Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/753
Title: DEBT COLLECTION OPTIMIZATION USING EFFECTIVE ELABORATE DATABASE( A CASE STUDY OF ATWIMA KWANWOMAN RURAL BANK LTD)
Authors: AFFRIM, ANITA
BERKYE, ELIJAH KWABENA
ASARFO, ADJEI JOSEPH
AKENTEN, FRED
Keywords: DEBT COLLECTION OPTIMIZATION A CASE STUDY IN ATIMA KWANWOMA RURAL BANK LTD USING EFFECTIVE ELABORATE DATABASE.
DEBT COLLECTION
OPTIMIZATION
CASE STUDY IN ATIMA KWANWOMA RURAL BANK
EFFECTIVE ELABORATE DATABASE
Issue Date: 1-Oct-2010
Series/Report no.: 1388;2019.1388
Abstract: The debt collection optimization system is a web application system proposed to be designed to improve the existing debt collection system. The main focus of the proposed system is to design a database collection of debt optimization system that would help banks to be able to trace loan collectors, monitor their accounts and be able to update their information from time to time in a reliable and secured manner very comfortably. During our research we discovered that there is no separate and protected debt collection optimization for the banks. The available debt collection optimization that the banks use is included in their big system that they use to run the bank and is seriously associated with a whole lot of problems and challenges. Some of these problems and challenges are: the banks are not able to update the information of the collectors and their guarantors, lack of accurate information of both the collector and the guarantor in the system, not creating an account for the guarantor in the same bank and some banks even write the name of their debtors in books. The above makes it very difficult for banks to collect their money from the debtors, monitor and manage the debt collection optimization system. The proposed system is thus designed to overcome the above problems and challenges. The proposed system is said to be very reliable, satisfactory, secured, user friendly and less time consuming relatively.
Description: Main Article
URI: http://localhost:8080/xmlui/handle/123456789/753
Appears in Collections:Department of Computer Science- ST



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