商業銀行對營建業的授信政策與評分模型

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楊景祺(Ching-chi Yang)

指導教授 ： 陳錦村

國立中央大學/管理學院/財務金融學系碩士在職專班/碩士(2007年)

摘要

國內因浮現雙卡債務問題，銀行近年來轉而爭取承作較具擔保條件之房屋貸款與建築融資，在國內金融環境極度競爭及房地產處於高檔觀望之下，銀行業者應思考如何審慎辦理不動產放款，以免重蹈覆轍，成為景氣拉回時的受害者。
目前國內幾家主要承作建築融資之行庫對營建融資授信辦法之訂定內容較為簡略，或辦法年久失修，不符需求，或授信過程過分依賴人為判斷方式，缺乏標準作為依循。本研究綜合目前銀行承作實務及研究人員之經驗，整合銀行辦理建築融資的相關放款條件，俾供銀行承作授信審查之參考。
本研究並利用Logistic Regression模型作實證分析，得出營建業授信風險評估之Logistic迴歸方程式，利用分割法探討每一分割值於信用評分模型建立後之預測準確率，進而評估其不同性質分類下之違約發生機率，期望能尋求出發生財務危機的顯著財務變數及模型預測率，以作為銀行、業者及投資者作為放款、經營及投資時參考之用。在研究中發現，財務比率變數Logsiict分析模型中，「營業利益率」、「TCRI 信用評等」、「在建工程佔資產比率」、「待售成屋佔資產比率」等四個變數達顯著水準；並得到在0.40機率界限下，為區分營建公司違約風險之最適點。另以無母數檢定方式（NPAR1WAY），得出本研究所定義之正常公司與有財務壓力公司間之違約率確有顯著差異，而在上市與上櫃公司間、TCRI風險級距、負債比率之區分上，違約率亦確有顯著差異。最後利用卡方檢定結果，比較出本研究之信用評分模型確實優於傳統大型企業評分方式。
研究中同時探討不動產證券化的發展，不動產證券化不但提供為投資人一項投資工具，亦提供企業作為籌措資金之管道。在進行風險分析時，建設公司必須根據其整體企業進行評估，而不動產證券化通常具備較明確且穩定的架構；目前實務上，開發型不動產在國內則尚未成型，依現行環境，尚不易成為營建業開發不動產過程之籌資方式。

關鍵字

Logistic迴歸模型分析 ； 營建業之授信政策

並列摘要

Influenced by the non-performing loans of cash cards and credit cards, banks in Taiwan gradually moved their focus, in recent years, to the mortgage loans and construction loans which were deemed to be better secured. Considering the highly competitive financial market in the country and the high price in the real estate market which is being observed, bankers should think carefully about their lending strategies to avoid repetition of the same problem, which could make them victims in the market when facing an economic recovery.
It was found that, among the major financial institutions in Taiwan who currently provide construction loans, the credit policies were either relatively cursory or had long been out-of-date, hence no longer meeting the market requirement. In some cases the credit approval process has been overly dependent on human judgment, being short of objective assessment criteria to follow. The purpose of the research, therefore, is to provide a good reference to banks in their credit approval process, by consolidating information on the current banking practices and the experience of researchers in the area, supported by a summary of the relevant terms and conditions for construction loans from the banks.
In this research, we used the Logistic Regression Model for our empirical analysis to obtain a logistic regression equation for the risk assessment on the construction loan business. Through the partitioning method, we further studied the forecast accuracy ratio for each partitioned value after the establishment of the credit scoring model, so as to analyze on the expected default frequency (EDF) under different categorization. The purpose is to identify the significant financial variables and the relevant forecast model ratio for companies with the potential of financial crisis, which could be used as a reference for banks, relevant companies in the industry and investors in the process of lending, management or investment decision-making. In was found in our research that, among the logistic analysis model on financial ratio variables, four items have reached the significant level, which are, respectively, the “Operating Profit Ratio”, “TCRI Credit Risk Index”, “Ratio of Constructions in Process against Total Assets” and “Ratio of Finished Buildings/Constructions for Sale against Total Assets”. The “Best Fit” point was also identified to be at the probability bound of 0.40. Further, through the NPAR1WAY methodology, we found that there was significant difference in the default ratio between the “normal companies” and “companies with financial pressure” defined in this research. There was also significant difference in default ratio between TSEC and GTSE listed companies, and in terms of the TCRI risk scale and liability ratio. Finally, a comparison was made through the Chi-squared fit test and the results showed that the credit scoring model referred to in this study was more effective than the traditional scoring method for large companies.
In the research, we also studied the development process of the asset securitization business. Asset securitization provides not only an additional investment instrument for the investors, but also an additional channel for companies to raise funds. When conducting risk analysis, it is recommended that the construction companies should assess on basis of the company as a whole. The asset securitization process normally has a relatively clear and stable structure. In practice, the securitization of real estate under development has not yet been materialized in the local market. Under the situation, therefore, it is unlikely to become one of the fund-raising channels for the construction industry when developing real estates.

並列關鍵字

Credit Policies for Construction Loans ； Logistic Regression Model Analysis

參考文獻

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