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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 opleiding Klassikaal

Totale prijs *
Leden: € 530
Niet-leden: € 640
Partner BZB: € 530
Incompany: op maat, prijzen op aanvraag

* Heeft u recht op subsidies?
* Prijs: prestatie in het kader van permanente beroepsopleiding, vrijgesteld van BTW

Geef ons uw interesse door indien er geen datum beschikbaar is, de geplande datum voor u niet past en/of deze sessie volzet is. Van zodra een vijftal personen ingeschreven zijn op de interesselijst stellen wij u een nieuwe datum voor. Uw inschrijving op de interesselijst is kosteloos en zonder enige verplichting.

Schrijf u in op de interesselijst

Doelgroep

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

Vereiste voorkennis

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

Programma

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?

Methodologie

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.

Docenten

Tamar Joulia-Paris
Risk, finance & treasury