Designing a Self-Learning Knowledge Based System for Credit Evaluation of Loan Application: in the Case of Commercial Bank of Ethiopia
| dc.contributor.advisor | Solomon Teferra (PhD) | |
| dc.contributor.author | Wesenu Bekele | |
| dc.date.accessioned | 2025-08-05T00:20:45Z | |
| dc.date.available | 2025-08-05T00:20:45Z | |
| dc.date.issued | 2014-10 | |
| dc.description.abstract | This study on prototype se lf-l earning knowledge based system is focused on evaluation of loan application (request) and is carried out to overcome the challenges that resulted from lack of domain experts and poor loan evaluations. The research attempts to design and develop a prototype se lf- learning knowledge based system that can provide advisory services for any credit customers and assists the domain experts in evaluation of customer's requests for the loan. To develop this prototype system, knowledge was acquired using semi-structured interview from domain experts which are selected using purposive sampling technique from Commercial Bank of Ethiopia and critique the acquired knowledge. Explicit knowledge is acquired by analyzing the secondary source of knowledge by method of document analysis. Then, the acquired knowledge is modeled using decision tree that represents concepts and procedures involved in credit evaluation and production rules are used to represent the domain knowledge. The prototype system is implemented using SWI Prolog editor tool. To determine the applicability of the prototype system In the domain area, the system has been evaluated and tested by the domain experts. Eighteen ( 18) test cases were selected purposively. Test cases are equally selected from both ineligible and eligible cases. The overall total performance of the prototype system is 77.7 1 %. The performance of the prototype system is hopeful and meets the objective of the research. The study concludes that the major credit production type that advanced to customer is import letter of credit facility, export credit facility, pre-shipment credit facility and merchandise. The eligibility of application is focused on general and specific criteria. Credit customer is classified as business, corporate and commercial based on the score sheet they achieved. Generally, in this stud y, the applicability of knowledge of prototype self- learning knowledge based system is proved as hopeful approach in banking industry for credit evaluation. The researcher also recommends further work; - like credit scoring, decision support system in credit evaluation and credit analysis. | |
| dc.identifier.uri | https://etd.aau.edu.et/handle/123456789/6044 | |
| dc.language.iso | en | |
| dc.publisher | Addis Ababa University | |
| dc.subject | knowledge based system | |
| dc.subject | se lf-learning | |
| dc.subject | credit (loan). | |
| dc.title | Designing a Self-Learning Knowledge Based System for Credit Evaluation of Loan Application: in the Case of Commercial Bank of Ethiopia | |
| dc.type | Thesis |