operational (58)

Using the ROC method to optimize controls

In the world of risk, analysts and managers alike try to reduce the likelihood of an event occurring by inserting controls between the event's driving factors and its outcome.

While the logic around this is sound, not all controls are equal and more often than not, some key risk indicators emit erroneous measures which mislead entire risk teams.
 
In this short post, we look at a method for weeding out erroneous control signals.
 
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ISO 31010 and Loss Modeling

One of the most concerning trends that continually persists in operational risk management, is the lack of interest from analysts to attempt to quantify this risk exposure coherently.

In this blog we look operational risk from the perspective of the normal and the extreme.

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Bow tie - Cause and Effect Analysis

There are several ways to look at operational risk but perhaps one of the most exciting and intuitive methods in use today is Cause-Effect Analysis.
 
In this short post, we look at how Cause-Effect Analysis works and we extend the bow tie concept further for measuring operational risk directly.
 
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14 techniques for modelling Loss Data

In general only a handful of businesses correctly capture Operational Risk Loss Data and of those that do, only a small number of risk units in these firms are modelling their risk data in a coherent manner. After a bit of research on the internet and in various other channels, it has become relatively apparent that there isn't a comprehensive list of potential models which can be uses for understanding Operational Risk. I would have expected an analyst somewhere at some point in time to have do

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The Loss Data Process

Building a loss reporting database for operational risk. What you need & links to some outstanding risk systems.

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.

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Monte Carlo and Loss Data

By looking at a case study in Monte Carlo and Loss Data, we are able to see how important it is to model loss experience and to categorise operational risk loss events.

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

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Frequency x Magnitude - the wrong measure

In the world of operational risk, there are a lot of analysts who believe that they can dimension the impacts from uncertainty by counting the number of events they experience over a period of time and then multiply that count by the average loss amount for the total event horizon they observe.

This approach for quantifying the impacts from uncertainty is full of error and it should be avoided. In fact, let's be clear, it is so fundamentally wrong as a measure of exposure that it isn't even a goo

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Heat Map Distortion

For most risk systems one big selling point is the heat map. It's tidy, it's colorful and in a macabre kind of way; it really energizes management to stare in ore at registered risks in the red zone.

Worthy or not, traditional heat maps distort risk reality, they squeeze risk into a two dimensional perspective that makes the reporting process itself as dangerous as it is useful.

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A question on measuring risk in manufacturing

Question : I have a situation in manufacturing operations where we have to take a judgmental decision on our equipment’s re-furbishing based on visual inspection.

It is a very crucial area of the business since it is part of the complex and risky Klinkerization process. In the short of it, we have to decide whether to replace brick lining which is critical for the survival of the equipment before the next shutdown and that is a year later.

Response : There are several ways I would go about dimensi
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How to use external data in operational risk

Four methods for using external data in a banks operational risk OpVar calculations the saga of external data continues.

Under Basel II operational risk Advanced Measurement Approach for quantifying operational risk losses, banks need to factor external loss data into their internal capital models. The argument is old and has been debated for years but this topic has resurfaced again among many financial institutions.

In this journal, we look at key practices for implementing external loss data in
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Building an Operational Risk System

There are stacks of operational risk reporting systems on the market however in general, many of these risk solutions are overpriced and unsophisticated programs. So why not build your own?

In this post, we look at building a risk modelling system from the ground up and believe me, it isn't as hard as you may think.

Please follow this link for the presentation
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What Cantaloupe and Citigroup has in Common

Two stories in the news recently have caught my eye: one involving a listeria outbreak caused by tainted cantaloupe, and the other involving Citigroup losing $285 million for defrauding investors.

In the cantaloupe story, the deadly, nationwide listeria outbreak was traced to a packing facility in Colorado operated by Jensen Farms, in which factors such as workers and trucks accidentally carrying the disease into the facility, and machinery being hard to sanitize created the environment in which

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I thought I would post a quick note about a recent blog post one of our clients wrote about their risk management initiative and the benefits it has brought.

In this post, the Head of Operational Risk talks about risk management becoming invisible in the organisation and the challenges of proving (to regulators) that risk management is been undertaken if indeed it does become invisible.

I think it is worth a read - http://www.hml.co.uk/blog/2011/09/23/risk-management-driving-value-from-a-long-game

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 PRESENTATION at this address : http://causalcapital.blogspot.com/2011/06/scenario-analysis-for-operational-risk.html

 

There appears to be a resurgence across the region for scenario analysis.  This interest to quantify extreme events seems to be motivated in part as an outcome from some of the banks looking to move their operational risk systems to a more advanced approach in Basel II.
 
While Basel-III's predecessor Basel-II doesn't require any changes to a banks operational risk framework, some
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Have you really got your companies operational risk framework in check? 


If you ask a risk analyst about their impression of their companies operational risk systems which, we have to admit is a relatively unframed question, it does seem to generate the typical responses that range between: We're totally sorted, It's kind of there and We are not really sure.

Very few people ask "is the operational risk process/system in check?"  

Then of course how do we know whether a company is good at measuring
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Cat Bonds and Catastrophe

In our first blog article on Catastrophe and Extreme Value Theory which can be found by clicking here, we looked at methods for predicting outcome probabilities for climatic events.

 

I promised that I was going to follow up with another article on how operational risk and catastrophes can be market traded, this new blog can be found here.

 

The ability to trade exposure from catastrophes or to allow insurance firms to securitise their underwritten risk is an important aspect of the insurance market

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This year has been particularly negative with respects to natural disasters and the humongous related impacts that obtrudes the lives and livelihoods of the communities affected. Considering we are only a couple of months into the year, the number of catastrophes that have struck various countries around the world is quite astonishing.
 
To list a few disasters alone, we saw Queensland which is normally a drought suffering state of Australia inundated with so much rain that mass flash flooding ens
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