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The Impact of Digital Transformation and FinTech on the Finance Professional

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Cover of 'The Impact of Digital Transformation and FinTech on the Finance Professional'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Batch Processing—Pattern Recognition
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    Chapter 3 Hyperledger Fabric as a Blockchain Framework in the Financial Industry
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    Chapter 4 Hyperledger Composer—Syndicated Loans
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    Chapter 5 The Concept of the Next Best Action/Offer in the Age of Customer Experience
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    Chapter 6 Using Prospect Theory to Determine Investor Risk Aversion
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    Chapter 7 Leveraging Predictive Analytics Within a Value Driver-based Planning Framework
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    Chapter 8 Predictive Risk Management
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    Chapter 9 Intraday Liquidity: Forecast Using Pattern Recognition
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    Chapter 10 Internal Credit Risk Models with Machine Learning
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    Chapter 11 Real Estate Risk: Appraisal Capture
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    Chapter 12 Managing Internal and External Network Complexity: How Digitalization and New Technology Influence the Modeling Approach
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    Chapter 13 Big Data and the CRO of the Future
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    Chapter 14 How Technology (or Distributed Ledger Technology and Algorithms Like Deep Learning and Machine Learning) Can Help to Comply with Regulatory Requirements
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    Chapter 15 New Office of the Comptroller of the Currency Fintech Regulation: Ensuring a Successful Special Purpose National Bank Charter Application
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    Chapter 16 Mathematical Background of Machine Learning
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    Chapter 17 Deep Learning: An Introduction
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    Chapter 18 Hadoop: A Standard Framework for Computer Cluster
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    Chapter 19 In-Memory Databases and Their Impact on Our (Future) Organizations
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    Chapter 20 MongoDB: The Journey from a Relational to a Document-Based Database for FIS Balance Sheet Management
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    Chapter 21 Summary and Outlook
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Mentioned by

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1 X user

Citations

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Title
The Impact of Digital Transformation and FinTech on the Finance Professional
Published by
Springer International Publishing, October 2019
DOI 10.1007/978-3-030-23719-6
ISBNs
978-3-03-023718-9, 978-3-03-023719-6
Editors

Liermann, Volker, Stegmann, Claus

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 16%
Student > Bachelor 4 9%
Student > Ph. D. Student 3 7%
Student > Doctoral Student 2 5%
Other 1 2%
Other 4 9%
Unknown 22 51%
Readers by discipline Count As %
Business, Management and Accounting 8 19%
Computer Science 6 14%
Economics, Econometrics and Finance 3 7%
Engineering 2 5%
Social Sciences 1 2%
Other 1 2%
Unknown 22 51%