7 Identify and remove supplier fraud.
Suppliers represent a significant share
of claims spend, from garages, to doctors, lawyers and accident management
companies. In many cases these are enablers of organized fraud, but they can
also be fraudulent in their own right. By
networking all of the claims around these
entities and then performing a range of
automated analytics such as outlier analysis, consistently anomalous behavior and
identification of links to known frauds
the identification of, what is frequently,
large-scale fraud within the supplier base
can be uncovered.
RED FLAGS FOR ADJUSTERS
At least $80 billion is paid out each year in fraudulent insurance claims. The earlier a
suspicious claim can be flagged, the better chance an insurer has of avoiding unwarranted
payouts. Here are some common indicators that can signal fraudulent activity:
E The insured is overly pushy for a quick settlement.
E Losses are incompatible with insured’s residence, occupation, and/or income.
E The insured is willing to accept an inordinately small settlement rather than document all
E Buildings and/or contents were up for sale at the time of the loss.
E Suspiciously coincidental absence of family pet at the time of fire.
E Building and/or business was recently purchased.
E Building is in deteriorating condition and/or lacks proper maintenance.
E Fire scene investigation reveals absence of items of sentimental value.
8 Prevent fraud from re-entering
Fraudsters are very persistent and once
they have been able to successfully deceive an insurer they will continue their
attacks. By capturing denied claims or
suspects onto the networks of customer
data it is possible to run a match at policy
inception. This can flag any connection of
a new customer to a previous fraudster or
ring of organized crimes and queue that
particular application for exceptional
checks before accepting the application.
The same approach can be used with
third-party known frauds or sanction
lists to prevent money laundering.
E Extensive losses are declared, despite lack of physical evidence, photos, or receipts.
E Items claimed do not seem to match the claimant’s lifestyle, decor, house, or income.
E Investigation reveals absence of family photos, heirlooms or items of sentimental value.
E No other homes were damaged or destroyed in the affected area.
E The insured claims that items were brand new.
E The property was in poor condition prior to loss event.
E The insured claims unrepaired damage from a previous disaster.
Source: Coalition Against Insurance Fraud and Louisiana Department of Public Safety & Corrections
The depth of insight that is obtained
by linking data across lines of business
and through history to produce complete
single views of customer or supplier can
be used for other purposes too. For exam-
ple, policy pricing could be dynamically
adjusted based on risks to improve the
quality of the customer base and market-
ing campaigns can be optimized through
the analysis of cross product adoption or
identification of ‘influencers.’ K
Jamie Hutton is head of the insurance prac-
tice at Detica NetReveal. For more informa-
tion, visit www.deticanetreveal.com.
9 Spot fraudulent brokers and insiders.
Sophisticated fraud rings will often
work through brokers or place insiders
within insurance operations to perpetrate volume fraud. For example, by adding the user ID’s of the staff members
who processed any part of the policy, to
the networks of customer data, it is possible to identify any staff who are showing
strange behaviors or who are overly connected to fraudulent activities.
J Sanctions list checking.
To protect from potential reputational
damage and financial penalties from the
regulators, insurers have to ensure they
operate an effective and auditable sanctions list checking process. By implementing a solution which provides a
‘single view of customer’ it is possible to
effectively confirm an individuals identity and check them against any non-trade
lists and reduce the burden of effective