Financial Statement Ratios and Models for Assessing Credit Risk

# Risk prediction based on financial statements


# Risk prediction based on financial statements












I have a profit loss statement and balance sheet with the following fields: Example

```

P&L          
Turnover420,363 -
  Cost of sales             £118,730    £140,169    -
Gross Profit                £178,862    £280,194    -
  Operating Costs           £154,889    £255,123    -
  Interest paid (received)  £3,007  £4  -
  Tax paid  -               £4,838  -
Profit After Tax (Loss)     £20,966 £20,229 -

Balance Sheet            
Total assets                £68,090 £47,032
  Current assets            £62,975 £43,847
  Fixed assets              £5,115  £3,185
Total liabilities           £56,560 £55,731
  Current liabilities       £56,560 £55,731
  Long-term liabilities     -   -
Shareholder Funds / Net Assets £11,530  £(8,699)
```

I'd be interested in what models exist to predict credit risk or bankruptcy likelihood based on this information. (I have other meta data available as well, such as industry and location, but I ignore that for the moment)

After researching for a while I found this paper by Altman http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.1968.tb00843.x/full He uses a method called Z-score that is the linear combination of five financial ratios. wikipedia Is this still widely used today? If not what are the alternatives?

## Answer by Karol J. Piczak (score 1)

https://quant.stackexchange.com/a/8158

You can start exploring the subject by having a look at Credit risk measurement: Developments over the last 20 years if only for the reference list. As a more modern approach an "upgraded" version of the original Z-score method was recently proposed by Altman: Z-Metrics™ Methodology For Estimating Company Credit.

Though be aware that despite numerous alternative methods being available (just search for discriminant analysis), most of the time you could describe the process as fitting a simple model to the available training/test data set. So the question you have to answer before all is about the appropriateness of the assumptions to your situation (analyzed universe, regime changes etc.). Quality of data is also an issue as already mentioned by @MattWolf.

## Answer by sets (score 1)

https://quant.stackexchange.com/a/8164

If you don’t have any market quotes, one possible way to assess the credit risk of an obligor is to use its financial statements. For instance, this paper describes the criteria that S&P use to derive the credit rating of a given obligor:

- Indicative credit ratings might be calculated using the following ratios: FFO/Debt, Debt/EBITDA and Debt/Capital.

- You also need to consider the business risk profile of the obligor (country & industry risk, competitive position, etc.)

Given its financial and business risk, a theoretical rating can be obtained using the matrix provided by S&P. Once you have the credit rating, to infer its credit risk you may:

- Compute the credit spread of bonds issued by companies with the same credit rating.

- Compute the historical default rates that have been observed for companies with the same rating (see S&P).

## Answer by geo_so (score 0)

https://quant.stackexchange.com/a/8161

You maybe want to have a look at this paper

Are Ratings the Worst Form of Credit Assessment Apart from All the Others?