Abstract
This study analyses a sample of confidential invoice discounting clients using one particular branch of machine learning - an inductive algorithm as used in case-based reasoning (CBR). The sample used consists of data collected from 98 business clients of a leading UK factoring and invoice discounting company. The data collected was supplemented by financial accounting information2. Factoring and invoice discounting is an additional form of finance to the company’s overdraft facility. This study examines the profile of business clients (or cases) which bank with the invoice discounting company affiliated bank versus those business clients (or cases) which bank with competing banks. A few attempts have been made by this leading UK factoring and invoice discounting company to differentiate between case profiles. For the first time, this study provides an empirical framework for examining invoice discounting data. It also suggests the potential for a case-based approach based on induction which specifically handles multidimensional case information. The findings raise interesting questions for this factoring and invoice discounting company specific to its clients.
We are very grateful to the Journal of Applied Accounting Research for providing a grant to fund this research. We are also very grateful to Giles Elliott for his comments.
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© 1999 Springer-Verlag London
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Elliott, J., Curet, O. (1999). Invoice Discounting - A Strategic Analysis Using Case-Based Reasoning. In: Milne, R.W., Macintosh, A.L., Bramer, M. (eds) Applications and Innovations in Expert Systems VI. Springer, London. https://doi.org/10.1007/978-1-4471-0575-6_15
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DOI: https://doi.org/10.1007/978-1-4471-0575-6_15
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