Visual Analysis For Insurance Fraud

Detection and Investigation

Valerie A. Zicko CCA, CFE

Agenda Finding Good Claims Data The Analytical Process Visual Analysis Visual Analysis And Visual Mining

Software Examples of Visual Analysis Pros and Cons of the The Software

Keys to Successful Analysis

T R A IN E D A N A L Y S T

TO O L SD A T A

M ETH O D O L O G Y

Finding Good Claims Data

Finding Related Claims is the Heart of Case Investigation and Fraud Detection

Claims Databases are the Most Effective Tool for Finding Claims

Finding Good Claims Data

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

Is the process of adding meaning to collected information

Requires going beyond the facts

Connect all the dots by using only three lines

Connect all the dots by using only three lines

C o l l e c tIn fo r m at i o n

O r g an i zei n fo r m at i o n

A n a l yzeR e s u l t s

E va l u a t eIn fo r m at i o n

As a Result of the As a Result of the Analytical Process We:Analytical Process We:

Identify what is knownDevelop a hypothesisFormulate a collection

plan for the missing information

Develop leads for further investigation or research

The Hypothesis orThe Hypothesis or Theory Theory includesincludes

Key Players WHO? Criminal Activities WHAT? Method of Operation HOW? Geographical Scope WHERE?

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

Summary: Statistically and through IFB referrals Smith appears to be billing for treatment that cannot be substantiated by documentation. This raises the possibility that no treatment is actually being provided.Referrals that allege treatment of jump-in and staged accident claimants reinforce the possibility that no real treatment is occurringbecause these claimants have not been injured. Further analysis or investigation is warranted. Hypothesis: James Smith is engaging in practices which create sufficient medical bills to exceed the tort threshold for Automobile bodily injury claims regardless of whetheror not they are medically justified.As a result his billing is facilitating unjustified bodily injury claims.

Premise 1: James Smith bills individually or in combination with another medical provider in excess of the tort threshold at a significantly higher rate than the auto PIP claims as a whole. This would tend to indicate that reaching tort threshold is a greatergoal that providing appropriate treatment. As an individual provider Smith billed over the 2K threshold 60% of the time versus 25% of all PIP claims In combination with other providers he billed over the tort threshold 70% of the time versus 45% for all PIP claims. Medical Organizations in which he is an officer and participant experienced similar percentages.

Premise 2: In spite of insurance industry efforts to contain these costs paid medical bills exceed the tort threshold more frequently for Smith and his organization more frequently than for all PIP claims. His high rate of billing over the tort threshold leads to a high rateof payments over 2K in spite of insurance company cost containment efforts.

As an individual provider Smith was paid over the 2K threshold 43% of the time versus 14% of all PIP claims In combination with other providers he was paid over the tort threshold 49% of the time versus 35% for all PIP claims. Medical Organizations in which he is an officer and participant experienced similar percentages.

Cost containment efforts such as Independent Medical Exams, Medical Audits and Special Investigation are reserved for claims with asuspicion level. Any increase over the average in using these methods indicates an increased suspicion level on the part of theinsurance claims personnel. When this is coupled with an average or higher than average percentage of claims that are adjusted basedon the result of the special handling, it is reasonable to assume that the suspicion is justified. [By contrast claims which are selectedfor special handling based on something other than reasonable suspicion would be adjusted less than average.]

Visual Analysis

Examine the data in terms of entities (fields) and relationships to discover or verify patterns, relationships and anomalies.

Visual cues are used to graphically depict the relationships an entities.

Operates at the detail/transaction level

An Everyday Visual Chart

Visual Analysis

Proactive– Seeks Out Patterns From Unrelated Data– General to Specific

Reactive– Seeks Additional Patterns in Related Data– Specific to General

Visual Analysis - Proactive

Large Segments of Analyzed to Discover Patterns– Claims for a Time Period– Claims for Geographic Area– Specific Claim Types

Subjects for Further Analysis May Emerge

Visual Analysis - Reactive

Specific Entities Are Targeted for a Drill Down Analysis.– From a Pattern Analysis– From a Suspicious Claim

Related Records Are Fed to the Analyzer

Visual Analysis Software

ALTA Analytics - NETMAP™Harlequin - WATSON™I2 - ANALYST’S NOTEBOOK™Winshapes - CASELINK™

ALTA Analytics - NETMAP™

NETMAP for Claims Works with your

corporate database NICB, AISG interface Works on normal Ins.

Link types www.altaanlytics.com Big Bucks -6 figures

Harlequin - WATSON™

Database + Chart Generator

Import your data Pre-defined links PC based www.harlequin.com Suite of programs $1,000 to $15,000 per

User

I2: ANALYST’S NOTEBOOK™

Chart Generator Reads your database

for charts User Specified links Suite of programs www.I2.co.uk PC based $5,000 to $8,000 per

User

Winshapes - CASELINK™

PC Based Database + Chart

Generator Predefined Links Designed for SIU www.winshapes.com $795 per user

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Visual Analysis Benefits

Links types are pre-defined by software

Enter data once - generate multiple charts

Auto update as new info added Source data linked to chart Can process large amounts of data Data mining is intuitive

Visual Analysis Disadvantages

Can Be Limited to Pre-defined Links Auto-generated Charts Can Look Like Dish

of Spaghetti Learning = Time + Effort Program Makes Decisions. You Must Know

How to Ask to Get the Desired Results. Non-standard Situations Are Forced

Summary Analytical methods help see beyond the

obvious facts Computer tools can make analysis easier

and faster Visual analysis software permits larger

amounts of data to be analyzed more quickly

Visual analysis displays information in a graphical manner which aids clarity.

Nothing replaces digging for the facts.