Category: Credit Rating Methodologies

How BigData can be useful for risk analysis

How BigData can be useful for risk analysis

In last one/two years, there has been an increasing discussion about Big Data and how people can exploit it efficiently to improve their own models.

We in modefinance can say that we love Big Data (more than 300 millions of companies rating and all the 65'000 worldwide Banks ratings) and we deal with credit risk analysis, practically assign the credit rating to all companies around the world. But how do we use the Big Data in our work?

The answer is with caution! Now I will try to explain briefly why!

Valentino Pediroda, the one who's behind this article, teaches Fundamentals of Numerical Design at the University of Trieste and I also developed numerical models that can help engineers improve their products. Among the methods that I taught (and I continue to develop) there are all machine learning and Artificial Intelligence methods. Here one example:


In a nutshell and a simplistic way: these methods that learn from the data given to divide them into categories (look at the figure 1). 

Basically, the Machine Learning/Artificial Intelligence model creates the blue line to separate the green circles from red squares (circles and squares are our data).

If you think that the squares are companies that failed historically and the circles are healthy businesses, one could say that the Machine Learning is just right model for you: you have practically created a mathematical model that separates companies from healthy ones from not healthy ones!


But there is one big problem: you have to have a COMPLETE database in your own hands, that is; you have to be able to know the whole universe, both healthy companies and companies which went bankrupt. And here come big problems: in Italy, thanks to the very efficient work of Chambers of Commerce and Companies’ Registry, we have this database, also in some European countries (such as France, Spain and UK), but outside of Europe? 

Absolutely missing: Machine Learning therefore will be fine for Italy and a few other countries, but it absolutely is not suitable for all over the world! Well then it is a problem!

Can we say Big Data does not serve in our field, so that modefinance should not use the huge amount of data held? No, Big Data is fundamental and modefinance uses it daily, but with caution: using them to understand the economic environment in which a company operates (a service company in India operates in a completely different environment from an Italian industrial enterprise) is one thing, but exploiting the Big Data DIRECTLY to build the evaluation model is another thing which we modefinance find particularly dangerous.

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