Managing Risk to Reputation - a Model to Monitor the Key Drivers a Key to Long Term Solvency for Insurance and Reinsurance Companies.
Managing Risk to Reputation - A model to monitor the key drivers A key to long term solvency for insurance and reinsurance companies.
April 29, 2011
ABSTRACT: Reputation is an intangible asset that directly affects the market value of the firm. A good reputation evidences belief that the firm is on a sustainable course. Reputation is built on the trust established with all stakeholders through past behaviour. Reputation may prove more resilient that one might think, yet even minor misconducts, if repeated, can lead to downfall. The foundation of reputation management and of all the risks associated with it, whether upside or downside, can be summarised in one word: authenticity. We propose an operational model to define, measure and monitor the nine key drivers of authenticity, classified in three categories:
Intentions : Vision/promises to partners, CSR Profile, Human capital; Actions : Leadership/governance, outreach, operations; Results : Sector profile, Regulatory profile, finance and value.
The model presented here proposes metrics for each driver by aggregating data gathered by different methods. The combination of the different driver values is conducted through multi criteria analysis based on fuzzy measure, to ensure that the resulting index preserves all the information contained in the data. The process itself, and the result it delivers, is ideally guided by experts outside the enterprise, to ensure inter-organisational comparability. The process reveals threats and opportunities through iteration, and establishes a framework for understanding risks to reputation. Any Enterprise Risk Management (ERM) project that does not include risks to reputation ignores a meta-risk and is incomplete and invalid. KEY WORDS: Cindynics, Expectations, Opportunity, Perception, Reputation, Risk, Stakeholders, Threat, Trust, MACBETH method, Multicriteria decision aiding, Interacting criteria, Fuzzy logic, Choquet integral.
1
Introduction
Warren Buffett (Chairman
April 29, 2011
ABSTRACT: Reputation is an intangible asset that directly affects the market value of the firm. A good reputation evidences belief that the firm is on a sustainable course. Reputation is built on the trust established with all stakeholders through past behaviour. Reputation may prove more resilient that one might think, yet even minor misconducts, if repeated, can lead to downfall. The foundation of reputation management and of all the risks associated with it, whether upside or downside, can be summarised in one word: authenticity. We propose an operational model to define, measure and monitor the nine key drivers of authenticity, classified in three categories:
Intentions : Vision/promises to partners, CSR Profile, Human capital; Actions : Leadership/governance, outreach, operations; Results : Sector profile, Regulatory profile, finance and value.
The model presented here proposes metrics for each driver by aggregating data gathered by different methods. The combination of the different driver values is conducted through multi criteria analysis based on fuzzy measure, to ensure that the resulting index preserves all the information contained in the data. The process itself, and the result it delivers, is ideally guided by experts outside the enterprise, to ensure inter-organisational comparability. The process reveals threats and opportunities through iteration, and establishes a framework for understanding risks to reputation. Any Enterprise Risk Management (ERM) project that does not include risks to reputation ignores a meta-risk and is incomplete and invalid. KEY WORDS: Cindynics, Expectations, Opportunity, Perception, Reputation, Risk, Stakeholders, Threat, Trust, MACBETH method, Multicriteria decision aiding, Interacting criteria, Fuzzy logic, Choquet integral.
1
Introduction
Warren Buffett (Chairman
References: © April 29, 2011 Decision matrix © April 29, 2011 informations are translated in the following set of constraints (see tab.11) include veto on a criterion