Bank Loans Valuation: a Straightforward Approach

2019 ◽  
Author(s):  
Bünyamin Erkan ◽  
Damien Pouponneau
Keyword(s):  
Bank Loans ◽  
Straightforward Approach

Discretionary Accruals in Italian Private Firms and Non-Linear Bank Loan Granting

2017 ◽  
pp. 83-99
Author(s):  
Elisabetta Mafrolla ◽  
Viola Nobili
Keyword(s):  
Financial Reporting ◽  
Banking System ◽  
Regulatory System ◽  
Discretionary Accruals ◽  
Bank Loans ◽  
Bank Loan ◽  
Banking Union ◽  
Private Firms ◽  
European Banking Union

This paper investigates whether and at what extent private firms reduce the quality of their accruals in order to signal a better portrait to the bank and obtain new or larger bank loans. We measure earnings discretionary accruals of a sample of Italian private firms, testing whether new and larger bank loans are associated with a higher (lower) quality of earnings in borrowers' financial reporting. We study bank loan levels and changes and how they impact discretionary accruals and found that, surprisingly, private firms' discretionary accruals are systematically positively affected by an increase in bank loans, although they are negatively affected by the credit worthiness rating assigned to the borrowers. We find that the monitoring role of the banking system with regard to the adoption of discretionary accruals is effective only when the loan is very large. This paper may have implications for policy-makers as it contributes to the understanding of the shortcomings of the banking regulatory system. This is an extremely relevant issue since the excessive amount of non-performing loans held by Italian banks recently threatened the stability of the European Banking Union as a whole.

CNN-based Classification of Degraded Images

2020 ◽  
Vol 2020 (10) ◽  
pp. 28-1-28-7 ◽  
Author(s):  
Kazuki Endo ◽  
Masayuki Tanaka ◽  
Masatoshi Okutomi
Keyword(s):  
Neural Networks ◽  
Image Restoration ◽  
Image Classification ◽  
Convolutional Neural Networks ◽  
Deep Convolutional Neural Networks ◽  
Alternative Approach ◽  
Degraded Image ◽  
Degraded Images ◽  
Straightforward Approach

Classification of degraded images is very important in practice because images are usually degraded by compression, noise, blurring, etc. Nevertheless, most of the research in image classification only focuses on clean images without any degradation. Some papers have already proposed deep convolutional neural networks composed of an image restoration network and a classification network to classify degraded images. This paper proposes an alternative approach in which we use a degraded image and an additional degradation parameter for classification. The proposed classification network has two inputs which are the degraded image and the degradation parameter. The estimation network of degradation parameters is also incorporated if degradation parameters of degraded images are unknown. The experimental results showed that the proposed method outperforms a straightforward approach where the classification network is trained with degraded images only.

The role of bank loans in economic growth of troubled regions

2019 ◽  
Vol 25 (12) ◽  
pp. 2859-2877
Author(s):  
N.V. Koloskova ◽  
◽  
G.F. Balakina ◽  
Keyword(s):  
Economic Growth ◽  
Bank Loans

Regression model of assessment of customer solvency and banking risks in the process of lending

2019 ◽  
pp. 69-73
Author(s):  
Zoryna Yurynets ◽  
Rostyslav Yurynets ◽  
Nataliya Kunanets ◽  
Ivanna Myshchyshyn
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Regression Model ◽  
Likelihood Ratio ◽  
Credit Scoring ◽  
Bank Loans ◽  
Management Decisions ◽  
Computer Data ◽  
Proposed Model ◽  
Loan Risk

In the current conditions of economic development, it is important to pay attention to the study of the main types of risks, effective methods of evaluation, monitoring, analysis of banking risks. One of the main approaches to quantitatively assessing the creditworthiness of borrowers is credit scoring. The objective of credit scoring is to optimize management decisions regarding the possibility of providing bank loans. In the article, the scientific and methodological provisions concerning the formation of a regression model for assessing bank risks in the process of granting loans to borrowers has been proposed. The proposed model is based on the use of logistic regression tools, discriminant analysis with the use of expert evaluation. During the formation of a regression model, the relationship between risk factors and probable magnitude of loan risk has been established. In the course of calculations, the coefficient of the individual's solvency has been calculated. Direct computer data preparation, including the calculation of the indicators selected in the process of discriminant analysis, has been carried out in the Excel package environment, followed by their import into the STATISTICA package for analysis in the “Logistic regression” sub-module of the “Nonlinear evaluation” module. The adequacy of the constructed model has been determined using the Macfaden's likelihood ratio index. The calculated value of the Macfaden's likelihood ratio index indicates the adequacy of the constructed model. The ability to issue loans to new clients has been evaluated using a regression model. The conducted calculations show the possibility of granting a loan exclusively to the second and third clients. The offered method allows to conduct assessment of client's solvency and risk prevention at different stages of lending, facilitates the possibility to independently make informed decisions on credit servicing of clients and management of a loan portfolio, optimization of management decisions in banks. In order for a loan-based model to continue to perform its functions, it must be periodically adjusted.

Industry Concentration and the Cost of Bank Loans

2010 ◽  
Author(s):  
Hoje Jo ◽  
Jay Junghun Lee ◽  
Jong Chool Park
Keyword(s):  
Bank Loans ◽  
Industry Concentration ◽  
The Cost
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