DOI: 10.4018/IJAIML.2019070104 International Journal of Artifcial Intelligence and Machine Learning Volume 9 • Issue 2 • July-December 2019 Copyright © 2019, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. 57 Intelligent System for Credit Risk Management in Financial Institutions Philip Sarfo-Manu, University of Energy and Natural Resources, Sunyani, Ghana Gifty Siaw, University of Energy and Natural Resources, Sunyani, Ghana Peter Appiahene, University of Energy and Natural Resources, Sunyani, Ghana ABSTRACT Credit crunch is an alarming challenge facing financial institutions in Ghana due to their inability to manage credit risk. Failure to manage credit risk may lead to customers defaulting and institutions becoming bankrupt, making it a major concern for financial institutions and the government. The assessment and evaluation of loan applications based on a loan officer’s subjective assessment and human judgment is inefficient, inconsistent, non-uniform, and time consuming. Therefore, a knowledge discovery tool is required to help in decision making regarding the approval of loan application. The aim of this project is to develop an intelligent system based on a decision tree model to manage credit risk. Data was obtained from the bank loan histories. The data is comprised of four hundred observations with seven variables: client age, amount requested, dependents, collateral value, employment sector, employment type, and results. The results of study suggest that the proposed system can be used to predict client eligibility for loans with an accuracy rate of 70%. KeywoRdS Artificial Intelligence, Credit Risk, Data Mining Algorithm, Decision Tree, Domain Expert, Expert System, Financial Institutions, Inference Engine, Knowledge Base INTRodUCTIoN Financial institutions such as banks are pursuing to advance their business operations with innovative technologies and intelligent or expert systems. This is to enable them to run their daily business processes such as solving, monitoring and credit risk management. Financial institutions have also undergone some changes due to globalization and use of new technology (Appiahene et al., 2019). This has created increased competition and further risks into the financial institutions. There are many evolving areas in the banking sector and one of the major areas is the risk management. Risk management in the banking sector has three vital areas; Market Risk Management, Credit Risk Management, Operations Risk Management (Kulkarni & Mali, 2015). Banks have been facing financial crises because lending loans to borrowers is one of the major ways to generate profit and this process is mostly done with the credit manager’s subjective knowledge. When client or customer defaults there is loss of principal and interest, disruption to cash flow in the banking system, and increased