Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) Automated Credit Decision Process -an insight into developing a credit-scoring model within the Nepalese Banking Sector.  There has been significant growth post-2000 in consumer credit within transition economies. Credit scoring, established within Western institutions, has the potential to be used to assess consumer creditworthiness here. This paper presents challenges and complexities relating to credit-scoring model development within the Nepalese banking sector. The research incorporates a mixed methods approach, involving model development using secondary data, supported by five in-depth interviews involving lending managers. A model was developed deploying binary logistic regression comprising six customer characteristics. Its overall ability to predict known outcome was high, particularly repayment success, although challenges remain in terms of predicting failure, pointing to a relative absence of current data on such customers. Implementation challenges also exist, reliance on traditional judgement prevails, together with ignorance of possible approaches to modelling. Decision overrides occur due to conflict between restricting defaulting customers and growth targets, traditional practice retention and desire to demonstrate expertise amongst lending managers.
REF examined the challenges and complexities relating to credit-scoring model development within the Nepalese banking sector.
Automated credit decision process – an insight into developing a credit-scoring model within the Nepalese banking sector
International Journal of Decision Sciences, Risk and Management
Economics