Structural modelling of operational risk in financial institutions: application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
Pro Business
2008
|
| Ausgabe: | 1. Aufl. |
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XVI 162 S. Ill., graph. Darst. 210 mm x 148 mm, 248 gr. |
| ISBN: | 9783868059748 |
Internformat
MARC
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| 245 | 1 | 0 | |a Structural modelling of operational risk in financial institutions |b application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling |c Irina Starobinskaya |
| 250 | |a 1. Aufl. | ||
| 264 | 1 | |a Berlin |b Pro Business |c 2008 | |
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| 336 | |b txt |2 rdacontent | ||
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| 650 | 7 | |a Bayes-Statistik |2 stw | |
| 650 | 7 | |a Expertensystem |2 stw | |
| 650 | 7 | |a Informationstechnik |2 stw | |
| 650 | 7 | |a Infrastruktur |2 stw | |
| 650 | 7 | |a Internes Kontrollsystem |2 stw | |
| 650 | 7 | |a Operationales Risiko |2 stw | |
| 650 | 7 | |a Risiko |2 stw | |
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Datensatz im Suchindex
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| adam_text |
Titel: Structural modelling of operational risk in financial institutions
Autor: Starobinskaya, Irina
Jahr: 2008
Contents
I Introduction 1
1 Introduction and outline 3
1.1 Introduction and motivation. 3
1.2 Research objectives and scope of the thesis. 4
1.3 Outline of the thesis. 6
II Theoretical background 9
2 Operational risk 11
2.1 Operational risk: Definitions. 11
2.2 Developments in regulatory requirements for operational risk modelling: The Basel
II Accord and The Sarbanes-Oxley Act. 13
2.2.1 The Basel II Accord. 13
2.2.2 The Sarbanes-Oxley Act. 16
2.3 Review of existing methods for modelling operational risk. 17
2.3.1 Methods based on historical data. 19
2.3.1.1 Actuarial models: Loss Distribution Approach. 20
2.3.2 Methods based solely on expert knowledge. 22
2.3.3 Methods based on a combination of historical data and expert knowledge . . 23
2.4 Problems and challenges of modelling operational risk . 23
vii
2.4.1 Data insufficiency problem. 24
2.4.2 Modelling dependencies. 25
3 Bayesian networks 29
3.1 Introduction to Bayesian networks . 29
3.2 Core concepts of Bayesian networks. 30
3.2.1 Introduction to the graph theory. 30
3.2.2 The Bayes' theorem and probability calculus . 33
3.2.3 Conditional independence, d-separation and formal definition of the Bayesian
networks. 35
3.3 Quantification of Bayesian networks . 37
3.3.1 Algorithms for learning Bayesian networks from data. 37
3.3.1.1 Known structure and full observability. 38
3.3.1.2 Known structure and partial observability. 39
3.3.1.3 Unknown structure and full observability. 40
3.3.1.4 Unknown structure and partial observability . 42
3.4 Inference algorithms for evaluation of Bayesian networks. 42
3.4.1 Exact inference algorithms. 43
3.4.2 Approximate inference algorithms. 45
3.5 Evaluating quality of Bayesian network models. 46
3.5.1 Logarithmic score. 47
3.5.2 Model assessment. 47
3.5.3 Diagnostic monitors. 48
3.6 Application areas of Bayesian networks. 49
3.7 Advantages and limitations of Bayesian networks as a risk modelling tool. 50
4 Balanced Scorecards 53
viii
4.1 Introduction to Balanced Scorecards. 53
4.2 Core concepts of Balanced Scorecards . 54
4.2.1 Basic principles of Balanced Scorecards . 54
4.2.2 Four perspectives of Balanced Scorecards . 50
4.2.3 Causality concept in Balanced Scorecard framework . 58
4.3 Designing a Balanced Scorecard. GO
4.4 Application areas of Balanced Scorecards. 64
4.5 Advantages and limitations of Balanced Scorecards as a risk modelling tool . 65
5 Expert knowledge elicitation 69
5.1 Introduction to expert knowledge elicitation. 69
5.2 Elicitation process . 70
5.2.1 General principles of the elicitation process . 70
5.2.2 Elicitation protocols. 71
5.2.3 Expert interviews and questionnaires. 73
5.3 Important facets and pitfalls of the elicitation process . 76
5.3.1 Necessary conditions for effective elicitation. 76
5.3.2 Consistency of expert estimates. 77
5.3.3 Biases of expert estimates. 78
5.4 Validation of expert estimates. 79
HI Application case study 83
6 IT infrastructure risk 85
6.1 IT risks . S5
6.2 IT infrastructure. 87
ix
6.2.1 IT infrastructure: definition and its role in risk generation. 87
6.2.2 Technical aspects of IT infrastructure risk. 89
6.3 Assessment of IT infrastructure risk . 91
6.3.1 Reliability, availability and maintainability analysis. 91
6.3.1.1 Basic principles. 91
6.3.1.2 RAM metrics. 92
6.3.2 Financial losses assessment . 95
7 Models construction 99
7.1 Risk mapping. 99
7.2 Constructing a Bayesian network model. 1""
7.2.1 Modelling the network structure . 102
7.2.1.1 Frequency network. 1"2
7.2.1.2 Severity network. 1°6
7.2.1.3 Model structure validation . 1°9
7.2.2 Quantification of the network. 1°9
7.2.2.1 Frequency network. 110
7.2.2.2 Severity network. 11J
7.2.3 Convolution of the frequency and severity distributions. *"
7.2.4 Maintaining the network. 118
7.3 Constructing a Balanced Scorecard model. * *
7.3.1 Combining Balanced Scorecard and Bayesian network models. H
7.3.2 Balanced Scorecard perspectives and indicators. *
7.3.3 Balanced Scorecard representation of IT infrastructure risk .¦ ¦ 1*°
8 Results and applications
x
8.1 Bayesian network model - Simulation results. 125
8.1.1 Descriptive statistics. 125
8.1.2 Risk metrics. 126
8.2 Updating the Bayesian network given event evidence. 127
8.3 Managing operational risk with a Bayesian network model - Scenario analysis . 128
8.3.1 Scenario 1 - Impact of adverse conditions . 130
8.3.2 Scenario 2 - Impact of dependence structure. 131
8.3.3 Scenario 3 - Impact of additional employee training. 133
IV Conclusion 135
9 Summary and conclusion 137
9.1 Summary of the thesis. 137
9.2 Further research questions. 139
9.3 Conclusion. 140
V Appendices 141
A Prior probability distributions 143
B Posterior probability distributions 145
C Monte-Carlo convolution procedure 147
Bibliography I50
List of Figures
2.1 Operational risk modelling methods . 19
2.2 Loss Distribution Approach. 22
3.1 A directed graph and its indirected version. 31
3.2 A complete graph. 31
3.3 A directed graph and its moral version. 33
3.4 Conditional independence in BN framework. 36
4.1 Balanced Scorecard - The four perspectives . 57
4.2 Example of linking the measures from the four perspectives. 59
5.1 Fragment of a questionnaire. 75
6.1 Timeline of a failure . 92
7.1 Subnetwork - Frequency of failures for technical component. 104
7.2 Subnetwork - Frequency of user incidents . 104
7.3 Network - Frequency of failures. 105
7.4 Subnetwork - Severity of failures for technical component . 107
7.5 Subnetwork - Severity of user incidents. 107
7.6 Network - Severity of failures. 108
7.7 Prior distributions - Frequency of failures network. 113
xiii
7.8 Prior distributions - Severity of failures network. 116
7.9 Convolution of the frequency and severity distributions. 117
7.10 Logistic loss function. 117
7.11 Mapping frequency BN and BSC perspectives. 121
7.12 Mapping severity BN and BSC perspectives. 122
7.13 Balanced Scorecard representation of IT infrastructure risk. 124
8.1 Histogram of loss distribution. 126
8.2 Updating frequency of failures network given two failures observed . 129
8.3 Severity network - Modification of technical support structure. 132
8.4 Impact of dependence level . 133
8.5 Impact of additional training. 134
List of Tables
2.1 The relative importance of the risk types. 11
2.2 Examples of operational risk. 12
2.3 Business lines and event types classification. 14
2.4 Main sections of the Sarbanes-Oxley Act. 16
2.5 Challenges in modelling operational risk. 24
3.1 Learning methods for Bayesian networks. 38
4.1 The four perspectives in a standard Balanced Scorecard . 55
6.1 IT infrastructure risk questions. 88
6.2 Comparison of IT infrastructures/architectures. 90
6.3 Loss evaluation methods. 97
7.1 Risk factors and indicators mapping. 101
7.2 Frequency network - nodes description. 112
7.3 Severity network - nodes description. 115
8.1 Descriptive statistics of annual loss distribution. 126
8.2 Value-at-Risk and Expected Shortfall of annual losses. 127
8.3 Impact of adverse conditions on Value-at-Risk . 130
8.4 "Quality of component" node distribution . 131
xv
8.5 "User skills" node distribution. 134
A.I Prior frequency distribution. 143
A.2 Prior severity distribution. 144
B.I Posterior frequency distribution - Adverse conditions scenario. 145
B.2 Posterior severity distribution - Adverse conditions scenario. 146 |
| any_adam_object | 1 |
| author | Starobinskaya, Irina 1982- |
| author_GND | (DE-588)13704335X |
| author_facet | Starobinskaya, Irina 1982- |
| author_role | aut |
| author_sort | Starobinskaya, Irina 1982- |
| author_variant | i s is |
| building | Verbundindex |
| bvnumber | BV035279629 |
| classification_rvk | QK 300 |
| ctrlnum | (OCoLC)311071255 (DE-599)DNB991725328 |
| dewey-full | 332.10285 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.10285 |
| dewey-search | 332.10285 |
| dewey-sort | 3332.10285 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| edition | 1. Aufl. |
| format | Thesis Book |
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| indexdate | 2024-07-20T10:01:36Z |
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| publisher | Pro Business |
| record_format | marc |
| spelling | Starobinskaya, Irina 1982- Verfasser (DE-588)13704335X aut Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling Irina Starobinskaya 1. Aufl. Berlin Pro Business 2008 XVI 162 S. Ill., graph. Darst. 210 mm x 148 mm, 248 gr. txt rdacontent n rdamedia nc rdacarrier Zugl.: München, Univ., Diss., 2008 Balanced Scorecard stw Bank - Risikomanagement - Informationstechnik - Balanced Scorecard Bank - Risikomanagement - Informationstechnik - Bayes-Netz Bank stw Basel II stw Bayes-Statistik stw Expertensystem stw Informationstechnik stw Infrastruktur stw Internes Kontrollsystem stw Operationales Risiko stw Risiko stw Balanced Scorecard (DE-588)4568727-4 gnd rswk-swf Informationstechnik (DE-588)4026926-7 gnd rswk-swf Bank (DE-588)4004436-1 gnd rswk-swf Bayes-Netz (DE-588)4567228-3 gnd rswk-swf Risikomanagement (DE-588)4121590-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Bank (DE-588)4004436-1 s Risikomanagement (DE-588)4121590-4 s Informationstechnik (DE-588)4026926-7 s Balanced Scorecard (DE-588)4568727-4 s DE-604 Bayes-Netz (DE-588)4567228-3 s text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3194589&prov=M&dok_var=1&dok_ext=htm Inhaltstext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017084858&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Starobinskaya, Irina 1982- Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling Balanced Scorecard stw Bank - Risikomanagement - Informationstechnik - Balanced Scorecard Bank - Risikomanagement - Informationstechnik - Bayes-Netz Bank stw Basel II stw Bayes-Statistik stw Expertensystem stw Informationstechnik stw Infrastruktur stw Internes Kontrollsystem stw Operationales Risiko stw Risiko stw Balanced Scorecard (DE-588)4568727-4 gnd Informationstechnik (DE-588)4026926-7 gnd Bank (DE-588)4004436-1 gnd Bayes-Netz (DE-588)4567228-3 gnd Risikomanagement (DE-588)4121590-4 gnd |
| subject_GND | (DE-588)4568727-4 (DE-588)4026926-7 (DE-588)4004436-1 (DE-588)4567228-3 (DE-588)4121590-4 (DE-588)4113937-9 |
| title | Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling |
| title_auth | Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling |
| title_exact_search | Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling |
| title_full | Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling Irina Starobinskaya |
| title_fullStr | Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling Irina Starobinskaya |
| title_full_unstemmed | Structural modelling of operational risk in financial institutions application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling Irina Starobinskaya |
| title_short | Structural modelling of operational risk in financial institutions |
| title_sort | structural modelling of operational risk in financial institutions application of bayesian networks and balanced scorecards to it infrastructure risk modelling |
| title_sub | application of Bayesian networks and balanced scorecards to IT infrastructure risk modelling |
| topic | Balanced Scorecard stw Bank - Risikomanagement - Informationstechnik - Balanced Scorecard Bank - Risikomanagement - Informationstechnik - Bayes-Netz Bank stw Basel II stw Bayes-Statistik stw Expertensystem stw Informationstechnik stw Infrastruktur stw Internes Kontrollsystem stw Operationales Risiko stw Risiko stw Balanced Scorecard (DE-588)4568727-4 gnd Informationstechnik (DE-588)4026926-7 gnd Bank (DE-588)4004436-1 gnd Bayes-Netz (DE-588)4567228-3 gnd Risikomanagement (DE-588)4121590-4 gnd |
| topic_facet | Balanced Scorecard Bank - Risikomanagement - Informationstechnik - Balanced Scorecard Bank - Risikomanagement - Informationstechnik - Bayes-Netz Bank Basel II Bayes-Statistik Expertensystem Informationstechnik Infrastruktur Internes Kontrollsystem Operationales Risiko Risiko Bayes-Netz Risikomanagement Hochschulschrift |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=3194589&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017084858&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT starobinskayairina structuralmodellingofoperationalriskinfinancialinstitutionsapplicationofbayesiannetworksandbalancedscorecardstoitinfrastructureriskmodelling |