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A Decision Support Approach for Accounts Receivable Risk Management
Stockholms universitet, Samhällsvetenskapliga fakulteten, Företagsekonomiska institutionen. University of Toronto, Canada.
2014 (engelsk)Inngår i: IEEE Transactions on Systems, Man, and Cybernetics: Systems, ISSN 2168-2216, Vol. 44, nr 12, s. 1624-1632Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Financial disasters in private firms led to increased emphasis on various forms of risk management, to include market risk management, operational risk management, and credit risk management. Financial institutions are motivated by the need to meet increased regulatory requirements for risk measurement and capital reserves. This paper describes and demonstrates a model to support risk management of accounts receivable. We present a decision support model for a large bank enabling assessment of risk of default on the part of loan recipients. A credit scoring model is presented to assess account creditworthiness. Alternative methods of risk measurement for fault detection are compared, and a logistic regression model selected to analyze accounts receivable risk. Accuracy results of this model are presented, enabling accounts receivable managers to confidently apply statistical analysis through data mining to manage their risk.

sted, utgiver, år, opplag, sider
2014. Vol. 44, nr 12, s. 1624-1632
Emneord [en]
Accounts receivable, data mining, decision support system, enterprise risk management, risk measures
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-111901DOI: 10.1109/TSMC.2014.2318020ISI: 000345627700006OAI: oai:DiVA.org:su-111901DiVA, id: diva2:779754
Merknad

AuthorCount:3;

Tilgjengelig fra: 2015-01-13 Laget: 2015-01-08 Sist oppdatert: 2015-01-13bibliografisk kontrollert

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