NEW YORK, Feb. 24, 1998 — The U.S. property/casualty insurance industry has tightened the vise on insurance cheats by moving to build a consolidated all-claims data base.
The National Insurance Crime Bureau (NICB®) Friday transferred its claims and related data bases and software to Insurance Services Office, Inc. (ISO). The NICB data and software will move from Palos Hills, Ill., to ISO's Data Center in Pearl River, N. Y., later this year.
ISO will merge the NICB's vehicle claims data with claims data bases maintained by ISO's American Insurance Services Group (AISG) unit into a single data base containing bodily injury, property, workers compensation and vehicle claims.
ISO will maintain for the NICB its other data bases separately. These contain a variety of vehicle-related data from sources other than insurance companies.
"This agreement marks an historic all-out fight to stem the flow of more than $20 billion a year to cheats who perpetrate fraud," said Fred R. Marcon, ISO's chairman, president and chief executive officer. "We have the commitment, and with an all-claims data base, we'll have a powerful weapon to detect and inform our customers of potential fraudulent claims. Moreover, enhanced technology and software employed by our new systems will accelerate the handling of meritorious claims."
"The integration of the data bases makes the most of the strengths of the NICB and ISO," said John G. DiLiberto, NICB's president and chief executive officer. "The NICB will now refocus our efforts to provide unique solutions to the problems of deterring, detecting and preventing insurance-related crime. What ISO brings to the fight against insurance crime is the ability to manage and analyze the data bases to strengthen earlier detection of fraud."
Under the NICB-ISO data-integration agreement that became effective Friday, ISO will manage data insurers provide to the NICB. The NICB, insurers, and self-insured entities will have access to the data. The NICB will continue to provide access to portions of the data to law-enforcement personnel at no cost to them.
The NICB will continue its long-standing mission by investigating claims referred by member companies, acting as the liaison between the insurance industry and law enforcement, training insurance and law-enforcement personnel in the latest fraud-fighting techniques, educating the public through awareness programs, and assisting in the development of anti-fraud legislation on both the state and federal levels.
ISO has established a claims council drawn from the NICB's board of governors and the AISG's former directors to guide development of the all-claims data base and related services.
"With a single all-claims data base, the industry will benefit from using ISO's proven analytical and technology expertise to analyze claims trends and patterns in new ways," said Marcon.
For example, ISO plans to use techniques such as data mining and link analysis to analyze the massive amounts of data in the combined AISG and NICB data bases. With such techniques, ISO will look across different lines of insurance to identify similarities in claims patterns and other common links in a variety of data.
"Besides increasing the odds of identifying insurance fraud, the all-claims data base will eliminate redundant costs of maintaining separate data bases and reporting data twice," DiLiberto said.
HOW THE CLAIMS DATA BASE FIGHTS FRAUD
In the past, much of an insurance investigator's time was spent physically retrieving information. Using new technology, investigators now "mine" data bases for patterns of prior claims by searching name/address combinations, Social Security numbers or license numbers to detect suspicious patterns that can point up complex fraud cases, such as organized rings. Here are three examples.
1. Incident: A major insurer suspects that staged auto accidents were increasing in the New York area.
Investigation: Identify patterns and trends that isolate organized auto fraud rings. Conduct data-base searches that point up common denominators of organized fraud groups — for example, accidents that involve claims by unrelated people who receive medical treatment from the same provider.
Outcome: 42 cases identified that generated $700,000 in fraudulent claims. Future savings: millions of dollars.
2. Incident: A slip-and-fall injury claimant demands payment of $200,000, hires an attorney, but refuses to disclose her identity, her medical records, or the complete nature of her injury.
Investigation: Use claimant's Social Security number to check data base for past claims. Check reveals claimant has filed 12 bodily injury claims using the same Social Security number but different names. Further data-base mining points up a relationship among the claimant's treating physicians (chiropractors) and attorneys.
Outcome: The insurer, which had offered a settlement before the investigation, withdraws its offer, and the claimant's attorney withdraws from case.
3. Incident: Claimant seeks $220,000, alleging multiple injuries from auto accident have left him unable to work.
Investigation: Data-base check reveals claimant filed a workers compensation claim for the same injuries a few months after the auto accident. Separate check of employment records establishes claimant holds a position with a new employer similar to the position he held when the auto accident occurred.
Outcome: When confronted with these facts, the attorney representing the claimant immediately withdraws the lost-wage claim.