運用現金流量模式篩選財務健全公司

信用風險管理是一個對業主及營建公司雙方都非常重要的事，信用危機的發生，往往對雙方造成龐大的損失。因此建立一套信用風險管理對雙方而言是個非常重要的課題，風險預審的目的是挑選出最適合的廠商或者業者，進而減少工程失敗的風險，審查標準包含了技術、管理能力、安全考量、環境及財務狀況，其中營建公司現金流量是一個最重要因素，現金流動不僅會使營建公司無法如期履行其債務，進而導致公司面臨週轉困難，甚至破產，這將使造成建設中工程延緩或者失敗。今日業主廣泛使用會計信用評分法以及財務信用評分法來對營建公司進行財務風險的評估，但會計信用評分法所使用的財報內容容易被人為操控，而且有時間落差的現象。而財務信用評分法的主要基礎是以股票所反應出的公司價值為主，並且假設公司所有的價值是如實反應在股票市場上，但現實上股票時常未能正確反應出公司的價值。本研究藉結構型現金流量基礎模型來對營建公司的財務風險進行分析，公司的財務風險與其是否有足夠現金來週轉其債務有高度關聯，本研究導入結構型現金流量基礎模型來模擬該公司的信用風險分數，業主可利用此分數來判別該建商是否符合財務資格，由於結構型現金流量基礎模型僅需要財報中的現金流量做為評計基礎，此模型適用於上市及非上市營建公司。本研究模擬出營建公司未來三年的財務信用風險，然後將之與各公司標準普爾(Standard and poor)信用等級做比較，本研究同時借用接受者操作特性曲線(R.O.C.)來評估本模型的辨別能力，研究結果第一年AUC:0.8833，第二年AUC:0.85，及至第三年AUC:0.85，R.O.C.結果證實結構型現金流量基礎模型是適用於營建業的財務風險評估，本研究期望此模型能建立成一個適合於營造業的財務預警分析模型，業主能藉此模型更準確篩選出財務能力佳的營建公司。

關鍵字

營建公司；信用風險；現金流量基礎模型

並列摘要

Evaluating a company’s financial health has always been a difficult proposition for construction industry. Credit risk evaluation challenges investors, financial institutions and academics alike. The construction industry has come to rely on two distinguished credit risk evaluation methods: the accounting-based method depends on a corporate balance sheet as a guide, whereas the market-based model relies on market information to predict financial distress. However, present credit risk evaluation models have their limitations. A corporate balance sheet is easily manipulated by management, and the market information method is based on the presumption that stock price is a full reflection of market information, which is doubtful even among scholars. This study evaluates a cash flow-based credit model proposed by Liao and Chen (2006). This model uses free cash flow to predict the credit qualities of construction contractors. In addition, this study uses the Area Under Curve (AUC) to determine the model’s discriminatory Performance. The Model’s performance will be benchmarked against Standard and Poor’s credit rating of the sample construction contractors. The empirical results indicate that the cash flow-based model has an excellent discriminatory power: AUC = 0.8833 in the first year, AUC = 0.85 in the second year and AUC = 0.85 in the third year. This model proves to be a useful tool in assessing the credit risk of construction Contractors. It is both applicable in listed and private construction contractors since this model only needs the information from accounting statements.