Ratemaking Seminar2005

The Convergence of Technology, The Convergence of Technology, Data Standards & Analytical ToolsData Standards & Analytical Tools

The Need for Better InformationThe Need for Better Information

Arthur R. Cadorine - ISOArthur R. Cadorine - ISO

Insurance Industry StandardsInsurance Industry Standards

Standards for policy and claim Standards for policy and claim transactions are being developedtransactions are being developed

ACORDACORDIAIABCIAIABCIDMAIDMA

These standards will change the industryThese standards will change the industry

Impact of StandardsImpact of Standards

If everyone speaks the same language, If everyone speaks the same language, communication is possiblecommunication is possible

Information quality and timeliness Information quality and timeliness improves improves

Data StandardsData StandardsWho Needs’Em and Why?Who Needs’Em and Why?

Trading partners such as insureds, Trading partners such as insureds, insurers, TPAs, vendors, and brokersinsurers, TPAs, vendors, and brokers

Various sources use different Various sources use different definitionsdefinitions

Need data that is clean and consistentNeed data that is clean and consistent Reduce duplication and costReduce duplication and cost Numerous indirect benefitsNumerous indirect benefits Some obstacles remainSome obstacles remain

Data StandardsData StandardsDon’t They Exist Already?Don’t They Exist Already?

Financial services and some retailers Financial services and some retailers use data standardsuse data standards

Some insurance standards developed Some insurance standards developed for specific applicationsfor specific applications

Standards are not identicalStandards are not identical

Data StandardsData StandardsCurrent Working GroupsCurrent Working Groups

IDMA TPA Data Standards Work GroupIDMA TPA Data Standards Work Group ACORDACORD ANSIANSI RIMSRIMS ISOISO WC Insurance Organizations (WCIO)WC Insurance Organizations (WCIO)

Data StandardsData StandardsCurrent ToolsCurrent Tools

PDRP - GL database for public entitiesPDRP - GL database for public entities IDMA Claims Data Exchange StandardIDMA Claims Data Exchange Standard IDMA Policy Data Element DictionaryIDMA Policy Data Element Dictionary IDMA TPA Data Standards White PaperIDMA TPA Data Standards White Paper www.idma.org/DS-announce.htmlwww.idma.org/DS-announce.html

Value of Knowing SoonerValue of Knowing Sooner

Delays in claims reporting cost moneyDelays in claims reporting cost money

Real-time fraud detection could save $$Real-time fraud detection could save $$

Early claim-trend detection means Early claim-trend detection means corrective premium actioncorrective premium action

Integrating EDI ReportingIntegrating EDI Reporting

Straight-through processingStraight-through processingbecomes possiblebecomes possible

Data quality improvesData quality improves

Information can be aggregatedInformation can be aggregated

ASP model has many advantagesASP model has many advantages

Integration of DataIntegration of Data

ASP can have policy ASP can have policy andand claim databases claim databases

Systems can talk to one anotherSystems can talk to one another

One source/multiple outputs One source/multiple outputs

Analytical ToolsAnalytical Tools

Predictive modelsPredictive models

Web accessWeb access

User-friendly report writers User-friendly report writers

User-friendly analysis softwareUser-friendly analysis software

ASOP #23: Data QualityASOP #23: Data Quality

Purpose is to give guidance in:Purpose is to give guidance in:Selecting dataSelecting dataReviewing data for appropriateness, Reviewing data for appropriateness,

reasonableness, and reasonableness, and comprehensivenesscomprehensiveness

Making appropriate disclosuresMaking appropriate disclosures Does not recommend that actuaries Does not recommend that actuaries

audit dataaudit data

ASAP #23: Data QualityASAP #23: Data QualityConsiderations in Selection of DataConsiderations in Selection of Data

Appropriateness for intended purposeAppropriateness for intended purpose Reasonableness, comprehensiveness, Reasonableness, comprehensiveness,

and consistencyand consistency Limitations of or modifications to dataLimitations of or modifications to data Cost and feasibility of alternativesCost and feasibility of alternatives Sampling methodsSampling methods

ASOP #23: Data QualityASOP #23: Data QualityDefinition of DataDefinition of Data

Numerical, census, or class informationNumerical, census, or class information Not actuarial assumptionsNot actuarial assumptions Not computer softwareNot computer software Definition of comprehensiveDefinition of comprehensive Definition of appropriateDefinition of appropriate

ASAP #23: Data QualityASAP #23: Data QualityOther ConsiderationsOther Considerations

Imperfect DataImperfect Data Reliance on OthersReliance on Others Documentation/DisclosureDocumentation/Disclosure

IDMAIDMA Data Management for InsuranceData Management for Insurance ProfessionalsProfessionals

Chapters at a GlanceChapters at a Glance

I. The History of Insurance Data ManagementI. The History of Insurance Data ManagementII. Role of Insurance Data ManagerII. Role of Insurance Data ManagerIII. Key Data Elements of InsuranceIII. Key Data Elements of Insurance

IV. Insurance Company’s Use of DataIV. Insurance Company’s Use of DataV. The External Insurance EnvironmentV. The External Insurance Environment

VI. Data QualityVI. Data QualityVII. Data RepositoriesVII. Data Repositories

VIII. Future Data Management IssuesVIII. Future Data Management Issues

C.A.S.RATEMAKING SEMINAR

New Orleans 2005

INT-1

Introduction to Insurance Data Management 101

Nathan Root

CNA

A group of people within insurance organizations whose primary day-to-day function is to provide

business managers with the information they need to accomplish the goals and objectives of the

organization.

– Core data managers are involved in: • Internal data coordination

• External data reporting

• Information systems development

• Data administration

Data Managers, Who-What-Where

What is a Data Manager?

• A Data Manager:– Provides data

• To internal customers

• To external customers

– Is concerned that the data provided• Is accurate & consistently derived & defined

• Is readily available and timely

• Is comparable/reconcilable

• Secure

Who are the customers?

• Internal customers include:– ACTUARIES

– Underwriters

– Accountants

– Claims

– Marketing and Distribution Network

– Management

Who are the customers?

• External customers include:– Statistical organization

– Rate making organization

– Insurance research organizations

– Investors

– State & Federal regulators

The data manger’s job?

• To interpret requests for data

• Determine how to obtain data

• Determine where to obtain data

• Control the cost of development and maintenance

• Provide data to customers in appropriate format

Data Management’s Task

The data manager’s task is to assure that the same data

in different systems can be reconciled, that the data

is consistent, and that derived data is defined and

calculated consistently.

Partnerships

Data users are, and should be, involved in a partnership

with insurance data managers.

-A partner in

= defining systems

= building systems

= testing systems

= and final acceptance of a system.

Knowledge and Other Users

Just as Data Managers need and must have knowledge

of the customer’s they serve, so must other insurance

professional understand the Data Manager’s function.

EACH TIME AN INDIVIDUAL WANTS INFORMATION, DATA MANAGEMENT SKILLS COME INTO PLAY.

It must be determined where the data is, how it is identified, how it is defined

AND HOW IT CAN BE VARIFIED.

What do you need to know about Data Management

• Data definitions and how they differ.

• Coding conventions.

• Data redundancy.

• Level of data available/needed.

• Where did the data come from and how is it maintained.

• Schedule for updating.

• Reasonability and reliability of the data.

Who are Insurance Data Managers?

• Managers of data which can be anyone– Professional insurance data managers– Actuaries– Underwriters and Agents– Claims personnel and SIU’s– Marketing personnel and Researchers– Accountants and Economists

Who Owns the Data?

Data use - implies data ownership - which mandates control.

An individual companies data is one of its most valuable assets, if not its most valuable asset.

With control comes definite responsibilities.

- You also become responsible for your data’s

- VALIDITY

- ACCURACY

- REASONABILITY

- COMPLETENESS

Confidentiality and Privacy

All users and managers of data MUST be constantlyaware of the issues surrounding Confidentiality andPrivacy. Confidential data is very different from data

that is controlled by privacy laws.-Confidential data: given with the understanding that the

information will be treated as confidential- Privacy of data: usually governed by law, either State or

Federal or both.

- GRAMM-LEACH-BLILEY(GLB)- HEALTH INSURANCE PORTABILITY and ACCOUNTABILITY ACT(HIPAA)

DATA for the REGULATOR

• Solvency Data

Accounting

Actuarial

• Ratemaking Data

Rate Filings

Special Calls

The Data Management Environment

Micro-Computers have changed the data management

environment. Literally every user of a micro-computer

has had to become a data manager.

The Insurance Data Management Association(IDMA)

provides education and a forum for knowledge in this field

Insurance Data Management Association(IDMA)

IDMA has partnered with the CAS and is prepared to share

its knowledge of data with CAS members.

The IDMA’s “Data Management for Insurance Professionals” is available today. It is designed as a primer and is intended for both the professional and those yet to become professional within the insurance industry.

For further information on this course contact the IDMA at 1-201-469-3069.

IDMA Data Management for Insurance Professionals

Chapters at a Glance

I. The History of Insurance Data ManagementII. Role of Insurance Data ManagerIII. Key Data Elements of Insurance

IV. Insurance Company’s Use of DataV. The External Insurance Environment

VI. Data QualityVII. Data Repositories

VIII. Future Data Management Issues

Casualty Actuarial SocietyRatemaking SeminarNew Orleans 2005

INT-1

Introductory Data Management 101

Al Hapke

Meadowbrook Insurance Group

Your Role in Data Management

• Demanding User

• Lack of defined needs

• Lack of knowledge about information technology

• Lack of business knowledge in the IT staff

Therefore, you must communicate your goals effectively and clearly.

Objective of Data Management:

To store and organize data in a way that allows the analyst to answer questions about the business.

These questions should help direct and guide the management of the business.

Processing Systems are not adequate to satisfy the analytical needs of the company.

They’re designed to do work, not answer questions.

Steps That Help Communication:

• Formulate many specific questions– Brainstorm yourself

– Talk to your customers/clients/boss

– Read actuarial papers

– Review competitive rate filings

• Write them down

• Design your spreadsheet or model to answer the question

• Determine what you need to populate the spreadsheet

Example of Questions:

What do we expect to pay for claims in this class vs. other classes?

1. Age/experience of driver

2. WC class code

3. Property construction

4. State/territory/location

5. Other characteristics such as credit rating,

new/renewal, etc.

Issues with this Question:

• Volume in each class or characteristic

• How much history?

• Can premium be appropriately matched with losses?

• Can earned exposures be captured?

• Can class definitions be multidimensional?

Other Questions:

• What is our exposure to maximum loss?– Answer can be found in limit/location studies

• How much development can we expect on reported losses?– Considerations:

• Report date

• Historical claim distributions

Other Questions (continued)

• Has our underlying book of business changed?– What types of losses are we seeing?

• This is only meaningful if we have been profiling our mix of claims so that we can see what’s different.

• e.g– Size of loss at consistent points in time– Minor coverage detail– Cause of loss

Other Questions (continued)

• Who, how much, and what is your producer selling?

What are the characteristics of the business being brought in the front door?

Or…. Leaving through the back door?

Issues to Consider in Your Management Information System

• Ease of Access - level of independence

from programmers

• Flexibility - new classes, new

characteristics, new products

• Quality of data