What a Strong Risk Manager Should First Care About!

Risk Management is become a key business discipline in any large organization and particularly in Financial Institutions; the 2008 financial crisis largely shed light on this discipline and prompted companies to massively strengthen their Risk and Compliance departments in order to cope with regulatory requirements and prevent another financial crisis. Independently from the Risk area you want to specialize, i.e. Market Risk, Credit Risk, or Operational Risk, a successful Risk Manager will never earn credibility among a well-informed audience though speechifying, but by a clear and precise message sustain by a robust data set, this can be achieved by paying a particular attention to the following:

  • Be obsessed by data-quality: Modeling using an irrelevant data set or with an incomplete range of data will always lead you to have a contested outcome. If the Risk Manager cannot directly improve the quality of data, he should nevertheless spend some time on cleaning and reorganizing figures; the Risk-Manager must perfectly be aware on how the model will be impacted by low quality data, and explain the implications to the audience ;
  • Think “automation”:  Processes that can be automatized must be automatized, it does not necessarily mean using complex coding, but sometimes just using basic codes or formulas. Every “manual” action undeniably increases the Operational Risk, i.e. a badly performed copy/paste leads to a wrong model output and consequently to wrong conclusions ;
  • Keep it simple: It is not always required to build very advanced models to supervise Risk; most of checks can be performed through simplistic tools. If the supervision requires advanced modeling, it is always good to apply a second layer of basic controls on the model, abnormal figures may translate technical issues and not effective Risk breaches ;
  • Always back-test / stress-test: Regular back-testing and stress-testing should be performed to ratify the model validity; it is very common that the model robustness changes across time ;
  • Care about statistics: If the output should be presented to colleagues or counterparties, keep focusing on the core information, while clearly defining assumptions. If the output produced by a Risk Manager is an automobile, statistics are the outer finishing; you must be confident about the mechanics, but don’t feel obliged to show the entire engine to the audience, they rather care about the design and how fast is the vehicle.

The above list is clearly not exhaustive, but it enables the Risk Manager to share his output with confidence, and will undeniably facilitate the discussion with internal and external counterparties.



Consider as much the Manager as the Job!

People often are considering a wide spectrum of aspects when looking for a new opportunity (i.e. title, remuneration, work-life balance, etc.), but sometimes are minimizing - or even not considering at all - one of the most important question they should ask themselves: “Will I enjoy working with my future manager? ”.

It can be challenging making an opinion on someone after only a few interviews; but I am convinced that the first impression is important, and that you can learn a lot about the comportment of a person or his global professional or academic knowledge just in a couple of hours.

In my opinion, you can already get a reliable idea of what a person is - or is not - by asking yourselves the two following questions:

  • What could my future manager bring me? The more Senior you are, the more you are expected to bring added value to your future employer (or at least this should be the case), but this assertion is also true the other way round; as for a Junior roles - and even if needs are not the same - you still are expecting your manager to share with you some knowledge (i.e. about the organisational structure), connections, etc. During the interview process, you can easily grasp how smart is your interlocutor and how he is inclined to share with you his knowledge. If you get the feeling that the person won’t or isn’t willing to share with you, you can conclude that this is not the right place for you. If the first feeling after leaving the interview is “Wow, this guy is impressive; I really learned a lot”, this is already a good start.
  • Would I be happy to work with that person on a daily basis? It is important trying to assess the personality of your interlocutor despite that it can be tough to answer this question after a brief interview; inter alia because people can easily simulate and show some aspects of their personality not representative of their real character during the interview. In case of any doubt it is always better not considering the job opportunity anymore.

Since the perfection is not attainable, do not expect your manager to be perfect, but it is better to avoid starting a new collaboration with the feeling “I have to make do with what I get”; bear in mind that a good manager is one of the most valuable aspect you can expect from your new job.

Whatever the reasons leading you to leave your current job, if you believe that your future manager will not meet your expectations, wait for another opportunity. If many aspects can be renegotiated when you are in your new work environment, do not expect changing how your manager is or how he behaves.

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Dealing with Behavioural Standardization!

In application of statistics such as modeling, standardization is defined as adjusting different values to a common scale; normalization of scores – i.e. aligning distributions to a normal distribution – is a typical standardization process. From an organizational perspective, a traditional Fordist system of mass production can define a standardization process; in other words, uniformizing tasks. I would like to dedicate this post to another type of standardization process, a phenomenon that can be observed in most large organization, the behavioral standardization. 

A wrong corporate culture - as defined by the Deal and Kennedy culture framework - is not optimal to support the organization’s activities; a potential outcome of an inadequate culture can be inciting employees to adopt smooth attitudes in line with their workplace, avoiding to put themselves at risk by expressing their opinion. Behavioral standardization is often a creeping phenomenon; there is not necessarily a stated desire coming from the employee or derived from the working environment to modify the employee attitude, but some tricks exist to fight behavioral standardization and to avoid falling into this trap:

  • Embrace opinions and keep interpreting advices: Colleagues’ opinions are valuable because you do keep your free will at the end; but remain vigilant with recommendations, particularly those concerning behavioral aspects; bear in mind that people may be tempted that you behave as they would do;
  • Find a model, but do not mimic it: It can be constructive to copying some behaviors or attitudes of people that one takes as example; but do never mimic that person. Bear in mind that the success of one person depends on a wide spectrum of criteria (e.g. academic and professional experiences, seniority, luck, etc.), only your own traits can make you successful;
  • Keep in mind that internal assessments are subjective: Internal assessments are originally made to improve your skills and competencies; this exercise can nevertheless easily derive to make you come into a shape. In my opinion, those assessments are valuable for quantitative assessments - e.g. the quantity and the quality of the work you have been through - not for qualitative ones; this is then your responsibility to interpret those assessments.

Employees not afraid of expressing their opinions in a constructive way are those that create a tangible added value for any organization. If you have been hired for a role, this is because your employer is convinced that you can perform the job; but you really can distinguish yourself from the competition by bringing new ideas an implementing them, and this can only be performed through your own personality. While remaining respectful and humble, do never try to normalize your traits, this is what really makes you unique.


Don't Make Rushed Decisions, Analyse!

The differentiation between problem-finding and problem-solving has widely been discussed in the modern literature of Corporate Governance; but past experiences led me to observe that people often are more concerned about providing a solution to a detected “anomaly” than lucidly identifying and understanding the underlying reasons of the problematic. I would like to prove within this post that detecting an anomaly is as decisive - if not more - as finding a remedy.


Let’s start with a basic illustration; as a Risk analyst, you are in charge of managing and supervising a market risk tool assessing the overall volatility of a portfolio of securities. The purpose of the tool is generating an alert when an internal threshold is breached; the model is highly sensitive to the intra-day market volatility. Someday, the bankrupt of a major institution generates whipsaw effects of financial markets, leading the model’s threshold to be breached. You can act as follows:

  • You produce statistics about the breach that you report to the line management;
  • You don’t report anything and contact the Investment Manager in order that securities with the higher marginal contributions are excluded from the portfolio;
  • You adjust the model parameters in order that the tolerance level increases and no breach is reported;
  • You don’t care, the model is just ornamental purpose.

Amid those possibilities, there is - according to me - one optimal decision, the first one. The last choice can be pushed aside; there are no advantages of managing a model that is purposeless. The second option leads the Risk analyst to transfer its oversight responsibility to another department and to minimize its analysis capabilities, this option is then suboptimal. The third option is an easy way to avoid short-term complication; because the bankrupt of a major Institution is an extreme event, you can expect this phenomenon not to be repetitive. We then keep the solution one, where the analyst reports and evaluates the anomaly. Please find below some thoughts on why I think this option is the best one:

  • You give yourself a larger time-period to perform an in-depth portfolio analysis; you then have the opportunity to analyse how the model works not only when an extreme event occurs, but also several days prior and post occurrence;
  • You can analyse the marginal contribution of each portfolio securities; this is a common pitfall to only consider what is the most visible and has the highest marginal effect, and moderate other effects;
  • You leave a room to the line management to make decisions; for instance about the model validity, or the significance to attribute to the event;
  • You understand how the model can/could be fine-tuned; by asking yourself: Are we happy with the current model? Could specific parameters be added to the model to make it more reliable in case of future similar events?

With this post, I want to spot that abnormalities detection requires more than just acting in order that things become normalized. Extreme values should be seen as an opportunity to ask ourselves WHY they occurred, WHAT precisely generated them, and HOW - if needed - could processes/models be improved.  

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