In a down economy, insurance fraud is on the increase, but companies such as Allstate, Erie Insurance and CNA tune their technology to fight fraud and organized crime.
Insurance Networking News, August 1, 2012
The numbers are huge: an alleged $297 million insurance fraud case, with 36 defendants, including 10 licensed doctors, three attorneys, 22 medical professional corporations, and eight members and associates of a criminal organization. All charged with offenses related to the single largest alleged no-fault auto insurance fraud case ever, and the first to include alleged violations of the Racketeer Influenced and Corrupt Organizations Act (RICO), which have been filed against the eight.
According to the U.S. Attorney's office, from at least 2007, the 'No-Fault Organization' is said to have defrauded auto insurance companies by creating and operating medical clinics that provided unnecessary and excessive treatments to take advantage of the no-fault law.
While charges are still pending, the No-Fault Organization case is extraordinary because it's indicative of the increasing sophistication and pervasiveness of insurance fraud, which is on the rise. According to the latest statistics from the National Insurance Crime Bureau, the number of questionable claims in 2011 increased 9 percent to 100,201, from 91,652 in 2010, which was an 8-percent increase from the 84,845 questionable claims reported in 2009.
Insurance fraud costs the U.S. property/casualty industry an estimated $40 billion to $120 billion per year, says Stephen Applebaum, senior analyst, property/casualty insurance at Aite Group. "It's hard to measure money that leaks out when you don't know where it goes," he explains. "But in an industry that only generates $495 billion annually, it doesn't matter whether it's $40 billion or $120 billion, it's too much."
But, as fraudsters become more organized and methodical in their methods, so too are insurance companies. To detect fraud, insurers such as Allstate, CNA, Erie Insurance and others are employing a raft of technologies-from rules-based analytics included in policy administration and claims systems, to predictive analytical models that scour internal databases, free-form text and external databases, and now social media sites-to identify patterns and anomalies indicating organized and sometimes massive fraud, for review, investigation and potential prosecution.
"About 18 months ago, Allstate drew a line in the sand," says Frank Llende, senior manager, Allstate innovation and field support. In addition to filing a $29.9 million lawsuit against the No-Fault Organization's defendants, the insurer is keeping an eye out for other fraud. "This is organized crime. We were convinced that there's got to be a way to identify anomalies, trends and aberrant behavior among organized and connected individuals. We need to be able to see who they are, what their behaviors are, and confront them as quickly as we possibly can and get this information into the hands of law enforcement and send these people to jail."
Use of Tools
The industry has come a long way. In the old days, the claims process was linear. "Every phone representative would take every claim in exactly the same way and pass it along to another unit that decided which claims unit needs to be assigned to it," Applebaum says.
Claims adjusters were then left to identify red flag fraud indicators on their claim files. Claims that accumulated enough red flags then were referred for investigation. The problem was that some adjusters are better at recognizing fraud, and as a result many referrals could originate from a small number of adjusters. The company also couldn't know how much fraud was missed.
Rules-based and predictive analytics can be used to detect fraud much earlier in the insurance lifecycle. When a policy is written, for example, companies now are able to access external databases to locate undisclosed drivers, such as spouses and children who share an address; access driving records and police reports; or find whether a driver has been dropped from a previous insurer, all common opportunities for fraud.
At first notice of loss, they can help an insurer beat the clock on paying claims. "The questions go: 'Were you injured? Yes. Was anyone else injured? Yes.' And in the background, the analytics engine is working: 'We've got a bodily injury and a third-party bodily injury. We are going to rout this claim to unit 1-A, because that's the unit that is highly skilled with third-party bodily injuries,'" Applebaum explains. "What the analytics have done is put the claim in the hands of the people best trained to handle it, compressed the claims cycle by days and increased the customer satisfaction level, because the policyholder is getting treatment and satisfaction in a shorter period of time."
Rules-based systems score claims based on an accumulation of red flags from data in claims and policy admin systems, explains David Rioux, VP and manager of the corporate security department for Erie Insurance. In and of themselves, each flag may be innocuous, but as the claims file develops and more data is added to it, claims that collect enough red flags are then reviewed and potentially investigated.
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