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| Thought Paper |
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Predictive Analytics and Claims Processing |
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| Abstract |
As competition from other financial service providers and pressures from customers and
regulatory agencies continues to mount, insurance companies are forced to explore ways
to improve operational efficiency and cut costs without sacrificing customer service. For
property casualty and health insurers, improving claims handling efficiency remains a high
priority, since up to 20 percent of insurer expenses can be related to processing claims. A
2002 survey by Accenture revealed that most property casualty claimants prioritize claim
resolution speed over the settlement amount. From the insurer point of view, speeding
settlement reduces both handling costs and loss adjustment expenses, and speedy claims
settlement translates to customer satisfaction - and retention. In fact, improvement in
claims results has a proportionately higher impact on a company's financial performance
than an improvement in any other operational area.
While everyone has a stake in the quick resolution of a claim, insurer losses due to fraud
have risen 63 percent in the last four years. Analysts estimate the annual cost of property
casualty insurance fraud to be at least $44 billion, with studies indicating that 10 to 15
percent of such claims presented in the U.S. are fraudulent.
To identify potentially fraudulent claims without impeding the claims handling process,
insurers are looking at technology options to support investigative and adjuster personnel,
to automate claims handling processes and to create an integrated, real-time claims
operation that ultimately reduces both claims payout and legal expenses. One technology
option now gaining favor within the industry is Predictive Analytics, an emerging market
that is expected to grow as much as $3 billion by 2008.
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