語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Event- and Data-Centric Enterprise Risk-Adjusted Return Management = A Banking Practitioner’s Handbook /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Event- and Data-Centric Enterprise Risk-Adjusted Return Management/ by Kannan Subramanian R, Dr. Sudheesh Kumar Kattumannil.
其他題名:
A Banking Practitioner’s Handbook /
作者:
Subramanian R, Kannan.
其他作者:
Kumar Kattumannil, Dr. Sudheesh.
面頁冊數:
XXVIII, 1090 p. 639 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Risk Management. -
電子資源:
https://doi.org/10.1007/978-1-4842-7440-8
ISBN:
9781484274408
Event- and Data-Centric Enterprise Risk-Adjusted Return Management = A Banking Practitioner’s Handbook /
Subramanian R, Kannan.
Event- and Data-Centric Enterprise Risk-Adjusted Return Management
A Banking Practitioner’s Handbook /[electronic resource] :by Kannan Subramanian R, Dr. Sudheesh Kumar Kattumannil. - 1st ed. 2022. - XXVIII, 1090 p. 639 illus.online resource.
Chapter 1: Commercial Banks, Banking Systems, and Basel Recommendations -- Chapter 2: Siloed Risk Management Systems -- Chapter 3: Enterprise Risk Adjusted Return Model (ERRM), Gap Analysis, and Identification -- Chapter 4: ERRM Methodology, High-level Implementation Plan -- Chapter 5: Enterprise Architecture -- Chapter 6: Enterprise Data Management -- Chapter 7: Enterprise Risk Data Management -- Chapter 8: Data Science and Enterprise Risk Return Management -- Chapter 9: Advanced Analytics and Knowledge Management -- Chapter 10: ERRM Capabilities and Improvements -- Appendix A: Abbreviations -- Appendix B. List of Processes.
Take a holistic view of enterprise risk-adjusted return management in banking. This book recommends that a bank transform its siloed operating model into an agile enterprise model. It offers an event-driven, process-based, data-centric approach to help banks plan and implement an enterprise risk-adjusted return model (ERRM), keeping the focus on business events, processes, and a loosely coupled enterprise service architecture. Most banks suffer from a lack of good quality data for risk-adjusted return management. This book provides an enterprise data management methodology that improves data quality by defining and using data ontology and taxonomy. It extends the data narrative with an explanation of the characteristics of risk data, the usage of machine learning, and provides an enterprise knowledge management methodology for risk-return optimization. The book provides numerous examples for process automation, data analytics, event management, knowledge management, and improvements to risk quantification. The book provides guidance on the underlying knowledge areas of banking, enterprise risk management, enterprise architecture, technology, event management, processes, and data science. The first part of the book explains the current state of banking architecture and its limitations. After defining a target model, it explains an approach to determine the "gap" and the second part of the book guides banks on how to implement the enterprise risk-adjusted return model. You will: Know what causes siloed architecture, and its impact Implement an enterprise risk-adjusted return model (ERRM) Choose enterprise architecture and technology Define a reference enterprise architecture Understand enterprise data management methodology Define and use an enterprise data ontology and taxonomy Create a multi-dimensional enterprise risk data model Understand the relevance of event-driven architecture from business generation and risk management perspectives Implement advanced analytics and knowledge management capabilities.
ISBN: 9781484274408
Standard No.: 10.1007/978-1-4842-7440-8doiSubjects--Topical Terms:
569483
Risk Management.
LC Class. No.: HD61
Dewey Class. No.: 658.155
Event- and Data-Centric Enterprise Risk-Adjusted Return Management = A Banking Practitioner’s Handbook /
LDR
:04184nam a22004335i 4500
001
1093358
003
DE-He213
005
20220512151500.0
007
cr nn 008mamaa
008
221228s2022 xxu| s |||| 0|eng d
020
$a
9781484274408
$9
978-1-4842-7440-8
024
7
$a
10.1007/978-1-4842-7440-8
$2
doi
035
$a
978-1-4842-7440-8
050
4
$a
HD61
072
7
$a
UR
$2
bicssc
072
7
$a
GPQD
$2
bicssc
072
7
$a
BUS033070
$2
bisacsh
072
7
$a
UR
$2
thema
072
7
$a
GPQD
$2
thema
082
0 4
$a
658.155
$2
23
082
0 4
$a
658.155
$2
23
100
1
$a
Subramanian R, Kannan.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1401288
245
1 0
$a
Event- and Data-Centric Enterprise Risk-Adjusted Return Management
$h
[electronic resource] :
$b
A Banking Practitioner’s Handbook /
$c
by Kannan Subramanian R, Dr. Sudheesh Kumar Kattumannil.
250
$a
1st ed. 2022.
264
1
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2022.
300
$a
XXVIII, 1090 p. 639 illus.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
Chapter 1: Commercial Banks, Banking Systems, and Basel Recommendations -- Chapter 2: Siloed Risk Management Systems -- Chapter 3: Enterprise Risk Adjusted Return Model (ERRM), Gap Analysis, and Identification -- Chapter 4: ERRM Methodology, High-level Implementation Plan -- Chapter 5: Enterprise Architecture -- Chapter 6: Enterprise Data Management -- Chapter 7: Enterprise Risk Data Management -- Chapter 8: Data Science and Enterprise Risk Return Management -- Chapter 9: Advanced Analytics and Knowledge Management -- Chapter 10: ERRM Capabilities and Improvements -- Appendix A: Abbreviations -- Appendix B. List of Processes.
520
$a
Take a holistic view of enterprise risk-adjusted return management in banking. This book recommends that a bank transform its siloed operating model into an agile enterprise model. It offers an event-driven, process-based, data-centric approach to help banks plan and implement an enterprise risk-adjusted return model (ERRM), keeping the focus on business events, processes, and a loosely coupled enterprise service architecture. Most banks suffer from a lack of good quality data for risk-adjusted return management. This book provides an enterprise data management methodology that improves data quality by defining and using data ontology and taxonomy. It extends the data narrative with an explanation of the characteristics of risk data, the usage of machine learning, and provides an enterprise knowledge management methodology for risk-return optimization. The book provides numerous examples for process automation, data analytics, event management, knowledge management, and improvements to risk quantification. The book provides guidance on the underlying knowledge areas of banking, enterprise risk management, enterprise architecture, technology, event management, processes, and data science. The first part of the book explains the current state of banking architecture and its limitations. After defining a target model, it explains an approach to determine the "gap" and the second part of the book guides banks on how to implement the enterprise risk-adjusted return model. You will: Know what causes siloed architecture, and its impact Implement an enterprise risk-adjusted return model (ERRM) Choose enterprise architecture and technology Define a reference enterprise architecture Understand enterprise data management methodology Define and use an enterprise data ontology and taxonomy Create a multi-dimensional enterprise risk data model Understand the relevance of event-driven architecture from business generation and risk management perspectives Implement advanced analytics and knowledge management capabilities.
650
2 4
$a
Risk Management.
$3
569483
650
2 4
$a
Financial Technology and Innovation.
$3
1388433
650
1 4
$a
IT Risk Management.
$3
1366666
650
0
$a
Financial risk management.
$3
564847
650
0
$a
Financial engineering.
$3
591542
650
0
$a
Risk management.
$3
559158
700
1
$a
Kumar Kattumannil, Dr. Sudheesh.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1401289
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9781484274392
776
0 8
$i
Printed edition:
$z
9781484274415
776
0 8
$i
Printed edition:
$z
9781484283752
856
4 0
$u
https://doi.org/10.1007/978-1-4842-7440-8
912
$a
ZDB-2-CWD
912
$a
ZDB-2-SXPC
950
$a
Professional and Applied Computing (SpringerNature-12059)
950
$a
Professional and Applied Computing (R0) (SpringerNature-43716)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入