The metarisk series (II), risk (bad) behaviour

 

Now that we agree on what is a more accurate risk definition, so behind the name there is a meaning, let’s try to deep dive on risks features. We know that in a very simplistic way all the risks a combination of likelihood and impact, you can apply that to a security breach, a compliance risk with the last regulation or to the risk of running out of battery in your smartphone before coming back home. Probably we all agree that there are many kind of risks, for instance many risk managers split between financial and non-financial ones, which may make us wonder what is the impact for a business if there is no financial impact, but let’s assume that it’s a way to separate different risks and activities. In the same way than operational risk and information risk are different branches of the same thing, it is just a way of specialization, so we deal with the complexity of each category in a better way.

So looking at the risk categories we may argue for eons about how many are there and each department should use to keep his activities under control. Risk categories are not that interesting to me so I will assume that we have the right list and no elephant is missing in your assessment. Let’s talk instead about risk behaviour, to understand this attribute we need to think twice about the impact  that this risk is creating to me. Let’s see some examples:

Case 1: Customer calls lost per minute waiting in the call centre:

This seems quite linear… so the more minutes, the more customer calls lost. Ok, no rocket-science.

Case 2: Financial penalties per low, medium and high deviations with a regulation (you name it).

Well now the picture is changing… is this a ladder? Do we have thresholds?

Case 3: Nº of servers unavailable until service lost… or Russian roulette:

This is kind of binary risk. I guess that Taleb put the example of the turkey in a Thanksgiving day. 0 risk for 364 days, happy life, all is sweet until we reach the ‘breaking’ point…

Case 4: Earthquakes:

Frequency (earthquakes x year) Vs Intensity (Ritcher scale), just in case that my drawing is not clear, this is logarithmic.

Case 5: Millions (€) lost per day with payment services down or…  Impact of an undetected security breach in a core banking systems per day or… The the wheat and chessboard problem (or how a King lost his kingdom).

This is an interesting one and is based on a geometric progression. Red line represents the bankrupt point. By the way, if you don’t remember the wheat fable just a picture to visualise it:

Case 6: Impact of personal data breach (millions of records x millions of €, 62% variance).

In the real world there is a myriad of scenarios, probabilities and potential outcomes so this risk behaviour seems quite ‘natural’, it’s a geometric dispersion. What does it mean exactly? It’s just that there is an infinite number of scenarios that may happen, in many of them we are out of business or death or we just fail in achieve whatever we want. It depends on the risk, the important thing is to know the limits and to recognise this pattern in whatever we are measuring / analysing / giving a professional judgement.

Case 7: Risk correlation

Risk C (yellow) as exponential combination of Risk A and B. Increase in inflation > 3%, increase in unemployment and poverty rate.

Ahhh, this is easy, you may think. It’s clear that there are interdependencies in some cases, we live in a complex world after all.

Citrigroup CEO (January 2008):

“Our financial results this quarter are clearly unacceptable. Our poor performance was driven primarily by two factors significant write-downs and losses on our sub-prime direct exposures in fixed income markets, and a large increase in credit costs in our U.S. consumer loan portfolio”.

The sub-prime crisis is a great example of how correlations may be missing (or hidden by greed) sometimes.

Case 8: 30 years mortgage earnings or expected loss in case of customer bankruptcy in the first 5 years (risk upside):

Yes, i know that this should not be here, but there are many risk managers that like to see to the ‘upside’ or the benefits of certain risks, this happens specially in the portfolio management or taking some investing decisions. Investors & traders should look usually at the risk asymmetry, so there is much more upside than downside in whatever they invest on (commodities, securities, etc.). Potentially, any company or country may go bankrupt, actually the lifespan of SP500 companies is getting smaller. 

I don’t agree that we should talk about ‘positive’ risk within ‘risk management’ functions, these functions are designed to deal and prevent risks, impacts, anything that may jeopardise the business. But business or intelligence departments may put the opportunities next to the impacts of business decisions, knowing that they have to look at them to keep the risk under control. Risks and opportunities (benefits) are everyday occurrences of laypeople, as discussed in the previous post there is a potential risk and benefit in almost any activity and we are wired to deal with it. However, it's of the uttermost importance to remember that the asymmetry between the risk and benefit shall be considered and measured (the more important the decision, the more accurate the assessment).

Risk properties summary:

Know that we know a little bit more about risks lets recap:

·      Events with one or more occurrences, with several causes and several consequences.

·       Risks are events with a likelihood.

·       They happen in the future, not in the past.

·       Depending on the behaviour of the risk, the events have an Impact:

o   Linear.

o   Binary.

o   Ladder scale.

o   Logarithmic.

o   Geometric progression.

o   Geometric dispersion.

o   Etc.

·       Risks are independent or correlated.

·     Risk and benefits are asymmetric and we need to analyse that (if they are symmetric, where is the business?

And yes, they may be grouped in categories as a way to specialise and deal with them within public or private organizations.

Now that we settled the foundations of what risk is and what do we mean when we talk about likelihood, impact or behaviour, we can start to talk about the metarisk, so the risk of risk functions getting this wrong.

https://todoesseguro.blogspot.com/2022/01/the-metarisk-series-i-can-we-agree-on.html

https://todoesseguro.blogspot.com/2022/01/the-metarisk-series-ii-risk-bad.html

The metarisk series (I), can we agree on what is risk?

This is the first of a series of articles about “metarisk” and probably it would help to start with a small definition of what this thing is about. No, this is not related with social networks and if you arrived here looking for that you can continue your search (maybe another day we can talk about that). At least in the IT Security community the buzzword ‘meta’ is well-known since many years ago, we use it to describe the data within Office documents and we find this ‘metadata’ with the glorious FOCA, the queen of metadata (congrats to those developers!). Then we have a little piece of software called Metasploit, probably it rings a bell to you too. This list may continue for a while...

Saying this, what is the Metarisk? If we follow the structure of thinking of other definitions, it’s the data about risk, just it. But this and next posts we are going to look at that from a slightly different angle, let’s talk about the risk of not reading / understanding the data about risk that we have. That’s a risk that face not business processes but, in particular, risk management departments such as those present from the 1^st to the 3^rd line of defence of the existing industries. Of course, external auditors or regulators are special guests in this journey.

As years go by and experience starts to flourish, there are certain patterns, errors, pitfalls or whatever you prefer to call them that repeat everywhere. In this series I try to present them and give some light on the many mistakes we all can make in our everyday job within risk departments. For the sake of the discussion I will provide the example of an internal audit department (so 3^rd line), but you can replicate / adjust the patterns in your favourite risk management department.

“The first principle is that you must not fool yourself, and you are the easiest person to fool”.

Richard P. Feynman

 The basics

“The internal audit activity must evaluate and contribute to the improvement of the organization’s governance, risk management, and control processes using a systematic, disciplined, and risk-based approach. Internal audit credibility and value are enhanced when auditors are proactive and their evaluations offer new insights and consider future impact”.

IIA – 2100 (Nature of work)

So, let’s start from the very beginning… What are we talking about when we talk about risk? Well, as apprentices in the matter let’s check what the experts have to say:

Institute of Internal Auditors

“The possibility of an event occurring that will have an impact on the achievement of objectives. Risk is measured in terms of impact and likelihood”.

ISO 31000: Risk Management

“The effect of uncertainty on objectives.”

Project Management Institute

“An uncertain event or condition that, if it occurs, has a positive or negative effect on a project’s objectives”

WordReference

1. dangerous chance.
2. the chance of loss.

3. to put or place someone or oneself near the chance of injury or danger.
4. to take the chance of;

      to hazard.

Crystal clear, isn’t it? As per the different definitions, risks share these attributes:

-      Risks happen in the future.

-      Risks produce damage (destruction that reduces value) or opportunity (¿?).

-      Risks are random (they happen, but we don’t know when and where). There is uncertainty around risks.

Here the challenge to the PMI folks (and whoever agrees with their definition) would be the following: There is nothing such a good outcome from risks, otherwise they would not be risks. It’s when the risk does not materalise or it has such a low impact that it’s meaningless when the good outcome arrives. So just in case that there were doubts, ‘risk departments’ are there to prevent risks mainly (that may feed other opportunities and value gains, but that’s not the focus of this post).

The associated formula for calculating risk is:

 R = (probability of the accident occurring) x (expected loss in case of the accident)

But we know that there is no 1 to 1 relation between risks and activities, so what we are actually talking about is the following:

So that is our starting point. To put it in simple-plain words:

 

We just may just have an idea of the how …But we don’t know when.

And considering the Risk definition… How do human beings deal with things that are random, happen in the future and produce damage?

Let’s think about it…

While playing…

Ok, enough sarcasm. I don’t wanna be pesimistic, we are wired to deal with risks, aren’t we?

Then, why all the fuss? Well, even if we are well wired & prepared to deal with risk, that doesn’t mean that our history with risk is a complete success. Understanding, preventing and dealing with risk is a continuous process that may waste a lot of our brainpower because there is no single risk-free decision that human beings can take:

•       If you drink coffee or water.

•       If you buy another t-shirt or save the money.

•       If you call your mother / father once per day, once per month or never.

•       If you take the bike or the bus, even better, if you work from home (always).

•       If you answer that e-mail at 19:00 p.m. or the next day.

•       If you go to the gym or practice sports outdoor.

•       If you go on holidays to Seville or Milan (the 17^th of February 2020).

•       If you buy your son that toy or that video game.

•       If you use facemask in the street or not.

•       If you read this post or tun the TV on.

Even thinking that something is a ‘zero-risk’ event / activity is a well-known BIAS (quite common I would say).

So, to get this thing called risk under control big players / companies define three lines of defense, Governments create public agencies, national security forces (dozens of them and usually independent but reporting to the top-level politician elected every X years, or not). That should increase our chances of success, of preventing impacts, of progress…

Well, at least that is what we all try to accomplish. Sometimes with more success than others.

Risks could be very simple or extremely complex to deal with. Many times, the higher is the goal, the biggest is the risk and our success is determined for how can break this formula. To be more clear, we gain value when we are able to achieve higher (more complex, more difficult) goals, objectives while keeping the risk ‘under control’. Let’s try to visualize it with a few images:

I hope that you follow me so far. Coming back to our favourite formula, it’s a way to say that the result may grow (exponentially) and sabotage our attempts to obtain something:

So, the risks of one single activity are an addition of all the things that may go wrong in that activity. As processes may have up to N activities, each step has it's own risks and interdependencies. So when we look at high level the impacts, on the contrary to the risk, may scale to unforeseen levels. 

In any case these statements are simplifications for the sake of the discussion, just to set a common foundation. Then we may wonder if all the risks are the same and where do we go exactly with this 'risk for dummies' article. It is so obvious, is it? We will talk about it in the part 2…