考量風險控制下最佳化資金分配之研究

Abstract

在現今金融自由化下，信用卡已經普遍成為民眾使用工具，而銀行為爭奪市場發卡量，對於申請人進行信用狀況審核時，均以較為寬鬆的審核條件通過，以致於信用卡催收帳款急速增加，此舉雖然助長了金融機構的消金業務，但也為國內的信用危機埋下不定期炸彈，除此，新版巴塞爾協定也就銀行內部最低資本適足率提出新的規範，其原因是為了強化銀行風險承擔的能力，也有助於未來的健全經營。因此針對前來申請信用卡的客戶，銀行要能建立一套正確的風險管理制度，讓內部資金可以在客戶之間做最有效的分配，使得銀行利潤最大化，而不是盲目發行信用卡。 考量風險雖然是銀行核心的課題，但對銀行而言更重要的是獲利能力，而能夠結合這兩個構面的績效指標就是風險調整資本報酬率(Risk Adjusted Return on Capital，RAROC)，目前在金融機構中都會以此來衡量各種業務的獲利狀況。本研究鑑於此，將參考馬克維茲(Markowitz)所提出的投資組合(Portfolio)理論結合風險調整資本報酬率的觀念並以經濟資本用來衡量風險的方式進行分析，在分析的過程中，本研究將給定各預期報酬下，求出目標為總風險最低的最佳人數比例以及對應的風險調整資本報酬率。接著，以國外某銀行信用卡顧客資料建構出模型參數並進行實證分析，最後，利用迴歸分析進行敏感度分析以看出參數對銀行利益的影響。 透過本研究之分析可以得知，利用模型結果所得出的效率前緣曲線來進行決策將可得到較佳的績效，但在決定新的策略定位前仍須考慮移動障礙、競爭者和風險三個問題。而在決定策略定位點後可由本模式得到此策略定位點下的每群最佳人數比例，讓銀行資金能夠有效率的運用增加其實質利益。

The credit card has become a popular financial tool as the liberalization of trade in financial services. The card-issuing banks adopt a looser terms of credit score to compete in the fast-growing credit card market. This action not only significantly increases the volume of credit card and enlarges the sales of financial institution, but also draws fire against itself. New Basel agreement also put forward a new regulation of minimum capital requirement to strengthen the risk-bearing capacity of the banks for improving bank’s operation. Nowadays, banks have to establish a proper risk management system for their customers, such that they can make the most effective allocation of internal funds among the clients. Although banks need to consider the risk, they also need to improve their profitability. One of the performance index need to consider both risk and profitability, which is frequently adopted by banks, is the risk adjusted return on capital (RAROC). Based on the Markowitz’s portfolio theory and the concept of the risk adjusted return on capital, this research firstly derives nonlinear programming formulation to achieve the overall goals for the lowest risk, determines the best allocation proportion for each customer credit group, and figures out the corresponding risk-adjusted capital return from a fixed expected return level. Next, we configure the model parameters from credit card department in a foreign bank and perform empirical study to explore the impact on the bank’s benefits. Finally, the sensitively analysis on several important parameters is conducted by using regression analysis. In this research, we find that efficient frontier derived from our models can result in better performance. But in order to determine the new strategic position of bank, three obstacles need to be considered, including (1) the moving obstacles, (2) the competitors (3) the risks. Once the positioning process completes, the best allocation for each customer credit group can be obtained from our model to improve the efficiency of the bank’s funds allocation for increasing their real benefits.