TY  - BOOK
AU  - Soprano,Aldo
TI  - Measuring operational and reputational risk: a practitioner's approach 
T2  - Wiley finance series
SN  - 9780470517703
AV  - HD61 .M428 2009
PY  - 2009///]
CY  - Chichester, England, Hoboken, NJ
PB  - Wiley
KW  - Risk management
KW  - Risk assessment
KW  - Operational risk
KW  - Corporate image
N1  - Includes bibliographical references (pages [193]-200) and index;  Table Of Contents; Foreword (Andrea Sironi); Preface; Acknowledgments; 1 The Development of ORM in UniCredit Group; 1.1 A brief history of a fast-growing group; 1.2 Creating a new function; 1.3 Developing the new control system; 1.4 Challenges in the early stages; 1.5 Methodology to measure operational risk; 1.6 Training and internal communication focus; 1.7 International regulatory challenges; 1.8 Reputational risk management; 2 The Calculation Dataset; 2.1 Definitions; 2.2 Rules of thumb; 2.3 Internal loss data; 2.3.1 Business line mapping; 2.3.2 Event type classifications; 2.3.3 Data quality analysis; 2.3.4 Special cases; 2.4 Minimum loss threshold; 2.5 External data; 2.5.1 Public or external data sources; 2.5.2 Consortium data; 2.5.3 Scenario data; 2.6 Business environment and internal control factors; 2.7 Scenarios; 2.8 Insurance information; 2.9 Scaling data; 2.10 The Unicredit Group Operational Risk database Evolution; 2.11 Final considerations; 3 Loss Distribution Approaches; 3.1 Calculation dataset building; 3.1.1 Internal calculation dataset; 3.1.2 External calculation dataset; 3.1.3 Scenario-generated calculation dataset; 3.1.4 Risk indicators calculation dataset; 3.2 General LDA framework; 3.3 Operational risk classes; 3.3.1 Identically distributed risk classes; 3.3.2 Inflation adjustment; 3.3.3 Data independence; 3.4 Parametric estimation and goodness-of-fit Techniques; 3.4.1 Severity distributions; 3.4.2 Graphical methods; 3.4.3 Analytical methods; 3.4.4 Frequency distributions; 3.5 Applying extreme value theory; 3.6 g-and-h distribution theory; 3.7 Calculating operational capital at risk; 3.7.1 Loss severity distribution; 3.7.2 Loss frequency distribution; 3.7.3 Annual loss distribution; 3.7.4 Single class capital at risk; 3.8 Insurance modeling; 3.8.1 Appropriate haircuts reflecting the policy’s declining residual term; 3.8.2 Payment uncertainty; 3.8.3 Counterparty risk; 3.8.4 Application of insurance; 3.9 Adjustment for risk indicators; 3.10 Operational risk classes aggregation; 3.10.1 Copulae functions; 3.10.2 Elliptical copulae; 3.10.3 Archimedean copulae; 3.10.4 Choice of copula; 3.10.5 Correlation coefficients; 3.11 The closed-form approximation for OpVaR; 3.11.1 Effect of the minimum threshold on capital at risk; 3.12 Confidence band for capital at risk; 3.13 Stress testing; 3.14 Loss data minimum threshold setting; 3.15 Empirical application on Algo OpData; 3.15.1 Descriptive statistics; 3.15.2 Autocorrelation analysis; 3.15.3 Capital at risk estimates using parametric models; 3.15.4 Capital at risk estimates using EVT; 3.15.5 Capital at risk estimates using the g-and-h distribution; 3.15.6 Capital at risk estimates considering Correlation; 3.16 Regulatory capital requirement; 3.16.1 The consolidated capital requirement; 3.16.2 The individual capital requirement; 3.17 Economic capital requirement; 3.18 Integration of operational risk in the budgeting process; 4 Analyzing Insurance Policies; 4.1 Insurance management and risk transfer; 4.2 Qualifying criteria in the Basel 2 capital Framework; 4.2.1 Rating of the insurance company; 4.2.2 Duration and residual term of the insurance contract; 4.2.3 Policy termination requisites; 4.2.4 Claims reimbursement uncertainty and ineffective coverage; 4.2.5 Conclusions; 4.3 A practical application to traditional insurance; 4.3.1 Insurance policies to cover financial institutions’ operational risks; 4.3.2 Operational event types and available insurance coverage; 5 Managing Reputational Risk; 5.1 Introducing reputational risk; 5.2 A financial institution’s reputational risk exposure; 5.3 Managing reputational risk: a matter of policy; 5.4 Reputational risk measurement; 5.4.1 Reputational risk as a function of share price volatility; 5.4.2 Measuring reputational risk using scenarios; 5.4.3 Scoring-card-based models for reputational risk assessment; 5.5 A recent example of reputational event; 5.5.1 A description of the event; 5.5.2 Background; 5.5.3 How the fake trading occurred; 5.5.4 The discovery and first reactions; 5.5.5 Measures planned and taken; 5.5.6 Immediate consequences for SocGen; 5.5.7 Reputational issues and comments; 5.5.8 The lessons learned – what can we do to avoid being next?; 5.5.9 Psychological, ‘soft’ factors; 5.5.10 Control instruments; 5.5.11 Managing data and signals; 6 Conclusions; References; Further reading; Index
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