Loss Data Management: Crystal Ball For RMs
In todays challenging economic climate, successful businesses recognize that one of the best ways to control expenses is to manage risk. By identifying loss trends, a company can instill measures to reduce its losses.
As a company grows in size and complexity, however, the task of spotting those trends becomes ever more daunting. A bank might want to analyze trip-and-fall incidents for its branches, while a trucking fleet operator might wish to track losses by location and driver.
A global manufacturer, on the other hand, might need to cross reference workers compensation claims by the type of injury, by state or region, by division, or even by a specific piece of machinery at a certain time of day.
Insurance carriers and brokers have developed powerful risk information management tools to help companies of all sizes track and analyze loss data. One of these sophisticated loss data management systems can be a risk managers crystal ball, allowing them to spot trends early and develop strategies to reduce losses and overall costs. This active approach to managing risk can reduce losses for insureds and their carriers.
Since the early 1990s these tools have grown in sophistication from data collection systems, which required managers to sift through reams of paper to identify trends, to todays Internet-based systems that provide in-depth analysis.
These powerful systems, which may range in cost from $10,000 to $50,000 per year, benefit a business of any size. While middle-market and larger businesses may benefit the most, smaller businesses can also benefit from tracking losses with simpler means.
Typically, sophisticated loss data management systems are used to track frequency claims in areas such as workers compensation, general liability and commercial vehicle coverage. The newer loss data tools allow risk managers to cross reference and compare losses by different variables and to drill down to summary or transactional level detail.
For a manufacturer, this might mean tracking the types of injuries from back strains at a warehouse, to carpal tunnel and eyestrain injuries at a home office. Losses in one region can be compared against other regions by the types of injury, where they occurred and the time of day they occurred.
Companies with large deductibles can track reimbursements, where claims have been paid and to whom, as well the status of a claim at any given time.
Besides reducing losses and insurance costs, loss data management tools can have other benefits. Such systems increase accountability by allowing losses to be tracked back to a specific location, operation, manager or employee.
A risk manager of a restaurant chain, for example, could pinpoint a liquor liability problem at a particular outlet. Mid- to large-size companies can use the system as a means of promoting best practices throughout the organization. Setting one standard for all of its operations can help a company with multiple locations maximize risk management efforts, increase productivity and enhance earnings.
With a number of Internet-based data management systems available, companies seeking to invest in such a loss data system should be sure it is tailored to their needs. The system needs to be intuitive and easy to use. A user should be able to manipulate data quickly and efficiently to look for trends. The system should provide the breadth and depth that a company needs, so that it can retrieve detailed information by type of loss as well as compare losses by region or division.
A client who only plans to access information once a month doesnt need to pay for 24-hour access. For companies that need it, there are high-end systems that allow policyholders and producers to access real-time data 24 hours a day through a secured Web site.
Additional key features of a state-of-the-art risk management information system include:
Split security that can restrict access to loss information by user, so that regional managers can view loss data for their region, while a worldwide manager can access all the data.
Scores of selection criteria and ad-hoc capabilities that allow users to create customized reports.
"Push" technology that allows users to establish a regular e-mail schedule for reports and notification of claim activity. A manager can be automatically alerted when a claim crosses a certain threshold, such as $1 million, or when a certain type of injury occurs.
A data conversion service that allows users to have historical loss information from prior carriers, self-insured programs or third-party administrator systems converted to the risk management information system. This ensures that a company does not lose 10-to-20 years of loss data should it change insurance carriers.
A data cleansing service that ensures the accuracy of the data that is being analyzed. For example, do loss codes match cause-of-loss descriptions.
If a company is not properly managing its loss data, it may be missing a valuable opportunity to prevent future losses and save money.
For a company with a sizeable cost of risk, an investment in a loss data management system can translate to substantial savings in the cost that the company ultimately bears.
If a company can prevent losses by trending and mining its data, its risk is significantly reduced up front. In addition, a company that institutes a strong risk management program becomes a better risk for insurers and stands a good chance of receiving more competitive pricing.
From an insurers point of view, an insured looking to improve its loss-tracking systems is a better risk. It is one of those rare cases where both sides do indeed win.
Steven R. Pozzi, managing director and senior vice president, Chubb & Son, and chief underwriting officer for Chubb's Commercial Insurance business unit, is based in the company's Whitehouse Station, N.J., office. He can be reached at spozzi@chubb.com.
Reproduced from National Underwriter Property & Casualty/Risk & Benefits Management Edition, November 7, 2003. Copyright 2003 by The National Underwriter Company in the serial publication. All rights reserved.Copyright in this article as an independent work may be held by the author.
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