Relevant bibliographies by topics / Credit analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Credit analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Credit analysis"

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Lestari, Rhisca Meci, Ratu Eva Febriani, and Novi Tri Putri. "Pengaruh Kredit Perbankan Terhadap Pertumbuhan Ekonomi Provinsi di Sumatera." Convergence: The Journal of Economic Development 3, no. 2 (July 19, 2022): 179–95. http://dx.doi.org/10.33369/convergence-jep.v3i2.22388.

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The purpose of this study was to analyze working capital loans, investment loans and consumption loans in Sumatra Province in 2010-2018. This type of research used in this study is secondary data, namely data in the form of numbers or quantitative time series. Based on the results of the panel analysis of regression data by E-Views 9, working capital credit are positive and significant to economic growth in Provinces in Sumatra, investment credit is positive and significant to economic growth in Provinces in Sumatra and consumption credit have positive and significant income to economic growth in the Provinces all over Sumatra. Keywords: Working capital credit1, Investment credit2, Consumption credit3, Economic growth4
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Jiao, Jie, Jiyuan Zhang, Jie Yang, Wenwen Zhang, Fengtao Guang, and Liying Liu. "The Study of Carbon Neutralization Effects with Green Credit: Evidence from a Panel Data Analysis for Interprovinces in China." Sustainability 15, no. 17 (September 4, 2023): 13267. http://dx.doi.org/10.3390/su151713267.

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Giving full play to carbon emission reduction of green credits is essential to achieve carbon neutrality. According to low-carbon pilot policies and the condition of industrial transfer, this paper first sorts those provinces into different research zones. The zones are as follows: (Ⅰ) the first and second batch of low-carbon municipalities and the first batch of pilot provinces (L1) and other provinces (L2) and (Ⅱ) strong industry transfer-out zone (STR), weak industry transfer-out zone (WTR), and industrial transfer-in area (TIR). Then, we employ a dynamic panel data model and systematic GMM (SYS-GMM) approach to empirically test the impact of green credit and nongreen credit on carbon emissions. Further, this paper analyzes how to coordinate two types of credits to achieve carbon neutrality. The results show that, first, at the national level, the nexus of green credit and carbon emissions with an inverted U-shaped curve and the current impact of green credit is still in the first half of the inverted U-shaped stage. The achievement of carbon neutrality is associated with the ratio structure of green credit to nongreen credit and the scale of green credit. Second, the achievement of carbon neutrality is with regional heterogeneity. The achievement of carbon neutrality is associated with the scale of green credit in L2 and TIR, but also with the ratio structure of nongreen credit to green credit in L2 and STR. However, the carbon neutralization effects with green credit are insignificant in L1 WTR. Finally, based on those conclusions, this paper puts forwards some suggestions to provide references for the policy formulation of green credits and carbon neutrality.
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K, Roopa. "Credit Risk Management - A Case Analysis." International Journal of Science and Research (IJSR) 12, no. 12 (December 5, 2023): 361–66. http://dx.doi.org/10.21275/sr231128152822.

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Prasetiono, P., and Anisa Puspa Dina. "Determinant analysis of MSMEs credit in Indonesia." Diponegoro International Journal of Business 3, no. 2 (December 31, 2020): 104–14. http://dx.doi.org/10.14710/dijb.3.2.2020.104-114.

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This study was conducted to analyze several variables as the determinants of credit of micro, small, and medium enterprises (MSME) in Indonesia. Those variables are society income, geographic branch penetration (GBP), demographic branch penetration (DBP), credit account per capita (CAC), and deposit account per capita (DAC) of commercial banks. The samples used in this study are 33 Provinces in Indonesia in the period 2013-2017 using the purposive sampling technique. We examined data uses the non-participant observation method by directly quoting financial, GRDP, banking, geographical, and demographic data. The analysis used in this research is multiple linear regression consisting of the classic assumption test, F test, t-test, and hypothesis testing. This study indicated that society income, CAC, and DBP have a positive and significant effect on MSME credit. In contrast, GBP has a positive but non-significant effect on MSME credit, and DBP has a significant negative effect on MSME credit.
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Jalilian, Negar, Seyed Mahmoud Zanjirchi, and Mark Goh. "Interactive scenario analysis of banking credit risks in intuitive fuzzy space." Journal of Modelling in Management 15, no. 1 (November 18, 2019): 257–75. http://dx.doi.org/10.1108/jm2-01-2019-0011.

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Purpose The purpose of the paper is to bring attention to documentary credits and the efforts to reduce debt obligations in credit history is recognized as an important source of uncommitted bank earnings. Credit risk has a significant impact on the stability of the banking system. This paper identifies the types of credit risk in the banking supply chain. Design/methodology/approach The authors model the types of credit risk using the intuitive fuzzy failure modes and effects analysis (IFMEA) and intuitive fuzzy cognitive mapping. The population of the study that is needed for the interviews and expert panels comprises senior managers and experts of a leading bank in Iran. The respondents are experienced in credit and banking risk and were selected through judgment sampling and snowballing. Findings The findings suggest that reducing the risks of the foreign letters of credit contracts can mitigate the risk in the agricultural sector, the specific risks of rent-to-own contracts, the risk of the long-term facilities and the specific risk of the domestic letter of credit contracts. Originality/value This research investigates Iran Tejart Bank’s credit risk, formulates a model of the types of credit risk present and analyzes them using the intuitive fuzzy failure modes and effects analysis and intuitive fuzzy cognitive map. Through this credit risk model, one can then facilitate risk management for better financial stability. Also, the model can be used to evaluate the risk indicators.
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Qasem, Mais Haj, and Loai Nemer. "Extreme Learning Machine for Credit Risk Analysis." Journal of Intelligent Systems 29, no. 1 (June 18, 2018): 640–52. http://dx.doi.org/10.1515/jisys-2018-0058.

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Abstract Credit risk analysis is important for financial institutions that provide loans to businesses and individuals. Banks and other financial institutions generally face risks that are mostly of financial nature; hence, such institutions must balance risks and returns. Analyzing or determining risk levels involved in credits, finances, and loans can be performed through predictive analytic techniques, such as an extreme learning machine (ELM). In this work, we empirically evaluated the performance of an ELM for credit risk problems and compared it to naive Bayes, decision tree, and multi-layer perceptron (MLP). The comparison was conducted on the basis of a German credit risk dataset. The simulation results of statistical measures of performance corroborated that the ELM outperforms naive Bayes, decision tree, and MLP classifiers by 1.8248%, 16.6346%, and 5.8934%, respectively.
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Yan, Shihang, Geyong Min, and Irfan Awan. "PERFORMANCE ANALYSIS OF CREDIT-BASED FLOW CONTROL IN INFINIBAND INTERCONNECTION NETWORKS." Journal of Interconnection Networks 07, no. 04 (December 2006): 535–48. http://dx.doi.org/10.1142/s0219265906001843.

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Credit-based flow control scheme that can be used to support both end-to-end and link-level flow control is becoming increasingly popular in high speed system area networks (SAN), e.g. InfiniBand networks where multiple processor nodes and I/O devices are interconnected using switched point-to-point links. By virtue of such a scheme, the downstream node sends credits to the upstream node indicating the availability of buffer spaces. Upon receiving credits, the upstream node injects packets into the networks. Performance analysis of credit-based flow control scheme plays an important role for the design and optimization of InfiniBand interconnection networks which have been widely used in many high-performance cluster, Grid and P2P computing systems. This study develops a new queueing network model for performance evaluation of credit-based flow control in InfiniBand networks. The performance metrics to be derived include the mean queue length, throughput and response time of the system. Simulation experiments have been used to validate the accuracy of the queueing network model. Results obtained from the analytical model have showed that this model can effectively evaluate the performance of credit-based flow control in InfiniBand networks.
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Ahn, Philip, and Dong-Hoon Shin. "An Emprical Analysis of Global Emission Offset Price Determinants on Voluntary Carbon Market: Focusing on Demand Factor." Crisis and Emergency Management: Theory and Praxis 20, no. 1 (January 30, 2024): 137–48. http://dx.doi.org/10.14251/crisisonomy.2024.20.1.137.

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This study analyzes the correlation between voluntary carbon market credit prices and three key sets of variables. Prior research on compliance carbon markets has identified these factors as a significant influence on emission price factors. This study employs the Autoregressive Distributed Lag (ARDL) model to test these relationships and empirically examines short and long term correlations by conducting cointegration tests between each variable and the emission credit price. The results of the study are as follows:First, electricity prices exhibit a positive relationship with credit prices in the short term but a negative relationship in the long term. Second, compared to regulatory carbon market prices, credit prices are influenced by temperature variables, reflecting local weather conditions. Third, the energy variable emerges as the most crucial factor impacting prices in both compliance emissions trading systems and voluntary carbon credits. This implies that companies aiming for carbon neutrality through voluntary carbon market credits must develop comprehensive strategies that consider various external circumstances.
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Godwin, Michael, and Colin Lawson. "The Working Tax Credit and Child Tax Credit 2003-08: a critical analysis." Benefits: A Journal of Poverty and Social Justice 17, no. 1 (February 2009): 3–14. http://dx.doi.org/10.51952/aiom7585.

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This article examines the policy, administrative and compliance issues that have arisen with the UK Working Tax Credit (WTC) and Child Tax Credit (CTC). It provides a critical commentary on overpayments; underpayments; error and fraud; take-up; and employer compliance costs. From a social policy perspective, these problems have damaged the effectiveness of tax credits, and from public policy and public finance viewpoints, they have damaged the reputation of HM Revenue & Customs (HMRC) and HM Treasury. There is a strong case for a re-examination of the programme and its administration, to see if realistic reforms could deliver a more effective system.
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Maag, Elaine, and Nikhita Airi. "Moving Forward with the Earned Income Tax Credit and Child Tax Credit: Analysis of Proposals to Expand Refundable Tax Credits." National Tax Journal 73, no. 4 (December 1, 2020): 1163–86. http://dx.doi.org/10.17310/ntj.2020.4.11.

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Policymakers grapple with the related issues of unequal incomes, relatively poor health, education, and economic outcomes for low-income children, and hardship among low- and moderate-income families. Refundable tax credits provide substantial support and relief to many. This analysis details who benefits from the earned income tax credit (EITC) and the child tax credit (CTC) and four large-scale tax credit proposals that would provide substantial and ongoing benefits through these or similar credits. Broadly, proposals focused on children exclude childless adults and the elderly, and proposals focused on work exclude nonworkers, including most of the elderly, but include many workers with children.
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Dissertations / Theses on the topic "Credit analysis"

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Zoccoletti, Valentina <1991&gt. "Credit risk and credit derivatives: an analysis of the market of CDS." Master's Degree Thesis, Università Ca' Foscari Venezia, 2018. http://hdl.handle.net/10579/12075.

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One of the most important risk for both financial institutions and private investors is credit risk. Credit risk arises from the possibility that the borrower defaults and does not pay back its debt causing a loss for the lender, but also, from the possibility that the creditworthiness of the borrower will deteriorate, affecting its ability to pay back its debt and the value of the investment. Credit risk has acquired a growing importance in the last two decades, which have been characterized by several financial disasters, started in 2007 with the US subprime mortgage crisis. In addition from the end of 2009, we could also observed at European level an increasing number of states such as Greece, Portugal, Ireland and Spain which were unable to repay their debt. As a result of such difficulties, it is increasingly felt the need of a correct management of credit risk and the creation of operations and financial instruments, which make it possible to negotiate this risk. In this thesis, I will analyze the main components of credit risk, then credit derivatives and in particular the valuation of Credit Default Swaps.
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Pille, Peter. "Performance analysis of Ontario credit unions." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0004/NQ33913.pdf.

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Ramanauskaitė, Giedrė. "Stress testing in credit risk analysis." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080620_110415-38466.

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The supervising institutions do not give to commercial banks indications what models have to be used for stress testing. This research was done in order to find out which mathematical/statistical models are and can be used in credit risk stress testing. Credit risk is one of the biggest financial risks that every bank faces. Stress testing is a tool of credit risk assessment that helps to estimate the consequences of the events that have really small probability to happen but if they occur, banks can have significant losses. This study determined that the most plausible event is adverse macroeconomic conditions. For this reason, models that include macroeconomic impact were presented. Vector autoregression and vector error correction model were tested using the empirical data received from Swedish central bank, Swedish statistics and Eurostat. For financial stability it is worth using vector autoregression or vector error correction model as they describe the macroeconomic environment in the most suitable way and they are appropriate for shock analysis by showing how the impact of any factor can change the whole system. Structure: introduction, main part (credit risk, methods and empirical analysis), publication, conclusions, references. Thesis consists of: 50 p. text without appendices, 13 pictures, 11 tables, 26 bibliographical entries. Appendices included.
Kredito įstaigų priežiūros institucijos nepateikia komerciniams bankams kokius metodus jie turėtų naudoti testavime nepalankiomis sąlygomis. Tiriamasis darbas buvo atliktas tuo tikslu, kad būtų išsiaiškinta kokie matematiniai ir statistiniai metodai yra ir gali būti naudojami kredito rizikos vertinime testuojant nepalankiomis sąlygomis. Kredito rizika yra viena iš didžiausių finansinių rizikų su kuria bankai susiduria. Testavimas nepalankiomis sąlygomis yra kredito rizikos vertinimo įrankis, padedantis nustatyti įvykių, kurių realizavimosi tikimybės yra mažos, tačiau jiems įvykus, bankai patirtų reikšmingus nuostolius, pasekmes. Šis tyrimas nustatė, jog labiausiai tikėtinas įvykis gali būti ypatingai nepalankios ekonominės sąlygos. Dėl šios priežasties darbe yra pristatyti metodai, kurie įvertina makroekonominių veiksnių įtaką. Vektorinė autoregresija ir vektorinis paklaidų korekcijos modelis buvo patikrinti naudojant Švedijos centrinio banko, Švedijos statistikos departamento ir Eurostat empirinius duomenis. Finansinio stabilumo įvertinimui vertėtų naudoti vektorinį autoregresijos ar vektorinį paklaidų korekcijos modelius, nes šie modeliai geriausiai aprašo ekonominę aplinką bei yra labai tinkami šokų analizei, kadangi įvertina bet kurio veiksnio įtaką visai sistemai. Struktūra: įvadas, pagrindinė dalis (kredito rizika, metodai ir empirinė analizė), publikacija, išvados, literatūros sąrašas. Tiriamasis darbas sudarytas iš: 50 psl. teksto be priedų, 13 paveikslų, 11... [toliau žr. visą tekstą]
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Sewart, Pete. "Graphical and longitudinal models in credit analysis." Thesis, Lancaster University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387438.

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Mbayi, Willy Bashiya. "Analysis of credit expansion in South Africa." Master's thesis, University of Cape Town, 2008. http://hdl.handle.net/11427/10675.

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Includes bibliographical references (leaves 71-74).
Developments in South Africa over the past few years clearly testify to the strong relationships between economic growth and credit expansion. The paper analyses the factors driving credit growth in South Africa. It shows the strong income effect on the credit level in South Africa while the changes in interest rates do negatively affect home loans but have less effect on other components of bank credit to the private sector. This paper concludes that the interest rates policy must be combined with other tools of monetary and financial policy to guarantee a structurally lower level of credit to the private sector.
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Cecchetti, Sara. "An analysis of credit risk financial indicators." Doctoral thesis, Luiss Guido Carli, 2011. http://hdl.handle.net/11385/200885.

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Dozzi, Anna <1993&gt. "Prosper: Interest Rate and Credit Risk Analysis." Master's Degree Thesis, Università Ca' Foscari Venezia, 2019. http://hdl.handle.net/10579/14422.

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The technological development of recent years has allowed a revolution in the financial sector with the introduction of new financing methods including Peer to Peer Lending. In this study it will be discussed the business model of Prosper, which is a Peer to Peer Lending platform that aims to facilitate the connection between borrowers and creditors by implementing the disintermediation process. To get a general idea of the theme that will be discussed later, the most discussed topics in recent literature regarding P2P platforms have been reported. In particular, it will be analysed the topics of the relationship with the banks, the importance of the information related to the users of the platform, the credit risk and the interest rate. Subsequently, the Prosper database will be studied in order to understand the real advantages of this platform. In particular, from the data provided by Prosper will be studied the various information concerning the borrowers and creditors. Then, the loans provided by the platform will be examined, and the risk adjusted interest rate will be calculated from their interest rate and credit risk. The objective of this document is to determine the adequacy of the interest rates proposed by Prosper and to establish the variables that influence them.
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Ho, Kam-wah Patrick. "An analysis of the Hong Kong credit card industry : the competition and future development /." Hong Kong : University of Hong Kong, 1995. http://sunzi.lib.hku.hk/hkuto/record.jsp?B14038997.

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Chun, Pan, and Qiu Tian. "Credit card business analysis of Bank of China : Is BOC credit card competitive?" Thesis, Mälardalens högskola, Akademin för hållbar samhälls- och teknikutveckling, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-9981.

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Goth, P. J. "Issues in credit union corporate governance : a comparative analysis of Canadian and irish credit unions." Thesis, Queen's University Belfast, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.419436.

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Books on the topic "Credit analysis"

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David, Stimpson, and Moody's Investors Service, eds. Global credit analysis. London: IFR, 1991.

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Collett, Nick. Corporate credit analysis. London: Euromoney, 1992.

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Coyle, Brian. Corporate credit analysis. Canterbury: CIB Publishing, 2000.

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Morsman, Edgar Martin. Beyond traditional credit analysis. [Philadelphia, PA]: RMA, 2001.

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Yu, Lean, Shouyang Wang, Kin Keung Lai, and Ligang Zhou. Bio-Inspired Credit Risk Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-77803-5.

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Sathye, Milind, James Bartle, Raymond Boffey, and Michael Vincent. Credit Analysis and Lending Management. sydney: Wiley, 2003.

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Ganguin, Blaise. Fundamentals of corporate credit analysis. New York: McGraw-Hill, 2005.

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Grier, Waymond A. Credit analysis of financial institutions. London: Euromoney Books, 2001.

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John, Bilardello, ed. Fundamentals of corporate credit analysis. New York: McGraw-Hill, 2005.

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Petersen, Christian V. Financial statement analysis: Valuation, credit analysis, executive compensation. Harlow, England: Financial Times/Prentice Hall, 2012.

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Book chapters on the topic "Credit analysis"

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Yhip, Terence M., and Bijan M. D. Alagheband. "Credit Analysis and Credit Management." In The Practice of Lending, 3–46. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-32197-0_1.

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Lichters, Roland, Roland Stamm, and Donal Gallagher. "Credit." In Modern Derivatives Pricing and Credit Exposure Analysis, 191–234. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137494849_15.

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Doumpos, Michael, and Constantin Zopounidis. "Credit Scoring." In Multicriteria Analysis in Finance, 43–59. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05864-1_4.

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Sawyer, Tony, and Ken Andrews. "Corporate Credit Analysis." In Current Issues in Financial Services, 122–41. London: Macmillan Education UK, 1995. http://dx.doi.org/10.1007/978-1-349-24462-1_8.

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Oricchio, Gianluca. "Consistency Analysis between EVA Metrics and Credit Pricing." In Credit Treasury, 332–53. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230307308_6.

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Kiesel, Rüdiger, William Perraudin, and Alex Taylor. "An Extreme Analysis of VaRs for Emerging Market Benchmark Bonds." In Credit Risk, 111–37. Heidelberg: Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-642-59365-9_6.

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Härdle, Wolfgang Karl, K. F. Phoon, and D. K. C. Lee. "Credit Rating Score Analysis." In Applied Quantitative Finance, 223–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-54486-0_12.

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Marney, Richard, and Timothy Stubbs. "Macroeconomics and Credit Analysis." In Corporate Debt Restructuring in Emerging Markets, 233–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81306-2_10.

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Wind, Stefanie A., and Cheng Hua. "Partial Credit Model." In Rasch Measurement Theory Analysis in R, 133–94. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003174660-5.

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Donaldson, T. H. "Analysis." In Credit Control in Boom and Recession, 13–35. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1057/9780230390249_2.

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Conference papers on the topic "Credit analysis"

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Okay Toprak, Aslı, Canan Özge Eğri, and Güldenur Çetin. "The Usage of Credit Cards: An Empirical Analysis on Turkish College Students." In International Conference on Eurasian Economies. Eurasian Economists Association, 2019. http://dx.doi.org/10.36880/c11.02263.

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In recent years, there has been a dramatic increase in the number of credit card usage among university students. Credit cards can be a convenient payment tool that gives university students a number of advantages and benefits to learn financial responsibility when it can be used in a controlled and responsible manner. On the other hand, using credit cards also have serious financial consequences when mismanagedly used. The excessive credit card debt and overdue payments give burden on university students’ shoulders before starting their full-time jobs. Besides that, when the other debts such as education credits are added, inevitable stress and anxiety make negative impacts on their newly started adult life. Also, lack of experience on using credit cards and personal financial information, tend to put some students at a higher financial risk due to a large and perhaps unmanageable debt burden. Therefore, rising number of students who use credit cards increases the concern for these long-term negative results of the credit card. In this context, we aim to evaluate the basic demographic and socio-economic factors that affect the attitudes of Kırklareli University students towards credit card ownership, credit card usage, and to evaluate the students' ability to manage their financial situation.
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Mach, Maria. "TAL Rules Versus ECA Rules: an Attempt for Comparison in the Credit Management Context." In 2002 Informing Science + IT Education Conference. Informing Science Institute, 2002. http://dx.doi.org/10.28945/2528.

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Credits are the one of the most important functions in bank management, because, from one side, thanks to a good credit policy a bank can earn money, but from the other side, in the case of weak or wrong credit policy the bank can make substantial losses. Therefore in the field of credit policy management, intelligent information systems can be very helpful, as it is a complex and heterogeneous field, needing complex management and decision-making procedures. There exist many technical solutions aimed at helping the decision-makers in this field, from “traditional” ones, as databases, to more sophisticated tools, as for example expert systems, the main aim of which is to perform the analysis of applications for a credit, thus helping to make proper credit decisions. Credit management is closely related to time, in other words, the temporal aspect of credit management can be very clearly seen. Therefore while building intelligent systems in this area, it would be recommended to take this temporal aspect into account. The article concentrates on the question of searching and choosing an intelligent computer tool which would fulfil the above mentioned requirements, the toll which would help to make necessary credit analyses, to make proper credit decisions, taking into account the temporal aspect of credit management. Two solutions are discussed: TAL language and active databases. Some exemplary credit management rules are encoded both in the TAL language and in the form of ECA rules. Both kinds of rules are analysed and discussed, as well as their advantages and disadvantages.
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Cheng, Frank, Yagil Engel, and Michael P. Wellman. "Cap-and-Trade Emissions Regulation: A Strategic Analysis." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/27.

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Cap-and-trade schemes are designed to achieve target levels of regulated emissions in a socially efficient manner. These schemes work by issuing regulatory credits and allowing firms to buy and sell them according to their relative compliance costs. Analyzing the efficacy of such schemes in concentrated industries is complicated by the strategic interactions among firms producing heterogeneous products. We tackle this complexity via an agent-based microeconomic model of the US market for personal vehicles. We calculate Nash equilibria among credits-trading strategies in a variety of scenarios and regulatory models. We find that while cap-and-trade results improves efficiency overall, consumers bear a disproportionate share of regulation cost, as firms use credit trading to segment the vehicle market. Credits trading volume decreases when firms behave more strategically, which weakens the segmentation effect.
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Bing Liu, Jing Wang, Yu Gu, and Gang Liu. "Commercial customer credit analysis and implementation." In 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE 2010). IEEE, 2010. http://dx.doi.org/10.1109/cmce.2010.5610007.

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Varun, S., Abishek Theagarajan, and M. Shobana. "Credit Score Analysis Using Machine Learning." In 2023 International Conference on Networking and Communications (ICNWC). IEEE, 2023. http://dx.doi.org/10.1109/icnwc57852.2023.10127493.

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Pawar, Rohan, Hardik Kathuria, and Praveen Joe I. R. "Credit Card Fraud Detection and Analysis." In 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2023. http://dx.doi.org/10.1109/icccnt56998.2023.10306410.

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Du, Mingyi, Yingqi Xuan, Yunxuan Zhang, and Anqi Zhu. "Risk Management in the Credit Loan Project." In International Conference on Public Management and Big Data Analysis. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0011345900003437.

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Baltazar-Larios, Fernando, and Pablo Padilla Longoria. "A minimum-entropy-production criterion to compare credit risk models." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756572.

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Li, Yongliang, and Yaqin Liu. "Analysis on the Problems and Countermeasures of E-commerce Credit System and Credit Management." In 8th International Conference on Management and Computer Science (ICMCS 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/icmcs-18.2018.18.

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Bhandari, Tejanshu, Prasun Payne, Mahendra Kumar Gourisaria, Sudhansu Shekhar Patra, and Vishwanath Petli. "Guardians of Credit: "A Comprehensive Analysis of Machine Learning Models for Credit Risk Detection"." In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS). IEEE, 2024. http://dx.doi.org/10.1109/icicacs60521.2024.10498659.

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Reports on the topic "Credit analysis"

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Brewer, Mike, James Browne, and Wenchao (Michelle) Jin. Universal Credit: a preliminary analysis. Institute for Fiscal Studies, January 2011. http://dx.doi.org/10.1920/bn.ifs.2011.00116.

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Klinger, Bailey, Asim Khwaja, and Joseph LaMonte. Improving Credit Risk Analysis with Psychometrics in Peru. Inter-American Development Bank, October 2013. http://dx.doi.org/10.18235/0009139.

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Access to finance remains a challenge for some micro, small, and medium-sized enterprises (MSMEs) in Peru, particularly informal enterprises with no borrowing history in the formal financial system. Lenders lack the tools to reach these borrowers with sufficient scale and control over risk due in part to the shortcomings of current screening technologies. For this paper, the authors carried out a pilot test of an innovative psychometric tool aimed at evaluating credit risk for business owners seeking a loan from Financiera Confianza, the fourth largest Empresa Financiera in Peru. Applicant responses were compared to self-reported sales, subsequent loan repayment performance, and credit bureau data to determine if psychometric-based credit scoring models could reduce the constraints on MSME finance. The authors created a scorecard based on that information using data from other countries and evaluated its effectiveness on this sample. It achieved a Gini coefficient of between 20 and 40 percent. Those MSMEs rejected by a psychometrically enhanced application scorecard with this Gini coefficient have a probability of defaulting that is up to four times greater than those accepted by the scorecard. Along with other policies to reduce information asymmetry in MSME lending, such a tool could help relieve constraints on MSME finance in Peru.
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Wagner, J. C. Criticality Analysis of Assembly Misload in a PWR Burnup Credit Cask. Office of Scientific and Technical Information (OSTI), January 2008. http://dx.doi.org/10.2172/1187880.

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Amador-Torres, Juan Sebastián, Celina Gaitán-Maldonado, José Eduardo Gómez-González, Mauricio Villamizar-Villegas, and Hector Manuel Zárate-Solano. Credit and business cycles : an empirical analysis in the frequency domain. Bogotá, Colombia: Banco de la República, September 2014. http://dx.doi.org/10.32468/be.843.

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Guarín-López, Alexander, and Luis Ignacio Lozano-Espitia. Credit funding and banking fragility : an empirical analysis for emerging economies. Bogotá, Colombia: Banco de la República, March 2016. http://dx.doi.org/10.32468/be.931.

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DeHart, M. D., and S. M. Bowman. Analysis of fresh fuel critical experiments appropriate for burnup credit validation. Office of Scientific and Technical Information (OSTI), October 1995. http://dx.doi.org/10.2172/171331.

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DeHart, M. D. Analysis of Fresh Fuel Critical Experiments Appropriate for Burnup Credit Validation. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/814589.

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Yaroshchuk, Svitlana O., Nonna N. Shapovalova, Andrii M. Striuk, Olena H. Rybalchenko, Iryna O. Dotsenko, and Svitlana V. Bilashenko. Credit scoring model for microfinance organizations. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3683.

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The purpose of the work is the development and application of models for scoring assessment of microfinance institution borrowers. This model allows to increase the efficiency of work in the field of credit. The object of research is lending. The subject of the study is a direct scoring model for improving the quality of lending using machine learning methods. The objective of the study: to determine the criteria for choosing a solvent borrower, to develop a model for an early assessment, to create software based on neural networks to determine the probability of a loan default risk. Used research methods such as analysis of the literature on banking scoring; artificial intelligence methods for scoring; modeling of scoring estimation algorithm using neural networks, empirical method for determining the optimal parameters of the training model; method of object-oriented design and programming. The result of the work is a neural network scoring model with high accuracy of calculations, an implemented system of automatic customer lending.
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Bielen, David, Richard Newell, and William Pizer. Who Did the Ethanol Tax Credit Benefit? An Event Analysis of Subsidy Incidence. Cambridge, MA: National Bureau of Economic Research, February 2016. http://dx.doi.org/10.3386/w21968.

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Fernández Lafuerza, Luis, Matías Lamas, Javier Mencía, Irene Pablos, and Raquel Vegas. Analysis of the usability of capital buffers during the crisis precipitated by COVID-19. Madrid: Banco de España, March 2023. http://dx.doi.org/10.53479/29750.

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This paper analyses the ability of banks to use voluntary and regulatory capital buffers, taking advantage of the experience of the COVID-19 pandemic. In the first place, we find that the usability of macroprudential buffers is not hampered in Spain by other parallel banks’ requirements. Additionally, we find that the existing voluntary buffers over capital requirements at the beginning of the pandemic have had significant effects on the financial markets, affecting the evolution of European bank stock prices, as well as the holdings of bank shares by investment funds. Lastly, we find no significant aggregate effect of voluntary capital buffers on the provision of financing to non-financial companies in Spain. However, we do identify negative effects in the supply of credit from banks with lower voluntary buffers to companies with which they had more recent relationships. Likewise, if the analysis is carried out exclusively on credit operations without public guarantees, we observe that those banks with lower voluntary capital buffers reduced credit more.
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