Research

Introduction

Elseware is involved in applied research since its creation.
Patrick Naim and Laurent Condamin were among the pionneers of application of neural networks [1] and bayesian networks ([5], [6]) in the financial sector [2] [3], back in the nineties, with applications in credit scoring, trading, and asset allocation.
When we started working on operational risk in 2005, we proposed the structured scenario approach XOI at a time when the mainstream approach was focusing on Loss Distribution Approach.
This approach was first described in a general risk management book[4], and then specialised for Operational Risk Modelling in the Financial Services[7].
Today, our main subjects of research are modelling cyber risk and modelling climate stress on financial business and risk.

Modelling Cyber Risks

Cyber risk is perceived as one of the top risks by the business community. It is consistently among the top 5 risks according to the World Economic Forum from 2017 to 2019. According to Risk.net, cyber risk is the number one operational risk.

Our research aims to model this risk for financial institutions in order to assess its cost. The approach is collaborative in order to reduce the subjectivity of the modeling.
This research is based on a specific set of models based on the XOI approach (The Cyber Risk Wheel, see below) and and has been awarded the best industry initiative by risk.net in 2020.

It has also contributed to the Cyber risk workshop held by the Federal Reserve of Richmond in November 2019.

Modelling Climate Risk

Climate change is a specific example of systemic environmental risks (S&E) that also include biodiversity loss or pandemics.
These risks share a number of characteristics that need to be considered when designing a risk assessment framework:
  • Horizon: The time horizon of S&E risk analysis is much longer than the usual time horizon of economic or financial risk analysis.
  • Forward-looking: Modelling cannot be based on historical data.
  • Systemic impact: S&E risks are systemic by nature.
  • Nature of knowledge: S&E risks are not in the usual expertise of financial institutions, and the study of their relationship with the economy is recent.
Our research relies on four blocks:
  • Scenario: Assessment of economic and physical consequences of climate change (external knowledge).
  • Stress: Assessment of the physical and transition impact on one considered «segment» of the business, modulated by the segment sensitivity.
  • Aggregation: Integration of segment impacts.
  • Response: Mitigation response of the firm (including reallocation of segments).
This approach assumes the definition of relevant «segments». This is dependent on the firm and of its maturity. We recommend a top-down approach for the definition of segments.

To learn how our solutions and the XOI method can help you assess operational risks, contact us

Contact us

About us inmail

About us

New York

1375 Broadway,
suite 504,
New York, NY

Paris

85 rue Edouard Vaillant
92300, Levallois Perret
Paris, FR