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Identifying the risk culture of banks using machine learning
Abena Owusu
, Aparna Gupta
Accounting and Finance
Research output
:
Contribution to journal
›
Article
›
peer-review
5
Scopus citations
Overview
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Dive into the research topics of 'Identifying the risk culture of banks using machine learning'. Together they form a unique fingerprint.
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Computer Science
Component Analysis
100%
Principal Components
100%
Machine Learning
100%
Learning System
100%
Risk Management
66%
Cluster Analysis
33%
Structured Data
33%
Data Source
33%
Machine Learning Technique
33%
Text Mining
33%
Unsupervised Learning
33%
Machine Learning Approach
33%
Good Governance
33%
Risk Governance
33%
Abstract Concept
33%
Keyphrases
Machine Learning
100%
Risk Culture
100%
Principal Coordinate Analysis (PCoA)
23%
Cultural Characteristics
15%
Design Methodology
7%
Two Dimensional
7%
Cluster Analysis
7%
Risk Management
7%
Traditional Data
7%
Reduction Method
7%
Risk Perception
7%
K-means
7%
Structured Data
7%
Unsupervised Learning
7%
Text Mining
7%
Dictionary
7%
Unstructured Text
7%
Default Risk
7%
Good Governance
7%
Learning to Cluster
7%
Unsupervised Machine Learning Approach
7%
Risk Governance
7%
Culture Management
7%
Cultural Concepts
7%
Regulatory Expectations
7%
Culture Group
7%
Unsupervised Machine Learning Techniques
7%
Profitability Ratios
7%
Bank Stability
7%
Culture Clusters
7%
Effective Risk Management
7%
Engineering
Principal Components
100%
Component Analysis
100%
Learning System
100%
Two Dimensional
33%
Data Source
33%
Learning Approach
33%
Machine Learning Technique
33%
Economics, Econometrics and Finance
Principal Components
100%
Machine Learning
100%
Risk Management
66%
Bank Stability
33%