Show Me the Data! Good Data Management Leads to Even Better Risk Management. but Risk Managers Seeking Their Company's Loss and Claims Data Often Find That Their Broker, Insurer or TPA Is Either Unable or Unwilling to Share Information. the Resulting Tug-of-War Is Enough to Leave Risk Managers Shouting

By Coffin, Bill; Quinn, Lawrence Richter | Risk Management, October 2002 | Go to article overview

Show Me the Data! Good Data Management Leads to Even Better Risk Management. but Risk Managers Seeking Their Company's Loss and Claims Data Often Find That Their Broker, Insurer or TPA Is Either Unable or Unwilling to Share Information. the Resulting Tug-of-War Is Enough to Leave Risk Managers Shouting


Coffin, Bill, Quinn, Lawrence Richter, Risk Management


Knowledge is power, or so the axiom goes. This is no truer than in the risk management industry, which has to handle an increasingly mind-numbing array of information. Risk managers must collect whatever data they can, analyze it and distribute it to a global base. For many, data management includes premium numbers; data on locations, vehicles and human resources; exposure analyses; policy and coverage management; loss and claims data; and loss forecasting.

Thankfully, technology has improved the efficiency of these processes. The Internet provides an electronic exchange among risk managers, brokers and insurers. Intranets offer an efficient, secure exchange of data between an enterprise's worldwide locations and its central risk management office.

But there is a problem. The success of any of these systems largely depends on the information provided to risk managers by their commercial insurance brokers, third party administrators (TPAs) and insurance carriers. And therein lies the rub. For various reasons, insurers and other outside parties often are unwilling or unable to give risk managers the loss and claims data they need to do their job more efficiently. It is a problem that has dogged risk managers for years, and for some in the risk management community, the situation is reaching a head.

Does Anyone Have the Information?

One big issue risk managers must overcome when chasing their loss and claims information is specificity, according to Vincent Ohva, vice president and research group director of Stamford, Connecticut-based Gartner Financial Services.

"Risk managers often buy a risk management information system (RMIS) to slice and dice the data so they can run loss projections," Oliva says, "but the historical data they get from insurers isn't very granular, and it makes the risk manager's job very hard."

By granularity, Oliva refers to the specificity of loss data, or in his words, "how deep the data goes." The more granular the data, the more it has been broken down, and the easier it is for a risk manager to pick and choose certain elements and run specific analyses of it.

"Let's say you've got fifteen claims in your packaging division that aggregated one million dollars in reserves and paid losses," Oliva says. "If your loss and claims information is really granular, you can dig down on that information and get not just the total claims and loss figures for your pack, aging division, but within that, the type of each loss, the time it took to settle them, the number of settlements versus judgments and so on. If you're an insurer, broker or TPA, you have to be able to give this kind of data. Just giving summaries won't do risk managers much good."

Sometimes, details are not the problem. An outright lack of useful information is, says attorney Linda Lamel, former CEO of New York-based Claims On Line, Inc. What risk managers know about their loss history is whatever data insurers, brokers and TPAs provide. In some cases, the data made available is virtually useless to the risk manager.

"When I was an insurance regulator, it was usual for auto insurers to use gender and marital status when they rated comprehensive auto insurance," Lamel says. "When the department asked what was the relevance of that data, the insurers admitted there was no causal relationship between that data and any sources of loss, and so they removed them as rating parameters. That always stood out to me. It was something they were able to collect and there were actuaries trying to make rates off of it, but it made no difference."

Another example Lamel offers involves the efforts of New York's governor to reduce the amount of drinking and driving in the state. As a way of drumming up support for the initiative, he decided to show how expensive this kind of behavior was. For that, he went to the state's insurance companies for data on DWI-related losses. …

The rest of this article is only available to active members of Questia

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
One moment ...
Default project is now your active project.
Project items

Items saved from this article

This article has been saved
Highlights (0)
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

Citations (0)
Some of your citations are legacy items.

Any citation created before July 30, 2012 will labeled as a “Cited page.” New citations will be saved as cited passages, pages or articles.

We also added the ability to view new citations from your projects or the book or article where you created them.

Notes (0)
Bookmarks (0)

You have no saved items from this article

Project items include:
  • Saved book/article
  • Highlights
  • Quotes/citations
  • Notes
  • Bookmarks
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Cited article

Show Me the Data! Good Data Management Leads to Even Better Risk Management. but Risk Managers Seeking Their Company's Loss and Claims Data Often Find That Their Broker, Insurer or TPA Is Either Unable or Unwilling to Share Information. the Resulting Tug-of-War Is Enough to Leave Risk Managers Shouting
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

Help
Full screen

matching results for page

    Questia reader help

    How to highlight and cite specific passages

    1. Click or tap the first word you want to select.
    2. Click or tap the last word you want to select, and you’ll see everything in between get selected.
    3. You’ll then get a menu of options like creating a highlight or a citation from that passage of text.

    OK, got it!

    Cited passage

    Style
    Citations are available only to our active members.
    Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

    1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

    Cited passage

    Thanks for trying Questia!

    Please continue trying out our research tools, but please note, full functionality is available only to our active members.

    Your work will be lost once you leave this Web page.

    Buy instant access to save your work.

    Already a member? Log in now.

    Oops!

    An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.