ASKED & ANSWERED

gathered over time. The more analytical the tools, the more chance of detecting fraud in the early stages and predicting potential areas of fraud before the criminals have even uncovered the opportunity. Automation also places less reliance on the human element and provides greater accuracy and fewer false positives to chase down.

Can Big Data
Nix Fraud?
15 minutes with
Stuart Rose

While insurance fraud has steadily bedeviled the industry since its inception, the tools to address the problem have improved markedly in recent years. Now insurers can sift through burgeoning data sets and employ increasingly sophisticated analytics to catch wrongdoers. Insurance Networking News asked Stuart Rose, global insurance marketing manager for Cary, N.C., analytics provider SAS, about how insurers can leverage the latest technologies in fraud detection.

As told to
Bill Kenealy
INN: What will the increas-
ingly large volumes of data
that insurers manage mean
for their ability to detect
fraud?
SR: It could be argued that
the more data available the
easier it is to hide fraud, how-
ever the converse is usually
true. The larger the amount
of data available, the greater
the likelihood of discovering
fraud, especially when insur-
ers go beyond viewing each
claim in isolation and view
claims at an enterprise level.
Today, insurers are begin-
ning to supplement their own
claims information with third
party data, such as National
Insurance Crime Bureau
(NICB) alerts, ISO claims his-
tory, even social media data,
to increase the possibilities of
discovering suspicious activi-
ties. Hence with this increas-
ing volume of data, insurers
need to implement data
management and analytical
software that enables them
to not only detect suspicious
behavior but to prevent future
similar fraudulent activities.

INN: What new analytic ca-
pabilities can help insurers
detect fraud?
SR: At most insurers, the
technology that is currently in
place to support fraud fighting
is a mixture of business rules
and database searches. While
these techniques have proven
successful in detecting known
fraud patterns, today insurers
need to invest in new ana-
lytical capabilities to detect
unknown and complex fraud
activities. These analytical
capabilities include: anomaly
detection, predictive model-
ing, text mining and social
network analysis.

INN: What new types of fraud should insurers be on the lookout for?

SR: The objective of fraudsters is to devise new ways of fraudulently obtaining money from an insurance company that is undetected. Hence predicting new types of fraud is like predicting the lottery numbers. Fundamentally, it is still the same old frauds being committed—it’s just in slightly new ways. One example is the emergence of online application fraud and ghost broking. Online application fraud is similar to rate evasion, the customer or insured alters some information to obtain lower rates, such as “ accidently” transposing the year of birth from 1987 to 1978. “Ghost” brokers work by acting as a “middle man” between the customer and other brokers/insurers and could provide the customer with a fraudulent insurance policy either by insuring incorrect information, or giving the insured a fake insurance policy.

Organized fraud activity, although not emerging, is rapidly increasing, especially with medical providers such as excessive treatment, inflated billing and solicitation. This type of fraud is particularly prevalent in “no-fault” states such as Florida for PIP claims.

Finally, watch for auto glass fraud, as insurers introduce fast track claims processing to settle these claims without adjuster evaluation, the amount of fraud according to the NICB has increased by more than 400%.