.
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碩士<br>銘傳大學<br>國際企業學系碩士在職專班<br>98<br>Among consumer lending of commercial banks, mortgage has always been a major business. As banks expand their mortgage credit businesses, they should have in place a comprehensive, regularised and systematic mortgage risk evaluation model and management system to reflect the actual credit risk of clients, thus effectively reducing the overdue ratio. The study attempts to build a warning model based on logistic regression analysis to provide a regional predication model of mortgage default in northern Taiwan to which financial institutions can refer. The findings of the research are as follows:
I. 17 representative, conventional feature variables were selected, and logistic regression analysis discovered 7 to be significant variables that affect credit quality with a certain predictable accuracy; they are guarantee, annual income, location of guaranteed item, item type, owner of guaranteed item, number of banks with business transactions and mortgage rate. The results of the research can assist the examination and approval process of mortgage and be used as future reference.
II. Conventional credit evaluation model has the prediction accuracy of 77.5%, which can be raised up to 89.3% when the four risk variables are included in the model: whether or not it is an investor and bulk mortgage, the surface area of the house and debt ratio. This shows the significant predicative power of these variables, among them the variable of whether or not it is an investor has the greatest predictive power with the highest odds ratio at 24.493, which has significantly higher correlation with credit quality than other variables. It is recommended that banks include the four risk variables in their credit-rating systems in the future.
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Yang, Cheng-Chieh, and 楊正傑. "A Study on Financial institution Small Loan Credit insurance." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/96027869310291371716.
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碩士<br>淡江大學<br>保險學系保險經營碩士班<br>95<br>According to change of industrial structure and financial crisis in Taiwan, the situation of most financing institutions exceed the time limit to loan is gradually worse. On this condition, we want to transfer the credit risk we undertaken by credit insurance. Furthermore, consumer’s loan credit insurance approves to sell in 1986, and stops to sell in 2003. And its ratio of loss every year mostly exceeds 100%. Investigating its main reason is that the content of contracts is too old to match with times and revises it in time. Do not establishing the appropriate way to control risks is the other reason. Therefore, financing institution neglects their essential responsibilities of investigating and controlling risk cause of insurance. Then it makes that the indemnity rate of insurance companies is high. Basis above, can the new kinds of credit insurance products approved in 2005, insurance contract, and way of controlling risks match the real demand? The question is worth to us to research and analysis.
Therefore, the research is in connection with the product of financial institution small loan credit insurance , rely on literature, academic base, analyzing articles and the situation of operation, in addition this research also compare with credit insurance in different countries and refer to agreements for risks control in insurance contracts to investigate the product feature and the direction of operation.. Furthermore, this research advances efficacious way to deal with the situation to help insurers and supervisor organization when they have to operate this business in the future and then the system in Taiwan would be integrant and completed.
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Young, Chi-Jou, and 楊啟洲. "Risk Prediction of Credit Loan Using Backpropagation Nwural Network." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/28503255685667719504.
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碩士<br>中華大學<br>科技管理研究所<br>93<br>According to the Bureau of Monetary Affairs, Financial Supervisory Commission in Taiwan, as of the end of December 2001, the average of nonperforming loan ratio of all banks had reached a historical high. As the financial leverage effect of the banks is getting worse, and the rate of interest is decreasing, the interest collected can no more cover the loss caused by the bad debts. Credit guaranty has becomes one of the important means, under the severe competition nowadays, to avoid as well as predict the risk of loan. Traditionally approaches using statistic or mathematic model to accomplish the risk-avoiding task, such as discriminant analysis and logistic regression have limited themselves to a stricter environment or background, which is lack of adaptability in reality. In this paper, a neural network trained by the backpropagation paradigm (BPN) is utilized as a tool for predicting the risk in credit guaranty. We enumerate 37 discriminated variables, partly theoretical and empirical, as the input variables for the neural network. The data were collected from a financial institute, where those between 1999 and 2002 were used for training and between 2003 and 2005 were used for testing. As a result, The BPN achieved a correct prediction rate of nearly 100% in predicting the attribute of the loaner. The proposed model is suitable for a decision-support tool in granting loans; furthermore, it establishes the groundwork for value-created activities in the customer relation management.
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Chen, An-Chi, and 陳安琪. "An Efficient Credit Risk Model for Banking loans through an Automatic Tailored Tool." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/15982395960005235627.
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碩士<br>國立清華大學<br>資訊工程學系<br>95<br>Almost every finance institution pays lots of attention and energy to deal with credit risk. The default correlations of credit assets have a fatal influence on credit risk. How to model default correlation correctly has become a prerequisite of effective management of credit risk. In this thesis, we provide a new approach to estimate future credit risk on target portfolio based on the framework of CreditMetricsTM by J.P. Morgan. However, we adopt the perspective of factor copula and then bring the principal component analysis concept into factor structure to construct a more appropriate dependence structure among credits. In order to examine the proposed method, we use real market data instead of virtual one. We also develop a tool for risk analysis which is convenient to use, especially for banking loan businesses. The results show the fact that people assume dependence structures are normally distributed will indeed lead to risks underestimate. On the other hand, our proposed method captures better features of risks and shows the fat-tail effects conspicuously even though assuming the factors are normally distributed.
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Peng, Shih-Weng, and 彭世文. "Analysis of the personal credit characteristic on comsumer banking – based on small-scale credit loan." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/52630083868649547078.
Full textAbstract:
碩士<br>國立政治大學<br>資訊管理研究所<br>96<br>This research analyses the characteristics of small-scale credit loan applicants on the persepective of repay performances，allowing the banks not only to discriminate
between good and bad applicants but also to establish different lending tatics for applicants of different repay performance groups。We also analyse the personal characteristics and joint credit informantion of these applicants to sieve out the representative factors，and study how these factors affect the repay performance
groups。
Our research discovers that the applicants can be discriminanted into three groups：「low but steady repay ability—low overdue loss」、「good repay ability—
acceptable overdue loss」、「very low repay ability—high overdue loss」。We can learn from those factors，that most applicants grouped as 「low but steady repay ability—
low overdue loss」also have good credit qualities in other aspect；applicants grouped as 「good repay ability—acceptable overdue loss」 have finance management concept
and good financial condition；applicants grouped as 「very low repay ability—high overdue loss」have debt burdens and bad credit qualities。
As for the revenues and riks，we can improve the profit and loss with fewer applicants by taking differenct lending policies to those three groups。By using multinomial logistic regression，we can discover those factors who has significant effects and use these factors to cluster applicants into groups and to adopt different lending policies for these groups。Because those factors represent the induction of the variables which can explain the applicants’ behaviors，we can somehow prevent the risks by establishing different policies with the coordination of these factors and clusters。
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Lu, Chin-Pin, and 呂金品. "Estimating the credit risk of consumer loan by decision tree." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/49115167751245611230.
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PAN, CHIN-LUNG, and 潘錦龍. "A Case Study Of Credit Warranty On Offshore Business Loan." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/78986656845954466680.
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Chuang, Hsin-Lin, and 莊欣霖. "Constructing Credit Rating Model for Bank Loan Using Logistic Regression." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/54583450065847219691.
Full textAbstract:
碩士<br>國立交通大學<br>工業工程與管理系<br>90<br>Credit rating is used for bank to investigate the repayment ability of borrower. Because of economics depression and higher overdue loan rate, more and more bank start to improve their present credit rating model to be a batter one. Character, Capacity, Capital, Collateral, and Condition of business are the factors that impact the borrower’s credit. And how to use these factors to built a useful credit rating model is just the importance that bank want to know.
Based on the above, we should use logistic regression to build a clear procedure for bank to construct a batter credit rating model. The procedure has three stages：（1）variables selection and data collection, （2）building risk assessment model for bank loan （binary discrimination）,（3）constructing multi-level credit rating model. Among that, risk assessment model is used to classify borrowers into regular group and default group and credit rating model is used for bank as a multi-level discrimination to investigate borrowers’ credit more flexibly.
Finally a finance company is chosen as a example in the study. We use above procedure to construct this company’s credit rating model. Our finding shows that not only risk assessment model for binary classification has high correct rate but using multi-level credit rating model we could find out the default borrowers which have shortest payment life（under 3 months）. According to above, it shows the model constructing by this procedure is useful for the finance company. Another bank and finance company also can follow this procedure to build their own credit rating model.
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Jow, Wen-Jang, and 周汶璋. "The Evaluation of Loan Risks under Agricultural Credit Guarantee Fund." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/04047144200397092287.
Full textAbstract:
碩士<br>國立屏東科技大學<br>熱帶農業暨國際合作系所<br>99<br>To help guarantee a lack of capacity of farmers and fishermen to enhance its credit, access to agricultural operations necessary funds to improve the agriculture and fishery management, improve the income of farmers and fishermen, by government agencies, agricultural banks and the farm and fishery co-donor fund established Agricultural Credit Guarantee Fund guarantee.
Meanwhile, in order to enhance the quality of bank credit to reduce the possibility of overdue loan, this research is an eastern branch of the Agricultural Credit Bank to study the main case. For 2005 to 2008 by the Agricultural Credit Guarantee Fund for guaranteed loans of small farmers credit, apply for loans on-line customers to use when the basic information such as annual income, age, amount of debt, housing its own, borrowing rates the loan period and finishing the last literature review, analysis and evaluation using Logit model to examine the impact of late and correlation of the main factors why.
Construct an appropriate model for credit review, audit reference for agricultural credit institutions in order to reduce the NPL ratio of credit cases, the compensation to reduce the amount of boundary disputes.
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Feng, Chi-I., and 馮祺壹. "The Credit Rating Models on Mortgage Loan for Financial Institutions." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/88710813008688758042.
Full textAbstract:
碩士<br>東吳大學<br>企業管理學系<br>98<br>Mortgage loans is the most important and the major income sources of banks personal
credit business project, but it also hide the over-focus on housing loan in loan credit business.
Once the housing loan client breakout serious overdue default, it will cause a great deal of
damage to the bank. Therefore, the bank must establish a complete credit racing evaluation
model and improve the percentage of good credit low-risk, in order to decrease the happen of
bad loans.
The major object of this research is for Taipei city and Taipei County’s housing mortgage
loan applications. The data ranges from 6.1.2008 to 5.31.2009 of 766 cases of housing loan
applications that has been approved. Using random forest first to arrange the variable of the
invest in sequence and find out the impact of credit rating of important variables. Then individually
build mortgage customer credit rating pattern by rough set theory, classification, regression
tress and decision to analyze the model. Expecting to find a better home loans credit
rating model that provides financial industry as a practical reference.
According to the empirical result, using random forest to arrange and the variable of the
invest in sequence, the importance should be list as below: credit card amount, no warranty
loop total debt, nearly three months that query times, length of service, loan rate, education
level, income, loan amount, work character, credit card number, etc., the main reason that influences
the real estate loan credit rating of the client.
In the terms of the forecast accuracy of the overall model, weather testing the sample
group through random forest or not, rough set theory performed the best. Using random
forest to arrange variable can increase the accuracy rate of rough set theory . In addition, the
entirety accuracy forecast of type II error shows that consolidation random forest and rough
set theory model , consolidation random forest and decision tree model , and integration of
random forest and classification regression tree model , increases the forecast accuracy of
credit rating for high risk customers even more.
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Yang, Shi-Jung, and 楊喜榮. "A Study of Consumer Personality Trait and bank’s loan credit." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/67452330603416067157.
Full textAbstract:
碩士<br>育達商業科技大學<br>企業管理所<br>100<br>Back into 2005, the USA suffered from the most serious housing bubble because of the increasing events that people could not pay their housing loans, and this situation jeopardizing its finance-related industries seemed to be worse and worse. Experienced the Bankruptcy of Lehman Brothers (2008) and mergence of Merrill Lynch by Bank of America (2009), even though the Iceland use to be so-called the most prosperous country among the worlds could not sit on the sidelines. The financial Tsunami has been sweeping the Europeans, and global economics is still under the severe recession. This means Taiwan with its financial market linking to international markets closely shall have to be vigilant on the contract break of loans.
This study takes the six consumer loans types of users in T bank, and divides the six types into groups successful or failed cases, and then analyzes the relation between the explicit and implicit Enneagram of personality and the credit extensions effect of the bank. The samples using for the research are collected from 279 valid questionnaires by sending out the total number of 300 ones. The research finds that the 2nd(Helper), 4th(Individualist), 7th(Enthusiast), and 8th(Challenger) types of consumers have most significant influences upon the fail loan cases, and on the other hand, the 3rd(Achiever), 5th(Investigator), and 9th(Peacemaker) types contribute the most to the successful loan cases based on the logistic regression model. Different from the verified aspect of public banks, the attempt to discovery different groups of consumers’ personality and then build a set of good verified rules for those in charge of credit extended verification to follow will help to bring down the risk of loan turning into bad debt, and then build. The study also extracts 9 consumer behavior factors with the most important degree to the successful loan cases for the strategy-planning people to refer to.
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Lin, Yueh-Shen, and 林岳伸. "A Study of Credit Risk Model to Evaluate Consumer Loan." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/09621680826055359124.
Full textAbstract:
碩士<br>國立雲林科技大學<br>財務金融系碩士班<br>101<br>Recent years have seen constant change in the global financial market. In late 2005, there was the outbreak of the dual-card crisis, which wrought serious damage to banks in Taiwan. Then there was the American subprime mortgage crisis in July of 2007, which dealt a blow to financial institutions worldwide, and led to the 2008 financial tsunami. In this ever-changing environment, risk control issues are subjects of great concern. Banks absorb the general public''s deposits, then use the funds for loans or intermediary financial instruments. Hence, banks have an obligation to fulfill their management responsibilities.
Between 1991 to 1992, the government approved the establishment and operation of 16 new banks, and simultaneously also approved the applications made by trust and investment companies, large credit unions and small and medium-sized banks to be restructured as commercial banks, thereby doubling the number of such banks. This brought about excessive competition between financial institutions to gain market share, specifically through price cutting, lowering loan interest rates or relaxing credit conditions. As a result bank profits were reduced. In the event of an economic downturn, they could easily become unable to write off bad loans. For this reason, a credit risk assessment model was established, able to identify effective risk factors and reduce bad loans, thereby increasing profitability in banks.
In this study, logistic regression analysis was adopted to arrive at a risk rating based on seven risk factors: gender, seniority in employment, current ownership of residence, marital status, discrepancy in loan application and approval, credit card usage, and joint credit score. A bank can then adjust its risk control operations accordingly. In addition, this study added cost as a factor for consideration, finding that several normal loans would be needed to compensate for the generation of one bad loan, and achieve breakeven. Therefore, only a stable and conservative modus operandi can ensure the profitability of banks and the deposit of public assets.