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We have brought together more than 15 years of research and fieldexperience to construct our MSTAR products.

Our forward-looking methodology for modelling operational risk scenarios is used by some of the world's leading financial institutions to assess their key risks for regulatory and risk management purposes.

MSTAR Desktop

The implementation of Exposure, Occurrence and Impact Method for structured risk scenario assessment.

Working with traders exposes a firm to rogue trading; selling products exposes a firm to mis-selling and to anti-competitive practices; operating in buildings exposes a firm to natural disasters or terrorist attacks. From this point of view, operational risk is exposure based.
The design of a loss generation mechanism for a given scenario starts by identifying the Exposure for a scenario, i.e. the resources of the firm exposed to the event considered.
A scenario is then fully defined by the resource (Exposure), the event (Occurrence), and the consequences (Impact).
MSTAR Desktop implements the XOI method and allows to you to design and quantify your own scenarios.
Design and quantification are kept independent in order to allow independent quantification in different legal entities or business units.
The distribution of potential losses are calculated using simulation. Scenarios can be tested for what-if analyses, and aggregated with various correlation methods (causal dependencies, copulas, etc.)

The main features of MSTAR are as follows:
  • Design: create the causal graph that links risk drivers to exposure, occurrence and impact.
  • Quantification: evaluate the distribution of each driver, based on data or expert judgment.
  • Simulation: sample all drivers in the scenario to assess the distribution of the scenario potential impact.
  • What-if analysis: test alternatives on key drivers - stress-testing or risk mitigation.
  • Aggregation: assess interdependencies between scenarios and simulate enterprise-wide risk.

MSTAR can also generate simulation scripts in Python, R or Matlab to integrate scenarios into external applications.

MSTAR Platform

Be informed of what happened. Understand what could happen.

The MSTAR platform gives you access to a comprehensive library of operational risk scenarios exposure models and to a free news feed of operational risk news.
The MSTAR platform also exists as a peer platform hosted by trusted third parties to help you benchmark your scenario assessments.
The first MSTAR Peer platform hosted by American Bankers Association is online.
The MSTAR platform offers two main features:
  • A newsfeed on events related to operational risk (loss events, reports).
  • A library of 36 scenarios in the areas of Conduct, Cyber, Internal Fraud, External Fraud, Error, Disruption, Legal.

The news are collected from official websites of regulators around the world, and also from press sources.
Access to the news feed is free of charge, provided that you have registered.
Each time a news is published, it is, if possible, linked to a scenario in our library.
This allows you to link the news with our analysis of each scenario and to understand the drivers of the risk that has just occurred.

The scenarios contained in the MSTAR library are the result of our research with financial institutions.
All scenarios have been simplified and stylized to make them relevant to all financial institutions that consider themselves exposed.
All scenarios are quantified, and there are 2 categories of drivers used for quantification.

Drivers of the first category are assessed independently of the bank, such as:
  • The probability of an earthquake, or the probability of human error, which are based on external studies.
  • The probability of a bank card compromise at a major retailer, which we calculate from historical data.
  • The fraction of undue revenue a bank has to disgorge in case of mis-selling, which will be based on the analysis of actual cases.
The second category of drivers is bank-specific, such as:
  • The number of derivative or futures traders,
  • The geographical location of the main headquarters or data centers.
In the MSTAR library:
  • The first type of drivers is quantified with all the relevant justifications and sources
  • The second type of drivers is quantified for an illustrative bank called MSTAR Bank. Consult the Operational Risk Exposures Report of MSTAR bank.
A bank quantifying the scenario for itself will need to evaluate the drivers in the second category only.

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

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