Register for the AREA42 project meeting at ISC'2020, June 8-10, 2020, UCD, Dublin, Ireland

Dear Colleague,

We are involved with a new project in the field of B2B trade innovation which aims to start with pre-operational meetings from the beginning of 2020 onward and a first full organizational meeting in June 2020 at our ISC conference.

At this point in time we are seeking interested simulation, modelling, AI, Data experts to attend and take part in these meetings which will focus on:

Please indicate your interest by tagging the topic which is relevant to you and return your reply before FEBRUARY 10

New simulation environments for trade risk assessments models

For the last decades all trade related risks, should they be operational, financial, geopolitical were assessed based on documents certifying one representation of the reality at a given moment plus when possible historical data to build probability, actuarial models. Nowadays technology allows us to leverage on a bigger variety of datasets (think social media, supply chain, weather, payments etc) sometimes accessible instantaneously. Which simulation could you propose to build and test the next trade risk assessment and prediction model? How could we test the impact of new sources of data on trade event.

Discrete Simulation Modelling Techniques and Tools & Simulation and AI

As far as simulation modelling techniques are concerned, it would be interesting to find graphical approaches to trade simulation modelling. A neutral, graphical, transparent representation of a transaction would allow a better understanding and assessment of the trade risk. The system could automatically generate simulation programs based on trade parameters. Such projects would involve Process Flow, Visual Modeling, Visualization and Animation, Business Process Modeling. Such a tool would benefit all trade parties. It would help financiers and insurers to have an exact representation of the trade to offer the best solution. It will help traders/exporters/credit managers optimizing their trades and negotiate the solutions proposed.

AI and Neural Networks

Behavioural and neural analysis of trade decision makers, such as commodity traders or credit managers as a preliminary study to the build of a trade credit robo advisor - any technology mentioned can be used.

Agent-Based Simulation

Agent Based Simulation of payment behaviour in B2B commerce, an analysis per country, sector and level of digitization of the economy.

IoT & Industry 4.0

Due to the heterogeneity of these components and their interdependencies, it is urgent to find a simple way for fast IoT-generation that guarantees interoperability and reconfiguration. How could we identify and request access to relevant IOT sensors to support the risk assessment in a trade context? What are the current blocking points?

Simulation in Environment, Ecology and Marine Biology

How to assess and predict the environmental/biological/medical impact of a B2B trade? Which data / criteria should be taken into account to do so? How could we score and rank such impact for it to be taken into account in a procurement decision?

Other topics

Next to these specific ideations on modelling topics, some other ideas that we'd be interested to explore came to mind:

  • Current and future effects of climate change on socio economical dynamics on a country level / Country risk analysis. Spatio temporal analysis.
  • Current and future effects of climate change on corporate performance in different sectors.
  • Is there value in diversity of credit risk models or can one credit risk model capture it all?
  • Is there and can we quantify the influence of platformisation on payment behaviour? Hypothesis can be that Platformisation issues trust and will provoque different payment behaviour between customer and supplier.
    This would have a major influence on Credit insurance through platforms.
  • Can we apply self explaining Machine learning (AI) algorithms to credit risk modelling? Credit risk models suffer from the fact that they need to be explained to the regulator.
    Most of the AI algorithms remain rather black box and do not deliver the reason for the model outcome. In order for AI to enter fully into the credit risk modelling it needs to be self explaining?
    Could we create such models and what are the data requirements (volume and kind) and how do they perform with respect to traditional models.
  • Altman Z-Score in the age of real-time / open data marketplaces
  • Homomorphic encryption and distributed AI
  • Quantum risk modelling


If you would like to be involved in the project please fill in your relevant contact data

I am interested to cooperate in the field of:
[] New simulation environments for trade risk assessments models
[] Discrete Simulation Modelling Techniques and Tools & Simulation and AI
[] AI and Neural Networks
[] Agent-Based Simulation
[] IoT & Industry 4.0
[] Simulation in Environment, Ecology and Marine Biology
[] Other topics


First Name: __________________________________

Address 1:____________________________________

Address 2:____________________________________

Address 3:____________________________________






and adding in your cv and short text on your area of expertise

More info about AREA42 can be found here:

Please email back this form to



Philippe Geril, EUROSIS-ETI
European Simulation Office
Greenbridge Science Park
Ghent University - Ostend Campus
Wetenschapspark 1
Plassendale 1
B-8400 Ostend Belgium
Tel: OO32.59.255330

* Your Scientific information site on *
* Computer Simulation - Concurrent Engineering - Multimedia- Games *


**** DISCLAIMER ****

"This e-mail and any attachments thereto may contain information
which is confidential and/or protected by intellectual property
rights and are intended for the sole use of the recipient(s) named
Any use of the information contained herein (including, but not
limited to, total or partial reproduction, communication or
distribution in any form) by persons other than the designated
recipient(s) is prohibited.
If you have received this e-mail in error, please notify the sender
either by telephone or by e-mail and delete the material from any
Thank you for your cooperation."


This email is sent out to all those on the EUROSIS-ETI database.If
you want to be removed from this database or want to update your
address details, please send an email to