Concentration Risk

The quantification of Credit Risk has both normal and stressed modes of measurement, just as all measures of risk do. However, when an analyst attempts to quantify stress in credit portfolios, they should attempt to dimension the concentration risk aspects of their portfolio in line with the stress test they have in mind.

  

In this blog post we look at the stress testing aspects around concentration risk and a presentation has also been attached to the end of this journal which can be downloaded. This presentation investigates standard and accepted practices for measuring concentration risk in credit portfolios.

Modelling Loss Data

In our previous post on Loss Event Data, we discussed the types of fields and specific risk framework elements that need to be in place for a best practice Loss Data Repository and you can follow this [Link] for a recap. In this third series on the Loss Data Monte Carlo debate (this is turning into a bit of a tome on data modelling), we take look at the types of techniques that can be used for understanding Operational Risk Loss Data better.

  

There are 14 key models that have been listed in this post and brief summaries, as well as the purpose for each model has been supplied within.

The Loss Data Process

In our last blog posting on Monte Carlo and Loss Data we described the importance of the Loss Data exercise. A few people have personally emailed me asking for more information on this aspect of risk management, so I have decided to write a blog post on it.
  

I will be posting two articles on the risk function around loss data specifically. In this post we look at what comprises a Loss Database and the event management process for administering Loss Data itself.  In a second posting, I will describe the types of statistical models we can use to carry out analysis of the data we capture in our Loss Data repository.

ISO 31000 for banks

ISO 31000 is a risk management standard that provides generic guidelines for the design and operation of an enterprise risk management framework. Released in 2009 by the ISO standards board, the standard itself has been crafted in such a manner that it makes ISO applicable for any organisation type. Theoretically banks to manufacturing firms can benefit from implementing ISO 31000.

What we are exploring in brief today is: Should the banking sector entertain ISO 31000 when it already has an established global risk standard of its own?

The presentation for this posting can be found by following this [link]

Monte Carlo and Loss Data

Recently I had a discussion on modelling risk with a fantastic and successful business person who said to me : "I have read about Monte Carlo, you even make mention to it on your blog but it doesn't make great sense to me. The maths in Monte Carlo is even worse because it seems to confuse the concept by taking it into an academic place that most people aren't from.

Is it possible to explain Monte Carlo by using a tool we all understand such as Microsoft Excel?"

So be it, this blog posting is an Excel example of Monte Carlo and Loss Data. Due to the size of the post, it will be separated into two, possibly three updates.