Although predictive modeling can identify a potentially fraudulent claim faster
than many cases in the past, successful
claims adjusting operations continue to
monitor claims as they progress and flag
them later if certain warning signs appear.
Predictive modeling begins with the
first notice of loss and then continues to
monitor for certain trigger points and
specific actions during a claim’s lifecycle,
such as the number of prior injury claims
submitted by a claimant and the amount
of time that an allegedly injured claimant is out of work. The model flags claims
based on patterns that have historically
proven fraudulent — patterns that a human adjuster often may not detect.
In addition to detecting fraud, predictive modeling can indicate whether
a legitimate claim has the propensity to
develop adversely. It can be used to evaluate the likelihood that a claim will result
in litigation. It may also provide the ability to identify Workers’ Compensation
claims with a greater likelihood of surgery. Such tools allow adjusters to develop case strategies at first notice and gain
control over the claim as it progresses.
Smarter allocation of resources
Despite the wealth of benefits from predictive modeling, the machines are not
taking over. Adjusters are still the critical element in claims management and
The “tool” delivers information that
gets adjusters thinking about fraud and
looking for clues. Modeling does not
prove that a claim is fraudulent; it tells adjusters to look closer. After that, they must
still conduct their claim investigation. For
instance, when predictive modeling registers a claim as highly suspicious, a notice is
forwarded to the SIU, where investigators
triage the claim and determine whether it
should be accepted. Once the SIU accepts
the claim, the SIU and file handler plan
the investigation together, with the claims
handler maintaining ownership over the
When done well, predictive analytics
does more than just inform; it smooths
out the efforts of hundreds of adjusters
across multiple claims offices around the
country. In any given group of adjusters,
some will be more focused on detecting
fraud than others. Predictive model-
ing builds a ground-floor foundation of
awareness so that these differences are
Human beings also have a say in how
the modeling tools are developed, integrated and used. The Chubb Claim Analytics team seeks input from claims professionals and gathers their feedback to
analyze business benefits and to discover
ways to improve existing solutions and
create new ones.
Better reputation management
Most important, predictive modeling can
help create a deterrent to fraud. Police and
other authorities know that fraud perpetrators talk to each other. They share information on insurance companies, down
to particular claims offices and individual
adjusters who are easy “marks.” Predictive
modeling can help insurers send the message that their company’s claims organization is not an easy target for fraud.
At present, predictive modeling is
showing clear signs of success — increased speed, smarter human involvement, financial savings, better reputation
management and continued vigilance.
As the technology is further developed,
it will become better integrated into the
claims process. While many claims today
are still handled manually and in the or-
der they are received, predictive model-
ing will help insurers move even more
toward segmentation. The tools will en-
able SIUs to identify those claims that
are best suited for experienced staff at a
given office, for instance, or those severe
enough to require immediate review,
contact and intervention.
Moving forward, greater success will
also involve the ability to input additional
unstructured data into the modeling systems. Posts on social media, such as those
linking a claimant to known fraudsters,
are examples of information the company
hopes to stream into the systems. Though
the use of such data can be sensitive because it may contain personally identifiable information, it may be possible for
firms to navigate safely around the potential privacy issues. In the near future,
systems will be able to track and match
social media with claims data.
It will be a new age of enhanced claims
management and customer service. But it
still will be a world in which it will be important for an adjuster to spot that broken chair.
Donald Siegrist is vice president of Chubb
& Son and oversees Chubb’s Special
Investigations Unit and its salvage and
subrogation claims operations.
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