Loans firms

Question 2

1. The following is a summary of SMEs’ data provided in terms of which firms default to pay the loans.

Lukacs, (2005, p.3) consider Small Medium Enterprises (SMEs) as the key driver and the backbone of the economy. SMEs are known to provide employment thus promoting the growth of an economy. Most of the SMEs fail to be transparent to their stakeholders as they are not listed. Banks comprises of the stakeholders who are greatly affected by the lack of transparency in financial reporting as they lend a huge amount of loans to SMEs. To curb such losses, banks have to separate “good SMEs” from “bad SMEs (Fantazzizini & Figini 2009, p.138). Over the years, various models have been developed with an aim of determining the Probability Default (PD) for business firms. A model with a higher success rate helps the banks in reducing the defaults rates thus it is beneficial to both the SMEs and its stakeholders.

According to Altman & Saunder (1998, p.1725), the best model to predict the SMEs default rate is the Altman Z score. The model uses five accounting indicators. The indicators are part of the financial ratios. The first indicator is obtained by dividing working capital with the total assets. Working capital is the difference between the total current assets and current liabilities.  This indicator is one of the leverage ratios.

The second indicator is obtained by dividing retained earnings with the total assets. This ratio is a measure of the amount of the money that is reinvested back into the firm. Altman (1968, p.590) argues that the ratio is essential as it helps the stakeholders to know where the finances of the company are coming from i.e. from previous profits. The third indicator is the measurement of how profitable a company is in its operations. The ratio is obtained by dividing earnings before interest and taxes by the total assets. This financial indicator is unaffected by the leverage.

The fourth indicator is given by dividing the market value of equity with the book value of liabilities. Equity value is determined by the market prices of both preferred and common stocks. This ratio helps to determine how much equity decline before liabilities overcoming the assets or the firm can become insolvent. The last ratio measures the capital turnover and is given by dividing total sales by the total assets.

A combination of the above mentioned ratios results to Altman Z-Score, which is an efficient predictor of the default rate by SMEs (Altman, Sabato & Wilson 2008, p.96). The following is the predictor model of SMEs provided in the excel spreadsheet.

Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + .999X5

Where: X1= Working Capital/ Total Assets

X2= Earnings/ Total Assets

X3= Earnings before income tax and interest / Total Asset ratio

X4= Market Value of equity/ Book value of total debt

And X5= Sales/Total Assets

Question 2 b: Estimating type 1 and type II Error

The table below shows the structure of the SMEs hold-out test sample. The first and second row contains the number and the percentage of non-defaulted and defaulted firms are shown.

The first measures of accuracy for each model is classified in defaulted and non-defaulted firms, as a complement of the arithmetic average of the type I and type II error rates. The second is referred to as the accuracy ratio (AR). The overall accuracy level (AR) of the two new logistic models is 75 percent, based on the unlogged variables, and 87 percent based on the logged variables. Most importantly, the type I error reduces when the logged variables model are used from over 21 percent to 11.76 percent. Also in the table, there is a comparison of the holdout results with the popular Z’’-Score results built by Altman & Saunders (1998, p. 1777) to include all industrial firm. Applying the five variable Z’’-Score model to the same holdout sample, there is an overall accuracy (AR) of 68 percent, compared to the 75 percent for the unlogged new variable model and the 87 percent for the logged structural approach. Again, the biggest improvement between the new model and the generic Z’’-Score approach was in the type I accuracy.

This part illustrates that improving the prediction accuracy of a credit risk model has a beneficial effects on the Basel II capital requirements for SMEs when the Advanced Internal

Question 2c:  Capital Requirement for SMEs

Rating Based (A-IRB) approach is used when applying a higher accuracy model, the results will be lower capital requirements regardless if the SMEs are all classified as retail customers or as corporate.

Most banks will use a blended approach, classifying a part of the SME portfolio as retail and a part as corporate (Altman & Sabato 2007, p.337). The following are the formulas necessary for calculating the capital requirement for the SMEs.

Substituting the formulas above, the total capital requirement is 4.755%

The conclusion is if banks classified their entire entire SME portfolio as corporate using the A-IRB approach, there is a possibility of facing higher capital requirements than when under the current Basel I.