5. Credit Risk Modelling for MSMEs - understanding financial statements (2/2)

In my last article I described a few features which can be created from a business’ Profit & Loss P&L)/ Income Statement and few more that can be created using its Balance Sheet (BS). In this article I will try to describe a few that can be created using the combination of these two statements.

A word of caution – these statements are published at a point in time (usually 31st March) and may not be correct representation of the situation at a different point in time. We assume that the representation holds true even after a few months.

Turnover ratios

These ratios tell us about the ability of business to convert current assets and fixed assets to cash. The underlying principle is that a good business is one that is able to generate more cash from its assets and is able to do that fast. Thereby, the assets are more productive.

Fixed asset turnover ratio

Imagine a factory that uses very sophisticated (and costly) machinery but operates only 6 hours a day. The value of goods produced is much lower than the potential it has and it can be said that its capacity utilization is sub optimum. In simple term, they are not operating well.

Fixed asset turnover ratio = net sales/ average fixed assets

Interpretation – higher ratio means that the unit is able to generate more sales from its fixed assets and is thus performing efficiently. One has to be, however, slightly cautious because a very high fixed asset turnover ratio may also mean that the assets are being over used and this can lead to potential disruption of operations in near future. A wise thing to do is to compare the ratio with peers. We will discuss the interpretation of the value at the stage of model development.

Many people also use the inverse formula of average fixed assets by sales. That is also correct and only the interpretation is reverse.

Inventory turnover ratio

It answers the question – how fast is the business able to convert inventory of finished goods (or total inventory) to sales (the sale may be on credit leading to sundry debtors). A business which does so quickly saves on cost, enjoys a high demand for its products and should be able to make good profits. Imagine standing in que to buy an apple phone[1].

Figure 1 - Que outside Apple store (image courtesy metro news)

Inventory turnover = sales/ average total inventory

There can be various sub classifications of this formula that consider the inventory or only raw material (and this use cost of goods sold to calculate the ratio) or the work in progress inventory.

Another variable that can be created is inventory turnover in days. That is easier to interpret and tells that how many days does it take on an average to convert inventory to sales. Or, the inventory we are holding it equivalent to how many days of sales.

? Figure 2 - inventory turnover days

?Interpretation

Inventory turnover ratio – higher the ratio, better it is. This should be taken for a normal business operation and not distress sales.

Inventory turnover days – the lower the better.

Debtor turnover days

In the traditional manufacturing businesses or product sales, there is a lag between the day goods are sold and the day payment is received. This is so because the buyer wants a few days’ time to inspect the goods and then it passes through the steps of payment. The days might vary depending on who the buyer is. I recall that when I used to work for Indian railways, there were as many as twelve steps between the receipt of goods and issue of payment cheque!?

? Figure 3 - Debtor turnover days

Interpretation

Banks would want to finance a business that is able to collect payment as quickly as possible. Thus lower the debtor turnover days, the better it is considered.

Summary of key ratios

The table below shows the summary of all the ratios described in this article and the previous one. The last column shows the hypothesis of probability of default. Increasing means that a higher value of the variable should lead to a higher PD and decreasing means that a lower value of the variable should lead to a higher PD.

Monotonicity

A credit assessment model developed using logistic regression requires that there should be a high linear correlation between the default rate and value of the independent variable. It is referred to as monotonicity. This may not always be true in real life and in such scenarios, one should explore machine learning algorithms such as decision tree and random forest.?

Figure 4 - Chart of monotonicity

Next steps

I have completed the description of a few sample variables and the underlying logic for using those for financial analysis and development of credit assessment model. In the next article I will explain the process of feature engineering and feature selection.?

[1] https://metro.co.uk/2014/07/29/thousands-queue-to-enter-new-apple-store-in-china-4813411/