of Using Claim
Chances are, by now you have heard a lot of discussions happening around the implementation of claim predictive models and the potential cost savings that can be achieved. However, have you considered the impact on claims handlers as a result of implementing a claims predictive model? In this article, we will focus on the human capital impact of leveraging advanced
analytics in the claims life cycle.
A Balanced Approach To Implementation
By taking the plunge and implementing claim predictive models
(CPMs), claims organizations have started the journey towards identifying and solving organizational problems that exist today, next month
and years down the road. If implemented and used correctly, models
can provide immediate insights and tangible cost savings for the organization. Leveraged effectively at first notice of injury or loss (FNOI/L)
and throughout the lifetime of the claim, advanced analytics can have an
impact on various aspects of the claims lifecycle: claims assignment, special investigative unit (SIU) referral, medical case management, litigation,
subrogation, escalation and, ultimately, claims settlement and outcome.
Much of the discussion around implementing CPMs to date has been
on the technical model building side of the equation, and rightly so. There
is still quite a bit of ‘noise’ across the CPM landscape, however. There are
great differences in capability in this market space from very basic data
mining and analytics to far more complex and statistically advanced predictive models; with hundreds of potential claims data variables, groupings or correlations in play. In fact, the observations described later in
this article are based on actual insights and experience from our having
implemented this more sophisticated type of CPM solution.
Beyond Potential Cost Savings
Claims organizations tend to focus heavily on how implementing claims
predictive models will favorably impact the bottom line. However, one of
the major benefits of rolling out a CPM comes from creating workflow
efficiencies through providing timelier loss insights to claims handlers.
By accelerating critical adjusting decisions and refocusing the composition of their pending workload in a way that better uses their experience
and skills, claim handlers can better focus on the right claims at the right