提昇應收帳款管理績效之因素探討

Improve the Determinants Management Performance of Account Receivable

林祝英(Chu-Ying Lin) ； 賴燕吟(Yan-Yin Lai)

《科際整合管理研討會》 2016第19屆 (2016/06) Pp. 132-149

https://doi.org/10.6495/CIMBM.2016.008

摘要

隨著交易方式的改變，已從現金交易逐漸為信用交易時代，同時伴隨信用風險，故企業需花費更多催收作業時間及人力成本來進行帳務管理，甚至須擔負著帳款可能無法回收而衍生之呆帳風險，為避免影響企業營運資金的運用及週轉，故應收帳款管理成為企業營運中需特別管理的目標。本研究擬由交易過程中取得的客戶基本資料、銷售資料、及應收帳款與票據等資料進行分析，以客戶公司特徵、風險徵兆等二個構面，共計10項變數來做為解釋應收帳款回收天數高風險之因素。經由上述分析研究，目的在於對應收帳款之風險評估資料，以logistic模型中逐步迴歸分析法來做為建立應收帳款回收品質之高風險預警模型。透過鑑別能力測試後，以此評估對於在應收帳款的高風險管控能力，達到降低應收帳款回收天數之目標並透過對催收部門人員之深度訪談，以瞭解個案公司在催收業務方面所遭過的困境，以提出如何有效降低應收帳款回收天數之建議。

關鍵字

應收帳款管理 ； 催收機制 ； 預警模型 ； 風險管理

並列摘要

With the changes of trading trends, transactions have gradually changed from cash transactions to credit transaction, accompanied by the risk of credit. So companies need to spend more time and manpower expenses for the collection practices of account management. Even to be charged by the balance and the risk of bad debt derivatives may not be recoverable. To avoid the impacts of using working capital turnover of enterprises, the accounts receivable become the target of recovery in business operations, which require special management. In this study, basic customer information, sales information, and accounts receivable and bills were analyzed. In two facets clients corporate identity, signs and other risk, total of 10 variables as explanatory factors do accounts receivable recovered several days of high-risk. Via the analysis, the aim of the accounts receivable risk assessment information to the to construct a high risk warning model quality of receivables recovery s prediction model by stepwise regression of Logistic. Through the ability to identify the test after, for this assessment of high risk management capability in receivables, for accounts receivable recovery targets to reduce the number of days and through in-depth interviews for collection of departments, to understand the business case in terms of the collection had been difficulties, in order to put forward recommendations on how to reduce the Days of Sales Outstanding.

並列關鍵字

Accounts Receivable Management ； Early Warning Model ； Collection Mechanisms ； Risk Management