Identity and Access Management Global Technology Audit Guide (GTAG) 9 von,,,, 1. Auflage Identity and Access Management White / Renshaw / Rai / et al. schnell und portofrei erhältlich bei beck-shop.de DIE FACHBUCHHANDLUNG The Institute of Internal Auditors Verlag C.H. Beck im Internet: www.beck.de ISBN 978 0 89413 617 7
1. Executive Summary 2. Introduction 2.1 Business Drivers 2.2 Identity and Access Management Concepts 2.3 Adoption Risks TABLE OF CONTENTS 3. Definition of Key Concepts 3.1 Identity Management vs. Entitlement Management 3.2 Identity and Access Management Components 3.3 Access Rights and Entitlements 3.4 Provisioning Process 3.5 Administration of Identities and Access Rights Process 3.6 Enforcement Process 3.7 Use of Technology in IAM 4. The Role of Internal Auditors 4.1 Current IAM Processes 4.2 Auditing IAM 1
Chapter 8 Data Management Data Management Market Example: Setting Up a Claims RDBMS Data Management Overview: Implications for Prevention, Detection, and Investigation References Chapter 9 Normal Infrastructure Normal Profile of a Fraudster What Types of People or Entities Commit Fraud? What Is the Key Element of a Fraudster? Anomalies and Abnormal Patterns Normal Infrastructure Overview: Implications for Prevention, Detection, and Investigation Chapter 10 Normal Infrastructure And Anomaly Tracking Systems The Patient Sample Patient Fraud Scenarios Patient Data Management Considerations The Provider Sample Provider Fraud Scenarios Provider Data Management Considerations The Payer Sample Payer Fraud Scenarios Data Management Implications The Vendor/Other Parties Sample Vendor/Other Fraud Scenarios Data Management Implications Organized Crime Sample Organized Crime Fraud Scenarios Data Management Implications Normal Infrastructure and Anomaly Tracking Systems Overview: Implications for Prevention, Detection, and Investigation Chapter 11 Components of the Data Mapping Process What Is Data Mapping? Data Mapping Overview: Implications for Prevention, Detection, and Investigation Chapter 12 Components of the Data Mining Process What Is Data Mining? Data Mining in Healthcare Components to the Data Mining Process within the HCC Data Mining Overview: Implications for Prevention, Detection, and Investigation 2
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Chapter 13 Components of the Data Mapping and Mining Process Forensic Application of Data Mapping and Data Mining Data Mapping and Data Mining Overview: Implications for Prevention, Detection, and Investigation CHAPTER 14 Data Analysis Models Detection Model Pipeline Application Detection Model Application Investigation Model Mitigation Model Prevention Model Response Model Recovery Model Data Analysis Model Overview: Implications for Prevention, Detection, and Investigation CHAPTER 15 Clinical Content Data Analysis CHAPTER 16 Profilers What Is SOAP? The SOAP Methodology Electronic Records Analysis Considerations with Electronic Records Narrative Discourse Analysis Clinical Content Analysis Overview: Implications for Prevention, Detection, and Investigation Fraud and Profilers Medical Errors and Profilers Financial Errors and Profilers Internal Audit and Profilers Recovery and Profilers Anomaly and Profilers Fraud Awareness and Profilers Profiler Overview: Implications for Prevention, Detection, and Investigation CHAPTER 17 Market Implications CHAPTER 18 Conclusions The Myth Persistent Persuasive Unrealistic Market Overview: Implications for Prevention, Detection, and Investigation Micromanagement Perspective Macromanagement Perspective 4
Index Overview of Prevention, Detection, and Investigation 5