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Masterclass in Risk Management

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This year's Masterclass in Risk Management will be focussing on 'Updates & new challenges in non-financial risk management'. We will give you an update on talent risk, IT risk & data compromise and model risk. Speakers will be announced shortly.

Niveau Expert
Type de formation En classe

Prix total *
Membres: € 530
Non-membres: € 640
Partenaire BZB: € 530
Incompany: sur mesure, prix à la demande

* Avez-vous droit à des subventions?
* Prix : prestation dans le cadre du recyclage régulier, exonérée de TVA

Manifestez votre intérêt lorsqu’aucune date n’est disponible, la date planifiée ne convient pas et/ou la session existante est complète. Dès que 5 personnes sont inscrites sur la liste d'intérêt, nous vous proposons une nouvelle date. Votre inscription sur la liste d'intérêt est gratuite et n'induit aucune obligation.

Inscrivez-vous à la liste d'intérêt

Groupe cible

The masterclass is aimed at employees working in a risk department of a financial institution.

Connaissances préalables

Expert level: Subjects will be treated thouroughly. You should have knowledge of macro-economical concepts.


Talent risk:

It’s clear that the finance industry is struggling to attract, train and retain the best and brightest amid competition from other sectors such as technology. At the graduate recruitment level, senior risk managers have long warned the industry is struggling to attract the brightest and best quant finance grads in the face of increasing competition from technology firms. Why is this relevant for a risk manager? Does this mean a risk manager should focus on recruitment, selection, etc? You'll find out at the masterclass.

IT risk & data compromise:

IT disruptions – whether from a disabling cyber attack, or the more mundane causes of human error or failure of aging hardware – are considered the top threat to financial services firms for 2018 by senior operational risk practitioners. Guarding against known risks such as DDoS is a given. What worries us more are the harder-to-measure disruptive threats – cyber and physical – to their firm’s networks. Malware, employee error and plain old hardware failure can be just as crippling when it comes to a loss of operational functionality.

Key note - Model risk: Machine learning vs increased regulatory initiatives

According to a survey from risk.net, model risk is one of the top 10 risks in 2018 - a reflection of the growing regulatory burdens placed on banks’ modelling and validation teams in a number of key jurisdictions. It also hints at the potential cost of errors should banks make a mistake.
The perceived rise in model risk among banks comes at a time when banks' freedom to use internal models to calculate regulatory capital is set to be severely curtailed under Basel III – which partially floors model outputs to capital numbers achieved using a standardized approach – or removed completely in the case of Pillar 1 calculations for operational risk.

Fact is that decision taking is going to be almost completely automated based on big data / artificial intelligence. What are the risks of a model of automated decisions? What are the risks connected to data analytics?


During our theoretical training courses we offer a combination of theory and practical exercises. The cases, examples and exercises are taken from everyday situations or are contributed by you and then solved under the guidance of the trainer.


Tamar Joulia-Paris
Risk, finance & treasury