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Visual Analysis For Insurance Fraud Detection and Investigation Valerie A. Zicko CCA, CFE.

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Presentation on theme: "Visual Analysis For Insurance Fraud Detection and Investigation Valerie A. Zicko CCA, CFE."— Presentation transcript:

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2 Visual Analysis For Insurance Fraud Detection and Investigation Valerie A. Zicko CCA, CFE

3 Agenda F Finding Good Claims Data F The Analytical Process F Visual Analysis F Visual Analysis And Visual Mining Software F Examples of Visual Analysis F Pros and Cons of the The Software

4 Keys to Successful Analysis

5 Finding Good Claims Data F Finding Related Claims is the Heart of Case Investigation and Fraud Detection F Claims Databases are the Most Effective Tool for Finding Claims

6 Finding Good Claims Data F Their Effectiveness is Directly Related to the Quality and Completeness of the Database –Multiple identifiers for a person: Name, SSN, DOB, Address –Properly formatted address –SSN preferably a verified SSN –Service providers

7 F Is the process of adding meaning to collected information F Requires going beyond the facts

8 Connect all the dots by using only three lines

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12 As a Result of the Analytical Process We: F Identify what is known F Develop a hypothesis F Formulate a collection plan for the missing information F Develop leads for further investigation or research

13 The Hypothesis or Theory includes KKey Players WHO? CCriminal ActivitiesWHAT? MMethod of OperationHOW? GGeographical ScopeWHERE?

14 SAMPLE HYPOTHESIS: A group of claimants from Watery Mills, including Merry Hider, I.M. Pompous, and Daffy Von Flake, are staging accidents. Daffy Von Flake is steering the claimants to Dr. Frank N. Stein, who is providing treatment and medical bills to support PIP/BI claims for non-existent injuries. Confidence Level: Somewhat confident

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16 Visual Analysis F Examine the data in terms of entities (fields) and relationships to discover or verify patterns, relationships and anomalies. F Visual cues are used to graphically depict the relationships an entities. F Operates at the detail/transaction level

17 An Everyday Visual Chart

18 Visual Analysis F Proactive –Seeks Out Patterns From Unrelated Data –General to Specific F Reactive –Seeks Additional Patterns in Related Data –Specific to General

19 Visual Analysis - Proactive F Large Segments of Analyzed to Discover Patterns –Claims for a Time Period –Claims for Geographic Area –Specific Claim Types F Subjects for Further Analysis May Emerge

20 Visual Analysis - Reactive F Specific Entities Are Targeted for a Drill Down Analysis. –From a Pattern Analysis –From a Suspicious Claim F Related Records Are Fed to the Analyzer

21 Visual Analysis Software F ALTA Analytics - NETMAP™ F Harlequin - WATSON™ F I2 - ANALYST’S NOTEBOOK™ F Winshapes - CASELINK™

22 ALTA Analytics - NETMAP™ F NETMAP for Claims F Works with your corporate database F NICB, AISG interface F Works on normal Ins. Link types F www.altaanlytics.com F Big Bucks -6 figures

23 Harlequin - WATSON™ F Database + Chart Generator F Import your data F Pre-defined links F PC based F www.harlequin.com F Suite of programs F $1,000 to $15,000 per User

24 I2: ANALYST’S NOTEBOOK™ F Chart Generator F Reads your database for charts F User Specified links F Suite of programs F www.I2.co.uk F PC based F $5,000 to $8,000 per User

25 Winshapes - CASELINK™ F PC Based F Database + Chart Generator F Predefined Links F Designed for SIU F www.winshapes.com F $795 per user

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30 Visual Analysis Benefits F Links types are pre-defined by software F Enter data once - generate multiple charts F Auto update as new info added F Source data linked to chart F Can process large amounts of data F Data mining is intuitive

31 Visual Analysis Disadvantages F Can Be Limited to Pre-defined Links F Auto-generated Charts Can Look Like Dish of Spaghetti F Learning = Time + Effort F Program Makes Decisions. You Must Know How to Ask to Get the Desired Results. F Non-standard Situations Are Forced

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33 Summary F Analytical methods help see beyond the obvious facts F Computer tools can make analysis easier and faster F Visual analysis software permits larger amounts of data to be analyzed more quickly F Visual analysis displays information in a graphical manner which aids clarity. F Nothing replaces digging for the facts.


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