actuarial data management (adm) in a high-volume transactional processing environment

2005 Ratemaking2005 RatemakingSeminarSeminar

ACTUARIAL DATA MANAGEMENT (ADM)IN A HIGH-VOLUME

TRANSACTIONAL PROCESSINGENVIRONMENT

Joe Strube and Bryant RussellGMAC Insurance, Southfield, Michigan


Goal of the ADM Function

Equip the Actuarial Staff with the data resources necessary to excel in the performance of their functions

Not simply “get the actuaries data”• Add value to their analytical processes• C.A.T. Criteria

– Complete (Collect, Consolidate, Derive)– Accurate (Clean dirty/distorted data)– Timely (Prioritize data resource deliveries)

• Possibly assume responsibility for next stage


What Is A High-Volume Transactional Processing Environment (HVTPE)?

Frankly, It’s Arbitrary! • Online Transaction Processing System (OLTP)• Mainframe/Midrange Server Extract Files• Operational Data Store (ODS)• Data Warehouse (DW)• Data Mart (DM)• Desktop DB

Consider your most granular actuarial data resource Are 1 million or more transactions added per

month? If YES, you’re operating in an HVTPE


ADM, An Outgrowth of End User Computing

Rockart & Flannery Research Study (1983)

• Sloan School of Management at MIT

• Interviewed 250 People• 3 Fortune 50 Manufacturers• 2 Major Insurance Companies• 3 Sizable Canadian Companies

• Identified Six Types of End Users• Non-Programming End Users• Command Level Users• End User Programmers• Functional Support Personnel• End User Computing Support Personnel• DP Programmers


The Square Rootof

12,345,678,987,654,321

is111,111,111


As Technology Evolves, So Do Deliverables

Mainframe to Minicomputer to Microcomputer (PC)

Complex mainframe programs• Originally produced reports• Historical data files • Data downloads

Data Management Technology Branches Out• Data Warehousing• Data Marts• Online Analytical Processing (OLAP)• Extraction-Transformation-Loading Software (ETL)• Meta Data Repositories• Decision Support Systems• Data Profiling/Cleaning/Integration Software• Data Mining


Modern Roles in End User Computing

Non-Programming End Users(Business Manager, Process Modeler, Trainer)

Command Level Users(HR Rep, Accountant, Claim Analyst, Market Analyst)

End User Programmers(Actuary, Financial Analyst, Strategic Planner)

Functional Support Personnel(Data Manager/Administrator, Actuarial Technician)

End User Computing Support Personnel(Help Desk, User Hotline, DSS Analyst, DW Support

Team) DP Programmers (a.k.a. Systems Analyst)

(Internal/Outside Contractor, Technical Consultant)


Key Roles for ADM in a HVTPE

The Actuary

The Actuarial Technician

Information Technology Dept. (IT)


HVTPE and The Role of the Actuary

HVTPE offers the opportunity to work with detailed, granular data

• Classification Analyses• GLM Analyses• Loss Distributions• Data Mining

Comparison of data sources across functional areas becomes possible

• Policy Year vs. Accident Year vs. Calendar/Accident Year “slices” can be reconciled more easily

• Common data source overcomes the “my data-your data” syndrome


The Role of the Actuary

HVTPE is inherently multidimensional• Transactional data is very granular, detailed• Multiple views can be aggregated from common

source (transactional data)• Very useful for examining interactions between

factors

As a “source”, HVTPE allows actuarial data repositories to be created, stored, and maintained over time

• Actuary can select data based on actuarial value• Less reliance on non-actuarial reports


Q: Why not let the actuary do it all?

Many actuaries well-versed with database and analytical software

But data from HVTPE is just the first step• Data extraction is input to analyses• Actuarial work typically requires more than just a

summary report of historical experience

Data extraction process can overwhelm traditional desktop tools

• Over 1 million transactions per month• Even data storage, can overwhelm desktop resources

available to actuary


Q: Why not let others (ADM) do it all?

Data specialization enables more robust process of gathering, storing, reporting data

• Data skills are specialized• Software and hardware can be “industrial strength”• Monitoring, balancing, aggregating are important,

but non-actuarial tasks

HVTPE is not a static environment • Changes to data definitions• Addition of new data elements• Addition of new data sources


Q: Why not let others (ADM) do it all?

Value of actuarial data elements may be seen as secondary to other functional areas

• Required level of detail for actuarial analysis is different

• Historical retention periods are different• Specific data elements may be uniquely valuable to

the actuary – other areas would not gather/maintain these.

Actuarial data needs are dynamic• Summary level varies by type of actuarial analysis• Variables included can range from few to many• Not realistic to try & build all possible aggregations

ahead of time (OLAP tools notwithstanding)


The Role of the Actuary Identify the value of actuarial data

• Critical Data Elements• Actuarially Valuable Data Elements• Nonessential Data Elements (for actuarial analysis)

Determine required level of detail• Granularity of data (e.g. at transactional level)• Historical time periods and retention periods• Definitions of derived data (e.g. books of business,

classes, etc.)

Support the Value Proposition of Data Dictionary

• What does the data mean? What are meaningful values?• Have definitions, coding, accuracy, completeness

changed over time?


The Role of the Actuarial Technician

Data Facilitator• Building Inspector• Lawyer• Guinea Pig

Data Supplier• Fulcrum• Sculptor• Magician


The Role of IT Management

Manage Infrastructure

Manage Corporate Projects


Data Management Processes

Data Modeling, Metadata, Data Dictionary

Data Extraction, Profiling, QualityData Integration, TransformationData LoadingNot Data Retrieval, Reporting


There are

336 cavities

on a golf ball.


GMAC Insurance Case Study

Vehicle Service Contracts• Multiple period contracts – under 12 months to

over 84 months• Multiple countries and business partners• Multiple data sources• Over 1 million transactions per month


Q & A


In Nawlins . . .

It’s mandatory to jazz things

up!

actuarial data management (adm) in a high-volume transactional processing environment

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