Chapter Summaries
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CHAPTER ONE - The History of Data Management
In the History of Insurance Data Management, the
student explores both the history and basic terms and fundamentals
of Data Management. Here you will discover how the insurance
industry has changed its perception of the value, the function,
and the ownership of corporate information. The chapter covers
fundamentals of insurance information processing, and describes
how data collection was shaped by the limitations of early
computer systems. You'll learn the key distinction between
data and information, and how Data Management has emerged as
a distinct profession to maximize the informational value of
data. The chapter closes with a detailed discussion of the
IDMA organization - its activities, its goals, and need for
the participation of motivated Insurance Data Management professionals
like you.
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CHAPTER TWO - The Role of the Insurance Data
Manager
While Chapter One emphasized the importance of data, you'll begin to understand
the responsibilities of the people who are entrusted with the collection and
oversight of insurance information in Role of the Insurance Data Manager. The
student will see the reasons why the actuary, the underwriter, and senior management
decision-makers all rely on the work of the Data Manager. You will be introduced
to the concept of data stewardship, and gain an appreciation for how the Data
Manager's role differs in Property/Casualty insurers, Life/Health insurers,
and Regulatory Agencies.
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CHAPTER THREE - Key Data Elements
of Insurance
In Key Data Elements of Insurance, you will learn the fundamentals of insurance
ratemaking, and understand how credible rates rely upon quality data. Since
one of the primary purposes of insurance data is to provide an historical basis
for future rates, it is vital for any Data Management professional to understand
how actuaries use this information. You'll learn the components of a rate,
the definition of an 'adequate' rate, and the distinction between accident
year and policy year ratemaking data. Beyond the work of insurance actuaries,
you'll discover the goals of insurance regulators as they try to fulfill their
obligation to the industry and to the public. When you've completed this chapter,
you will be prepared to better understand data collection requirements, both
in published Statistical Plans and in new requirements that are asked by actuaries
and regulators.
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CHAPTER FOUR - Insurance Companies'
Use of Data
Insurance Companies' Use of Data continues the theme of Chapter Three,
but moves beyond ratemaking. Here you will see how insurers rely upon
quality data for internal departmental and corporate needs. You'll study
the importance of data in establishing underwriting guidelines. Insurers
and regulators have developed ratios used for assessing a company's
profitability and financial health; you will learn the definition and
uses of loss ratio, expense ratio, and combined ratio. The chapter demonstrates
why insurers need a distinct Data Management section or department,
and how its activities benefit the company by assuring access to a solid
and reliable knowledge base of data. The elements of good enterprise
data strategy are discussed. The chapter includes a discussion of
the impact of Data Management on the insurance customer. The difference
between ratemaking and statistical needs for data is explained.
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CHAPTER FIVE - The External Insurance
Environment
In The External Insurance Environment, you'll learn about the variety of stakeholders
who influence insurers and the need for information. Key organizations covered
include government agencies, insurance advisory/rating services, Departments
of Motor Vehicles, statistical agents, the NAIC, the IAIABC, MGAs, and TPAs.
You'll see that there are many factors that influence the insurance contract
beyond the insurer and the insured. Covered topics include the relationship
between internal and external uses of data, an overview of the statutory environment
(State Insurance Departments, State Worker's Compensation Commissions, The
International Association of Industrial Accident Boards and Commissions, and
the National Association of Insurance Commissioners), and some details on the
major rating advisory organizations and data collection agencies (AAIS, ISO,
NAII, NCCI, NCIS, NISS, AIPSO, SAA). You'll also discover how the role of statistical
agents may dramatically change in response to industry consolidation, the Internet,
deregulation, the threat of federal intervention, and social/legal pressure.
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CHAPTER SIX - Data Quality
You'll begin to understand the tools, methodologies,
and fundamental tenets embraced by Data Management professionals
in this chapter, Data Quality. The basic components of data
quality are listed and defined, the concept of systems testing
is introduced, and the process of error evaluation is covered.
To establish and promote the quality of information in your
own company, you'll benefit by learning these proven techniques
that have become the standards of the profession. You will
understand the difference between financial and statistical
data, in terms of means of collection, customers, uses, and
standards. Data standards, especially key in electronic communication,
are introduced and discussed. Quality assurance tools are covered
in an overview of statistical sampling measures, data audits,
and data monitoring systems. No architect of data quality is
equipped for the job without a command of these toolsets.
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CHAPTER SEVEN - Data Repositories
The nature of data storage and retrieval has changed along with available
technology. From ledgers and filing cabinets, early information processing
was advanced by the use of computers, tabulation machines, and the 80-column
keypunch cards. There has been a metamorphosis from the legacy computer
environment in which millions of electronic records (still largely analogous
to the 80-column keypunch card) are stored and manipulated in their
'flat file' format, to relational databases of information stored in
a hierarchical but flexible series of data tables. In Data Repositories,
you'll study the latest advances in technology for the storage of key
insurance data, such as Data Warehouse and Data Mining. You'll discover
the advantages inherent in the new technology, including the ease of
query by members of business units. The importance of metadata is explained.
Data backup and recovery are introduced and discussed as key elements
in ensuring data integrity.
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CHAPTER EIGHT - Future Data Management
Issues
The final chapter, Future Data Management Issues, examines the critical concerns
in technology, financial services, and regulation that face data managers.
You'll understand the key concept of convergence and how the necessity for
change is constant. Historical perspectives on convergence precede a discussion
on the digital nature of the New Economy and convergence in financial services
and in regulation. The course and chapter conclude with an emphasis on the
increasing need for professionalism within data management, and how data managers
must recognize that what they do is both a discipline and a profession. You'll
find a deeper appreciation of the history, the current efforts, and the continuing
need to educate and promote the value of certified, professional data managers
in organizations like IDMA. You will see a newly focused discussion with emphases
on public trust, the post 9/11 world, and the post-Enron world.
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Look over these sample objectives from the course — what would your responses
be like?
The History of Insurance Data Management
- Explain why insurers produce and use data, and summarize
how it is important to the company's competitive advantage.
- List the responsibilities of Data Administration and explain
how it relates to the database environment.
- Differentiate Data Management and Database Administration.
- Trace the improvements that set one generation of computers
apart from the preceding generation beginning in the 1960s
and onward.
- Explain the difference between data and information.
- Identify the founding purpose of the Insurance Data Management
Association (IDMA) and list eight activities and explain how
they relate to IDMA's stated purpose.
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Role of the Insurance Data Manager
- Describe some impediments to efficient communication.
- List important questions to ask when investigating meta-data.
Propose more that assure clarity.
- Define data stewardship and explain its purpose.
- Explain how property and casualty data managers support
actuaries, underwriters, and senior management decision-makers.
- List the characteristics of Statistical Plans and explain
their purpose.
- Name the similarities and differences between the property
and liability industry and the life and health industry, vis-à-vis
the role of the data manager.
- Trace the logic that holds that with increasing consolidation
of the industry, the data manager's role will become more critical.
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Key Data Elements of Insurance
- Quote the phrase that regulators use to judge insurance
rates (hint: it includes three conditions).
- Define an adequate rate, and go into some detail concerning
how that is determined; discuss what might complicate judging
whether or not a rate is adequate.
- Explain the "fair rate of return" approach and then state
the insurers' contrary argument.
- Distinguish between fair discrimination and unfair discrimination.
- List the seven goals regulators address in order to fulfill
their obligation to the industry and the public.
- Name the types of insurance regulation.
- List the five types of laws used in rate regulation.
- Define key ratemaking terms.
- Explain why accident year data and policy year data are
more useful for ratemaking than calendar year data.
- Differentiate policyholder, insured, and beneficiary in
the data elements required for life and health insurance.
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Insurance Companies' Use of Data
- Name at least three types of data which statistical organizations
provide that staff underwriters likely to evaluate before they
consider writing a new line of business or expanding an existing
line of business.
- Contrast the data collected by LOMA, LIMRA, and HIAA with
the data collected by property and casualty statistical bureaus,
in terms of regulatory demands, its completeness in representing
its side of the industry (life and health or property and casualty),
and its uses.
- Compare class rating with individual rating.
- List six ways data may be used to satisfy internal department
or company needs.
- Data are used to create three ratios important to determining
profitability. Define loss ratio, expense ratio, and combined
ratio.
- Advocate for sharing loss data - all forms of loss data
- with Underwriting.
- Give reasons life and health companies report to various
organizations when they are not required to by law.
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The External Insurance Environment
- Define the role of an advisory organization.
- Contrast the role of statistical agent with that of advisory
organization.
- Name the six major types of external organizations that
use insurance data and briefly explain how and why they collect
and use the data.
- Explain how submitting data to external users may eventually
benefit the insurer.
- List at least five specific activities that state insurance
departments engage in as they regulate the insurance industry.
- Give a brief summary of the purpose of the NAIC and describe
its membership.
- Describe the functions of each of the eight rating advisory
organizations named in this chapter.
- Contrast the capabilities of the MGA and the TPA.
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Data Quality
- Explain the difference between financial and statistical
data in terms of means of collection, customers, uses and standards.
- List several examples of the impact of using inaccurate
or inconsistent data within the industry and among its customers.
- Promote the concept of systems testing.
- Name and define the standard components of data quality.
- Characterize unit testing, system testing and acceptance
testing (user acceptance testing or field-testing).
- Define a Test Plan by referring to its five essentials.
- Name and explain seven steps in the process of error evaluation.
- Describe three error evaluation tools
- Enumerate the elements of a successful data audit.
- State the purpose of data monitoring systems, and specify
what insurers and statistical agents are responsible for under
a data-monitoring program.
- Define standards. List and explain the industry challenges — both
those that demand standards and those that stand in the way
of acceptance of standards.
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Data Repositories
- Define the data warehouse, citing the key components and
explaining what each term means specifically in relation to
this definition.
- List six functions and decision-making activities which
data contained in a data warehouse can support.
- As you read the "Historical Perspective - Where We Were" portion
of this chapter, realizing that the period covered is only
a few years, name the problems inherent in the early data warehouses
and tools developed to use them.
- Define naturally evolving architecture.
- Legacy systems, as their faults and uses are recounted here,
are still with the industry; name three reasons mainframe computers
are still in use today.
- Discuss the advantages and disadvantages of enterprise data
warehouses.
- Discuss and explain data backup and recovery reasons and
methods.
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Future Data Management Issues
- Use convergence as a model for evaluating the changes taking
place in the insurance marketplace.
- Identify critical issues in technology, financial services
and regulation facing data managers.
- Discuss various strategies and techniques for managing in
times of convergence.
- Identify the key aspects of a professional, and apply them
to data managers.
- Explain how professionalism is integral to successful data
management.
- Data managers routinely collaborate with other functions
and activities. Explain how this collaboration will broaden
and intensify as a result of the passage of the U.S. Terrorism
Risk Insurance Act.
- Discuss the impact of the tragedies of 9/11/2001 upon data
management.
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