Intelligent Automated Small and Medium Enterprise (SME) Loan Application Processing System Using Neuro-CBR Approach

Developing a group of diverse and competitive small and medium enterprises (SMEs) is a central theme towards achieving sustainable economic growth. SMEs are crucial to the economic growth process and play an important role in the country's overall production network. The focus of this study is to develop an automated decision support model for SMEs sector that can be used by the management to accelerate the loan application processing. This study proposed an intelligent automated SME loan application
processing system (i-SMEs) that is a web based application system for processing and monitoring SME applications using Hybrid Intelligent technique which integrate Neural Network and Case-based Reasoning namely NeuroCBR. i-SMEs is used to assist SME bank management in order to improve decision making time processing as well as operational cost. i-SMEs be able to classify SME market segment into three distinctive groups that are MICRO, MEDIUM and SMALL and also can make a pre-approval loan processing faster. It is possible to transform the patterns generated from i-SME into actionable plans that are likely to help the SME Bank .