Watch Webinar: http://bit.ly/1olR8gO Listen to Podcast: http://bit.ly/1mJJLAp Using semantic analysis to extract hidden textual insights Experts estimate insurance fraud reaches as high as $5 billion each year. To stay ahead of the game, Insurance companies must be positioned to detect early warnings of fraud to curb financial losses. Attensity’s James Purchase, VP of Product Management and Kevin Mulcahy, Head of Business Analytics Solutions at Tata Consultancy Services discuss the benefits of unstructured claims analytics and the untapped opportunities available by surfacing early signals of fraudulent activities. Learn: · the current market climate for insurance businesses · recovery opportunities in subrogation · use cases of fraud detection using unstructured analytics · benefits and elements of a social fraud radar

1. Surfacing Early Fraud Indicators for Insurance
Companies
Using Semantic Analysis to Extract Hidden Textual Insights

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Today’s presenters
James Purchase
VP, Product Management
Attensity
Kevin Mulcahy
Head of Business Analytics Solutions
Tata Consultancy Services

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Agenda
» The Importance of Advanced Analytics
» Current Insurance Market Climate
» Use Cases for Fraud Detection
» Social Fraud
» Recovery Opportunities in Subrogation
» Expected Business Benefits

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Advanced analytics
» Many organizations are moving beyond traditional BI reporting, descriptive analytics and
diagnostic analytics to advanced analytics, such as predictive modeling, clustering, affinity
analysis and optimization
» 70% use descriptive and 30% use diagnostic analytics, 16% use predictive analytics, 3%
use prescriptive analytics
Source: Gartner 2014

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Insurance fraud problem
» 10% of all P&C claims are fraudulent –
representing over $30 Billion of cost to the industry
» Industry best practice finds fraud in 1 to 3% of
claims
» Average claim settlement times are too long,
driving loss and adjustment expense higher
» The Claim Adjuster workforce is aging: 70% is over
45 years old – knowledge and experience
is leaving the industry
» Specialization has limited the breadth of claim
adjuster knowledge
» A high percentage of all claims involve
unstructured data and manually intensive analysis
Fraud
Detection
10%
0%
All Claims
Fraud
100%
1 to 3%
Sources: NICB, NAIC and Coalition Against Insurance Fraud

6. » Insurers that adopt a comprehensive, cross-functional enterprise data analytics strategy in
2014 are likely to outperform those carriers with more fragmented approaches
– Pool internal data and relevant external data into one logical place, and look for known and
uncover unknown patterns of fraud
– Correlate the resulting high-priority alerts across monitoring systems to detect patterns of abuse
and fraud
– Profile accounts, members or other entities, and look for anomalous transactions against those
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How do insurance companies address fraud issues?
Source: Gartner 2014
profiles

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How we help
Deliver enterprise class analytical and engagement applications that
enable users to:
create a corporate “radar” to
discover, identify and understand
threats & opportunities
make strategic decisions based on
deep insights
Benefits: Helps companies protect brand equity and manage operational execution
and corporate intelligence

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Use Case: Improving detection of fraudulent claims

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Use Case: Improving detection of fraudulent claims

10. Scoring Models and Dictionaries
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Use Case: Improving detection of fraudulent claims
Intelligent
Workflow
All claim
data is
fused
together
» Workers Comp
» General Liability
» Auto
» Property
All claims
are
analyzed
and scored
Scored
claims are
assigned to
1 of 4 tiers
» Claims Database
» Text Sources
» Internet Content
» Imaged Content
» Email
» Social Media
» 3rd Party Data
» Fraud
» Subrogation
» Business Rules
» Claim Filters
Straight
Through
Processing
Appropriate
Claim
Examiner
SIU
Subrogation
Unit
Supervisor
Patent Pending at USPTO & EPO

11. Scenario: Commercial Auto Claim
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Domain specific linguistics
Domain Specifics
Concept: soft tissue injury
stress, strain, sprain, swelling, soft, tissue,
injury, contusion, bruise, etc.
Indicator: combines concepts
» Soft tissue injury
» Involved attorneys send disinformation
» Individual names as lien holders
» Insured or claimant vague on details
» Claims Database
» Text Sources
» Internet Content
» Imaged Content
» email
Actionable
Claims
Key Enablers
» Knowledge Engineering
» Domain-specific taxonomies

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Identifying fraudulent/subrogation claims
Score
Actionable
Claims
No Suspicion or
Subrogation Opp.
High Suspicion or
Subrogation Opp.
Tier 1 no suspicion or subrogation opportunity and
should be fast tracked
Tier 2 minimal signs of suspicion or subrogation
opportunity and may require analysis
Tier 3 stronger signs of suspicion or subrogation
opportunity and should be analyzed
Tier 4 high suspicion or subrogation opportunity and
should be referred to SIU/subro unit
Highly Configurable
- all parameters are user controlled
Fused Claim Records:
Claims enter the funnel using filtering options
to identify claims to be processed
Tier 1
Tier 2
Tier 3
Tier 4

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Social fraud radar
» A claimant(s) may have submitted a “slip and fall” claim implying that the claimant is
somewhat incapacitated (e.g. broken leg)
» Attensity can initiate a social media search to identify potential claimant matches

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Social fraud radar
» Attensity performs a search against
Twitter using the name and location
attributes
» Attensity brings back all claimant
candidates matching the search with
profiling information
» Attensity identifies a likely “target”
claimant
» User could potentially select alternative
candidates

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Social fraud radar
» Attensity pulls back tweets associated with selected claimant, analyzes tweets using its own
Natural Language Processing (NLP) and identifies “material inconsistencies”, ex: running,
swimming…
» User experience can be optimized to report/alert on material inconsistencies

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Relationship with Dr #2
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Provider fraud example – Misdiagnosis for financial gain
Claimant #1
Active pursuits
Diagnose
Claimant #2
Replay Data for claim insights
associated with Dr #2
1. Claimant #1 reports “slip and
fall”
2. Claimant #2 also reports “slip
and fall”
3. Dr #1 exaggerates claim for
claimant #1
4. Track activities of claimant #1
in Social Media
5. Dr #2 has professional tie to
Dr #1 and same misdiagnosis
6. Replay data
Dr #1

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Use Case: Accurate identification of subrogation

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Use Case: Accurate identification of subrogation

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Expected business benefits
Fraud Detection
 Identify and categorize suspicious claims more
accurately and earlier in the claim lifecycle
 Increase quantity and improve quality of SIU
referrals
STP - Claim Routing
 Quickly route claims with low or no suspicion and
subrogation opportunities to expedite processing
 Reduce claim handling costs
 Improve customer satisfaction
Subrogation
 Identify subrogation opportunities more accurately
and earlier in the claim lifecycle
 Score and categorize opportunities based on
amount, likelihood of success and projected effort
 Increase identification rate and average
opportunity value
Claim Severity
 Reduce claim severity by analyzing unstructured
claim data
 Improve loss ratio and reserve accuracy
Underwriting
 Use claim analytics to improve risk selection and
identify fraud earlier in the process

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About Attensity and Tata Consultancy Services
Tata Consultancy Services (TCS)
Tata Consultancy Services is an IT services, consulting and
business solutions organization that delivers real results to
global business, ensuring a level of certainty no other firm
can match.
TCS offers a consulting-led, integrated portfolio of IT and IT-enabled
infrastructure, engineering and assurance services.
This is delivered through its unique Global Network Delivery
ModelTM, recognized as the benchmark of excellence in
software development. A part of the Tata Group, India’s
largest industrial conglomerate, TCS has a global footprint
and is listed on the National Stock Exchange and Bombay
Stock Exchange in India.
Attensity
Attensity is a leading provider of corporate insight
solutions based on proprietary data contextualization
for Global 1000 companies. As a pioneer in natural
language processing and sentiment analysis, Attensity’s
solutions identify relevant and accurate information from
multi-channel data sources using highly sophisticated and
patented semantic technologies, analytics and context
based discovery.
Using Attensity’s integrated solutions, enterprise companies
can interpret and “understand” massive amounts of structured
and unstructured data from many different sources, thereby
helping to improve the customer experience, manage brand
equity, enhance revenue, mitigate business risk, and help
inform business
strategies.
www.attensity.com
For more information, visit us at www.tcs.com

21. More Questions?
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Thank You!
Questions?
info@attensity.com