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Browsing Research Article by Author "Namarta kapoor"

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    Fuzzy logic based decision support system for loan risk assessment
    (IJCSt Vol. 2, ISSue 2, 2011) Sangeet Kumar; Nitin Bhatia; Namarta kapoor
    This paper is concerned with risks associated with the loan Risk analysis and related adaptation strategies have grown in importance and complexity during last years. The large amount of data and information that needs to be handled and integrated requires specific methodologies and tools. So selecting a new loan applicant is a important issue of a financial organizations or Banks. There are so many different factors which effect on the selection of applicant who apply for loan. So, it’s a problem for Banks and other private financers to choose right applicant so that minimum risk involved during loan process using fuzzy logic. We control this problem in quicker and cheapest way using knowledge and experience of experts which are involved in this process and having knowledge about this field. This paper provides risk analysis based on fuzzy inference system. And provide GUI based interface tool regarding different parameters of an applicant which effect loan risk assessment. The analysis of experimental results of different applicants checks the correctness and consistency of decision Support system for correct decision making.
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    FUZZY LOGIC BASED TOOL FOR LOAN RISK PREDICTION
    (Apeejay Journal of Computer Science Applications Vol. 2, 2014) Sangeet Kumar; Nitin Bhatia; Namarta kapoor
    Loan risk is a major decision for any financial organization like banks or for decision maker for loan applicant. The uncertain domain of risk assessment has long been in need of a reliable and consistent system to help simplify the decision making process. Fuzzy Logic provides a completely different, unorthodox way to approach a control problem. This method focuses on what the system should do rather than trying to understand how it works. One can concentrate on solving the problem rather than trying to model the system mathematically, if that is even possible. This almost invariably leads to quicker, cheaper solutions. This research work will help in analysis risk for a loan applicant according to different factors like its job, salary, loan amount and loan period etc. the decision factor helps in making decision about how to select correct loan applicant. Using fuzzy logic decision variable has been defined, new rules defined, according to different rules added and takes average decision based on questionnaires filled by different categories of applicant’s. The analysis of case studies shows the consistency and effectiveness of the approach in making correct decision.