Disruptive Technologies to
Combat Insurance FraudJune 17, 2015
Presented by
Shailendra Deo,
Head, Insurance Solutions Group
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Original source for Videos –
— https://www.youtube.com/watch?v=QvsNsWAv-EY
— http://www.cbsnews.com/news/investigators-combing-social-media-to-expose-insurance-
scams/?dbid=562634672845230080&adbpl=tw&adbpr=2340940998&cid=social_20150203_398473870
UNDETECTED FRAUD
IS ESTIMATED TO COST
INSURANCE COMPANIES
BILLIONS IN WRONGFUL
PAYOUTS.
THE CHALLENGE IS TO
COMPREHEND IT!
$
Insurance Information Institute, USIII estimates that fraud costs $29 billion to P/C lines,
$4.3 – 5.8 billion to auto injury settlements and $95 billion
to Healthcare industry every year
National Insurance Crime Bureau, US
NICB estimates that fraud accounts for 10% of the
property / casualty insurance industry’s incurred losses
every year. This costs $300 / household
Coalition Against Insurance Fraud, US
Fraud costs nearly $80 billion annually to US Insurance
Industry and around $950 per family More than one third
of people hurt in auto accidents exaggerate their injuries
National Health Care Anti-Fraud Association, US
Fraud costs nearly $51 billion annually to US
Healthcare Industry
NONE OF THE LINES
OF BUSINESS HAVE
BEEN SPARED BY
FRAUDSTERS.
THERE IS THOUGH A
CONCENTRATION IN
SPECIFIC FEW.
Auto - giveup
Auto - padding / false claim
Auto - staged
Auto - underwriting
Business - arson
Business - padding / faking
Disability
Drug diversion
Fraud - general
Homeowners - arson
Homeowners - fake / padding
Insider - agent
Inside - insurer
Liability - false claim
Life insurance
Medical - false claim
Medicare / Medicaid
Underwriting
Workers comp - employer
Workers comp - provider
Workers comp - worker
Auto, Workers Comp and Healthcare Claims are traditional favourites of fraudsters.
They have also started looking at areas like Marine, Travel and Weather Insurance.
2
44
51
21
66
58
96
73
8230
17
39
31
82
109
121
115
64
159
176
117
Few regions in US are favourite to fraudsters
Cities with the
Most staged Accidents
New York
Tampa
Miami
Orlando
Houston
Los Angeles
Chicago
Hialeah, FL
Las Vegas
Glendale, CA
TO
P10
FloridaTexas
LouisianaMost Disaster
Prone States3
Fraudsters are quick at innovating new ways to deliver results.New patterns evolve while the historical ones are still maturing
Common Interests –
Claimant and Service Providers
Cartoonstock.com
Increasing
Complexity
of Fraud
LAYERS
of Advanced Analytics
While Investingators are
irreplaceable, technology
can enable faster and
accurate investigation
Outlier analysis through use of business rules is a common technique to understand patterns and detect fraud
Suspicious claims
from a particular
repair shop
Fraud in new
policies or policies
about to expire
Anomaly
Detection /
Business Rules
0
20
40
60
80
100
Normal Profile
Abnormal*Activity
Measures
*Probable
Intrusion
Anomaly Detection
Average Claims
Paid / Month
Frequency of
claims / per day
Any Problem?
Relatively high false positive rate
Anomalies can just be new normal activities
Anomalies caused by other elements
─ E.g: Large number of claims on weekend, from a specific repair shop
Predictive Analytics is one of the strong pillars of identifying fraudulent patterns in historical data
Ditching
Past Posting
Misrepresentation
Staged accidents
Vehicle Smuggling
Phantom Vehicles
VIN Switch
Predictive
Analytics WhatHappened? WHY What
Next
BusinessIntelligence
PredictiveAnalytics
Quantifiable ROI
?
Insurers have started looking at text mining to detect fraud through tweets on social portals and information hidden in some of the claim documents
Tweets that do not
match with the claim
information
False location or timing
of accident (social
media)
Inflated damages
(various reports)
Text Mining
Text Data Mining
Text Data Mining
Text
Mining
Predictive
Coding
Tone
Detection Named
Entity
Extraction
Part of
Speech
Tagging
Topic
Mapping
Traditional
Search
Evolution of topics, Interactions, relationships and emotions over time
Prefill data update detection can identify fraudulent intentions right at the source itself
Over writing of
prefilled
information on
online portals
Multiple changes to
description of
information
Prefill Data
Update Detection
Techniques that can bring out hidden relationships through use of internal and external data
Fraud rings
Connections to
known fraudster
Social Network
Analyzer
Confirming true identify
of a person
Identifying relationships
between participants in
multiple claims
Link Analysis
Fraud rings
Duplicate claims
Industry Database
Lookup
Search Match Link Analyze Act
More and more customers are adopting to usage based insurance. This enables insurers to utilize telematics data to detect fraud at the time of accident
Driving Behaviour
Detection
Event Monitoring
Telematics
Some data capable
of being captured
by telematics
systems
Speed,
Acceleration
Battery
Voltage
Aggressive
Maneuvers
MileageFuel Use
Engine
Health
Location
Breaking
Some data capable of being captured by telematics systems
Voice Stress Analysis: A game changer to techniques utilized to detect fraudulent claims at the FNOL stage itself
Speech modulation
and voice stress
analysis
Voice-to-text
conversion and
analysis
Voice recognition
Voice Analysis
Comparison of Emotions of Same Person
in 2 Different Situations
Image & Video Analysis: Disrupting the ways claims executives approve damaged parts and estimate losses
Image morphing
Damaged part
analysis wrt to
accident description
Text recognition
from images
Image & Video
Analysis
While almost all of the fraud detection
solution providers use one or more of
these technology options, Hexaware’s
iFraudEngine enables fraud detection
utilizing all 10 layers of advance analyticsIncreasing
Complexity
of Fraud Predictive Analytics
Text Mining
Prefill data update detection
Social Network Analyzer
Link Analysis
Industry Database Lookup
Telematics
Voice Analysis
Anomaly Detection / Business Rules
Image & Video Analysis
Fraud Engineii
Detect underwriting irregularities and suspicious claims
Leverage information from multiple structured & un-structured,
internal and external data sources
iFraudEngine helped a leading P&C Insurer achieve measurable business benefits
Increased the fraud
detection rate by 2 folds01
Reduced per claim cost by
$250 which led to an annual
saving of $31 Mn
02
Reduced the false positives
to one third which led to
each investigator handling
10 more cases every month
03
Reduced claims and
underwriting leakage thereby
improving profit margins
04
8% claims flagged
as fraudulent
Repair shops from where
lot of low value fraudulent
claims are getting reported
Repair shops from
where lot of low value
fraudulent claims are
getting reported
Thank You
www.hexaware.com
Questions?
Visit Hexaware Booth # 126 for a Solution DEMO
Email Us – [email protected]
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