東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Predicting powers of potential incom...

Addo, Charles Kwame.

FindBook

Google Book

Amazon

博客來

Predicting powers of potential income versus credit history for loan repayment.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Predicting powers of potential income versus credit history for loan repayment./
作者:	Addo, Charles Kwame.
面頁冊數:	118 p.
附註:	Adviser: Reza G. Hamzaee.
Contained By:	Dissertation Abstracts International67-10A.
標題:	Business Administration, Banking. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3237579
ISBN:	9780542921209

Predicting powers of potential income versus credit history for loan repayment.
Addo, Charles Kwame.

Predicting powers of potential income versus credit history for loan repayment. - 118 p.

Adviser: Reza G. Hamzaee.

Thesis (Ph.D.)--Walden University, 2006.

This study examined Potential Income as a factor in predicting loan repayment to minimize the problem of loan defaults. Risk management theories have provided emphatic guidelines for risk control and management of banks' loans, yet the results of other research indicate that the credit evaluation system does not fully explore all available predictors of loan repayment and is therefore less efficient at predicting loan repayment. Specifically, there is a lack of academic research on the predictive power of potential income on loan payments. Lending exposures constitute the most material risk concentrations within a bank. This study will help Banks to impose better controls over credit risk.

ISBN: 9780542921209Subjects--Topical Terms:

1018458
Business Administration, Banking.

Predicting powers of potential income versus credit history for loan repayment.
LDR:02977nam 2200313 a 45 001 967934
005 20110915
008 110915s2006 eng d
020 $a 9780542921209
035 $a (UMI)AAI3237579
035 $a AAI3237579
040 $a UMI $c UMI
100 1 $a Addo, Charles Kwame. $3 1291803
245 1 0 $a Predicting powers of potential income versus credit history for loan repayment.
300 $a 118 p.
500 $a Adviser: Reza G. Hamzaee.
500 $a Source: Dissertation Abstracts International, Volume: 67-10, Section: A, page: 3883.
502 $a Thesis (Ph.D.)--Walden University, 2006.
520 $a This study examined Potential Income as a factor in predicting loan repayment to minimize the problem of loan defaults. Risk management theories have provided emphatic guidelines for risk control and management of banks' loans, yet the results of other research indicate that the credit evaluation system does not fully explore all available predictors of loan repayment and is therefore less efficient at predicting loan repayment. Specifically, there is a lack of academic research on the predictive power of potential income on loan payments. Lending exposures constitute the most material risk concentrations within a bank. This study will help Banks to impose better controls over credit risk.
520 $a The purpose of the present study was to investigate the predicting powers of potential income as an additional independent variable to credit history to predict loan repayment. An original survey instrument was designed and administered to 146 participants. Loan Repayment was the dependent variable, and Credit History and Potential Income were the independent variables. The key statistical tool employed to establish meaningfulness of the relationships was multiple regression. Results of the regression were significant, F(2, 143) = 83.13, p < .001; and Credit History and Potential Income predicted 53.1% of the variance in Loan Repayment. The findings suggest that lenders should consider both credit history and income potential predictors in credit rationing decisions. Further studies are recommended to enhance sound credit decisions by reducing incidences of loan defaults.
520 $a The results may impact positively on the way society rations credit. Lenders may gain in-depth understanding of the most important factors in making credit decisions to reduce loan default experiences. This would allow for increased consumer spending and lead to more stimulating effects on macroeconomic activities. This would also make homeownership possible for many who would be otherwise judged on their credit history more than their potential incomes.
590 $a School code: 0543.
650 4 $a Business Administration, Banking. $3 1018458
650 4 $a Business Administration, Management. $3 626628
650 4 $a Economics, Finance. $3 626650
690 $a 0454
690 $a 0508
690 $a 0770
710 2 0 $a Walden University. $3 718925
773 0 $t Dissertation Abstracts International $g 67-10A.
790 $a 0543
790 1 0 $a Hamzaee, Reza G., $e advisor
791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3237579