• Customer experience: Efficiently
managing data to provide agents with
real-time access to pertinent information to expedite resolutions.
A better use of time and
Putting talented claims adjusters on the
task of compiling information is not an
optimal use of time; machines work faster and yield greater results at significant
savings. To envision the impact in terms
of cost-benefit and user satisfaction, consider the following examples.
According to the National Insurance
Crime Bureau (NICB), insurance fraud
ranks second to tax evasion as the costliest white-collar crime. The FBI estimates that more than $40 billion is lost
to insurance fraud annually, not counting health insurance fraud, costing U.S.
families upwards of $700 per year in increased premiums.
Fraud comes in many forms through
many avenues, including individuals,
businesses and crime rings, involving
professionals such as doctors, lawyers,
pharmacists, supervisors and other credible employees. The level of sophistication
among fraudsters is high. As quickly as
investigators unravel one scam, new ones
hatch, creating a dangerous dynamic that
costs carriers and customers alike.
Armed with accurate data at the right
time, carriers can identify potential fraud
through clever referral models that pri-oritize relevant cases for investigation.
Uncovering complex patterns of known
or suspected fraud, using historical records, social media, overlooked details
and other background information can
help identify suspicious individuals or
groups that present previously identified
negative behavioral traits or patterns.
At the operational level, the ability to ef-
fectively triage incoming cases for referral
to the right adjuster not only streamlines
workflow, optimizes assignments and
expedites resolution, it can significantly
lower costs by avoiding overpayment and
possible litigation. Analytics models can
be created to look at the nature of a claim,
past data, organization skill set, injury
type, severity and other factors to iden-
tify the appropriate resource to manage
Highly skilled resources, such as nurs-
es or engineers, can be reserved for spe-
cial cases, taking into account current
bottlenecks and availabilities that ensure
the best resource is on any given case.
This can result in more intelligent and
economical treatments in the case of
healthcare claims, or less expensive ma-
terials and supplies in property damage
claims, significantly reducing payout. It is
typical to see annual claims payouts drop
as much as 15% annually where predic-
tive analytics is employed.
Assigning low-level clerical work to
automated workflows and robots will allow talented adjusters to apply their experience, training and skills to solve critical
claims and risk issues at a higher level of
Putting advanced automation
The road to creating an operationally valid predictive analysis capability involves
customizing machine learning technology around a rules-based business model.
Machine learning describes the ability
of a computer to recognize patterns and
apply computational theories to simulate
human-like intelligence. Customizing a
rules-based machine learning business
model relevant to claims and risk man-
agement decisions is essential to utilizing
As you go about configuring a solution
for your organization, examine the full
claims lifecycle to identify areas where
machine learning or robotic intervention
could reduce manual labor or errors, un-
cover overlooked opportunities, create
efficiency, enhance agent effectiveness or
improve customer satisfaction.
Companies that do not have the in-house resources to implement a tailored
predictive analytics solution can utilize
a partner to compress the time, cost and
disruption of building their own solution.
The partner should have a proven implementation methodology and a track
record of working with similar types of
The benefits of predictive
Given the combined state of today’s digital business environment and modern
analytics technology, there is no reason
for talented claims personnel to perform
tasks better suited for machines. Let robots perform robot duties, while you empower your people to improve expense
ratios, loss ratios, operating ratios and
Sean Allen ( firstname.lastname@example.org)
is vice president of EXL and a leader with
over 18 years of business development
and strategy experience in the BPO and
Putting talented claims adjusters on
the task of compiling information is
not an optimal use of time; machines
work faster and yield greater
results at significant savings.