001443590 000__ 05186cam\a2200541\i\4500
001443590 001__ 1443590
001443590 003__ OCoLC
001443590 005__ 20230310003552.0
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001443590 008__ 220108s2022\\\\cau\\\\\ob\\\\001\0\eng\d
001443590 019__ $$a1291229559$$a1291267956$$a1291289570$$a1291312487$$a1295440517
001443590 020__ $$a9781484274408$$q(electronic bk.)
001443590 020__ $$a1484274407$$q(electronic bk.)
001443590 020__ $$z1484274393
001443590 020__ $$z9781484274392
001443590 0247_ $$a10.1007/978-1-4842-7440-8$$2doi
001443590 035__ $$aSP(OCoLC)1291316034
001443590 040__ $$aEBLCP$$beng$$erda$$epn$$cEBLCP$$dTOH$$dORMDA$$dGW5XE$$dYDX$$dSTF$$dYDX$$dOCLCO$$dOCLCF$$dOCLCQ
001443590 049__ $$aISEA
001443590 050_4 $$aHD61$$b.S83 2022
001443590 08204 $$a658.155$$223
001443590 1001_ $$aR, Kannan Subramanian,$$eauthor.
001443590 24510 $$aEvent- and data-centric enterprise risk-adjusted return management :$$ba banking practitioner's handbook /$$cKannan Subramanian R, Sudheesh Kumar Kattumannil.
001443590 264_1 $$a[Berkeley, CA] :$$bApress,$$c[2022]
001443590 300__ $$a1 online resource (1112 pages)
001443590 336__ $$atext$$btxt$$2rdacontent
001443590 337__ $$acomputer$$bc$$2rdamedia
001443590 338__ $$aonline resource$$bcr$$2rdacarrier
001443590 504__ $$aIncludes bibliographical references and index.
001443590 5050_ $$aChapter 1: Commercial Banks, Banking Systems, and Basel Recommendations -- Chapter 2: Siloed Risk Management Systems -- Chapter 3: Enterprise Risk Adjusted Return Model (ERRM), Gap Analysis, and Identification -- Chapter 4: ERRM Methodology, High-level Implementation Plan -- Chapter 5: Enterprise Architecture -- Chapter 6: Enterprise Data Management -- Chapter 7: Enterprise Risk Data Management -- Chapter 8: Data Science and Enterprise Risk Return Management -- Chapter 9: Advanced Analytics and Knowledge Management -- Chapter 10: ERRM Capabilities and Improvements -- Appendix A: Abbreviations -- Appendix B. List of Processes.
001443590 506__ $$aAccess limited to authorized users.
001443590 520__ $$aTake 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. What You Will Learn 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 Who This Book Is For The global banking community, including: senior management of a bank, such as the Chief Risk Officer, Head of Treasury/Corporate Banking/Retail Banking, Chief Data Officer, and Chief Technology Officer. It is also relevant for banking software vendors, banking consultants, auditors, risk management consultants, banking supervisors, and government finance professionals
001443590 588__ $$aDescription based on print version record.
001443590 650_0 $$aFinancial risk management.
001443590 650_0 $$aFinancial risk management$$xData processing.
001443590 650_0 $$aBanks and banking.
001443590 650_6 $$aFinances$$xGestion du risque.
001443590 650_6 $$aFinances$$xGestion du risque$$xInformatique.
001443590 655_0 $$aElectronic books.
001443590 7001_ $$aKattumannil, Sudheesh Kumar,$$eauthor.
001443590 77608 $$iPrint version:$$aSubramanian R, Kannan.$$tEvent- and Data-Centric Enterprise Risk-Adjusted Return Management.$$dBerkeley, CA : Apress L.P., ©2022$$z9781484274392
001443590 852__ $$bebk
001443590 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-1-4842-7440-8$$zOnline Access$$91397441.1
001443590 909CO $$ooai:library.usi.edu:1443590$$pGLOBAL_SET
001443590 980__ $$aBIB
001443590 980__ $$aEBOOK
001443590 982__ $$aEbook
001443590 983__ $$aOnline
001443590 994__ $$a92$$bISE