Do you want to publish a course? Click here

A Copmarative Study of Creditworthiness Models

دراسة مقارنة لنماذج الجدارة الائتمانية

3914   8   233   0 ( 0 )
 Publication date 2015
and research's language is العربية
 Created by Shamra Editor




Ask ChatGPT about the research

The use of the creditworthiness models is one of the used methods in the evaluation of bank loans and facilities clients in commercial banks,The main objective of creditworthiness study is to identify the future potential of the customer to repay the Granted credit and interest, many creditworthiness models had been provided, These models have been in a constant development of the variables included, And it has sought a researcher to study the most important of these models and compare them to gain access to the most comprehensive model, which can be used in the study of the customer's creditworthiness as a tool to avoid future risks at public and private banks in syria. Research problem stems from the fact that the granting of credit without study the creditworthiness of clients leads to face risks of future defaults in credit repayment, This requires knowledge of all factors of the creditworthiness to reduce the risks resulting from the granting of credit, both of which related to the bank or the client or other variables beyond the control of the parties. The research aims to identify the concept of creditworthiness and its Justification, and display the most important models, and a comparison between models and identify similarities and differences among them, it has been relying on the historical and descriptive and analytical approaches in the presentation of the creditworthiness of models, in addition to the inductive approach in order to access to the most comprehensive variables creditworthiness to be recommended to follow it during the credit decision making model. The researcher reached a set of results most important is the need to provide a model creditworthiness fits with the application environment, and that the form is familiar with financial and personal factors for the client borrower, and the more creditworthy models briefing these factors is the 18C's model, Accordingly, the researcher recommended the adoption of this model to study the creditworthiness of loan clients in the public and private banks operating in Syria.

References used
Gapko, Petr; Smid, Martin. Dynamic Multi-Factor Credit Risk Model with Fat- Tailed Factors, Journal of Economics and Finance, Vol. No. 62, Issue No. 2,2012
Feschijan, Daniela. Analysis of the Creditworthiness of Bank Loan Applicants, Economics and Organization Journal, 3 November 2008, Vol. 5, pp 273- 280
Moscardini, Alfredo; Loutfi, Mohamed; Al-Qirem, Raed. The Use of System Dynamics Models to evaluate the Credit Worthiness of firms, International Conference of the System Dynamics Society, 23rd July 2005, p 273
rate research

Read More

This study aims at identifying the differences between Syrian commercial public and private banks regarding the role of client's creditworthiness criteria and their relative importance in the credit decision-making process, in addition to recognizi ng the differences in empowerment between bank's branches in credit decision. To achieve the objectives of the study, a questionnaire is designed to cover the creditworthiness fields according to 5Cs model, which includes (Character- Capability – Capital – Collateral- and Condition). A Descriptive approach is used where hypotheses are tested by Independent Sample T-test from SPSS. The results showed that all 5Cs criteria are important in the credit decision- making process, but their importance differs among private and public commercial banks except for the collateral, where private banks place more weight to this criterion. Both types of banks have a high degree of centralization regarding credit decision, and restrict the power of their branches in dealing with lending files.
The study of clients creditworthiness aims to identify the aspects that may lead the client to a tumble in the future in the credit and burdens repayment, which requires an advance specific of the factors affecting it, and in order to avoid the ris ks that may occur in the future and lead to tripping, this paper seeks to study the most important factors of creditworthiness, and analysis to financial and personal factors, and determine the impact of these factors on creditworthiness. The researcher depended on the descriptive analytical approach in the presentation of the creditworthiness models, and to study and analysis of financial and personal factors in order to identify the most affecting factors in the creditworthiness of the credit clients. The researcher has reached to set of results, most important to analysis the creditworthiness factors to personal factors such as reputation, relationship with the lender and other banks, and the relationship with sovereign entities, and financial factors such as studying statements and financial ratios and predict financial failure. The most important recommendations of the paper the need to divide the creditworthiness factors to personal and financial factors in any model is proposed to assess creditworthiness. some personal factors such as reputation belongs to personal factors and predict financial failure belongs to financial factors will determine the value using a dualism [0,1], and any model creditworthiness must include most important personal factors which in addition to a reputable, relationship with banks and sovereign entities, and query the banking, and that the guarantees not be a starting point for grants in any case, the starting point should be in the purpose of the loan, and that the field visit attaches great importance to the strengthening of the credibility of the financial statements of the client, and interest in analyzing cash flows to be synchronized between the payment of premiums and inflows.
This research aims through using of the Financial failure prediction models to recognize the future possibility of financial failure of the studied company, these models are primarily based on a set of financial ratios that make up the indicator ca n be guided to evaluate the future possibility of financial failure. Research problem is in the absence of a certified model of financial failure prediction in Syriain spite of the abundance of available models. The research aims to introduce the concept and importance of financial failure, and to display a summary of the most important financial failure prediction models, and then make a comparison between them to determine the most accurate models to predict financial failure to Suit the Syrian financial and banking business environments.
From statistical to neural models, a wide variety of topic modelling algorithms have been proposed in the literature. However, because of the diversity of datasets and metrics, there have not been many efforts to systematically compare their performa nce on the same benchmarks and under the same conditions. In this paper, we present a selection of 9 topic modelling techniques from the state of the art reflecting a diversity of approaches to the task, an overview of the different metrics used to compare their performance, and the challenges of conducting such a comparison. We empirically evaluate the performance of these models on different settings reflecting a variety of real-life conditions in terms of dataset size, number of topics, and distribution of topics, following identical preprocessing and evaluation processes. Using both metrics that rely on the intrinsic characteristics of the dataset (different coherence metrics), as well as external knowledge (word embeddings and ground-truth topic labels), our experiments reveal several shortcomings regarding the common practices in topic models evaluation.
Abstract Debugging a machine learning model is hard since the bug usually involves the training data and the learning process. This becomes even harder for an opaque deep learning model if we have no clue about how the model actually works. In this s urvey, we review papers that exploit explanations to enable humans to give feedback and debug NLP models. We call this problem explanation-based human debugging (EBHD). In particular, we categorize and discuss existing work along three dimensions of EBHD (the bug context, the workflow, and the experimental setting), compile findings on how EBHD components affect the feedback providers, and highlight open problems that could be future research directions.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا