Fraud Detection and Deterrence in Workers CompensationRichard A. Derrig, PhD, CFEPresident Opal Consulting, LLCVisiting Scholar, Wharton School,University of Pennsylvania

PCIA Joint Marketing and Underwriting SeminarMarch 18-20, 2007

Insurance Fraud- The ProblemISO/IRC 2001 Study: Auto and Workers Compensation Fraud a Big Problem by 27% of Insurers.CAIF: Estimation (too large)Mass IFB: 1,500 referrals annually for Auto, WC, and (10%) Other P-L.

Fraud DefinitionPRINCIPLES

Clear and willful act Proscribed by law Obtaining money or value Under false pretenses

Abuse: Fails one or more Principles

HOW MUCH CLAIM FRAUD?

(CRIMINAL or CIVIL?)

10%Fraud

REAL PROBLEM-CLAIM FRAUDClassify all claimsIdentify valid classesPay the claimNo hassleVisa ExampleIdentify (possible) fraudInvestigation neededIdentify gray classesMinimize with learning algorithms

Company Automation - Data MiningData Mining/Predictive Modeling Automates Record ReviewsNo Data Mining without Good Clean Data (90% of the solution)Insurance Policy and Claim Data; Business and Demographic DataData Warehouse/Data MartData Manipulation Simple First; Complex Algorithms When Needed

DATA

Computers advance

Experience and JudgmentArtificial Intelligence SystemsRegression & Tree ModelsFuzzy ClustersNeural NetworksExpert SystemsGenetic AlgorithmsAll of the Above

FRAUD IDENTIFICATION

POTENTIAL VALUE OF AN ARTIFICIAL INTELLIGENCE SCORING SYSTEMScreening to Detect Fraud EarlyAuditing of Closed Claims to Measure FraudSorting to Select Efficiently among Special Investigative Unit ReferralsProviding Evidence to Support a DenialProtecting against Bad-Faith

Implementation Outline Included at End

CRIMINAL FRAUD?

(Massachusetts)

MASS INSURANCE FRAUD BUREAU

PRIVATE INVESTIGATIVE AGENCY, WORKING WITH AG, DAs, DIA

FORMED IN MAY 1991 BY STATUTE, STRENGTHENED FOR WC IN DECEMBER 1991

RECEIVES REFERRALS FROM INSURANCE COS., EMPLOYERS, THE PUBLIC, AND LAW ENFORCEMENT

ALL LINES OF INSURANCE

BUDGET FUNDED BY AUTO AND WC INS. COS.

Prosecution Study Mass. IFB Data 1990-200017,274 Referrals; 59% auto, 31% wc, 35% accepted for investigation.3,349 Cases, i.e. one or more related accepted referrals.552 Cases were referred for prosecution;293 cases had prosecution completed.

Prosecution Study Mass. IFB Data 1990-2000Case Outcomes: No Prosecution (CNP)

Prosecution Denied (PD), Prosecution Completed (PC) Auto Cases: 1,156 CNP,50 PD,121PCWC Claim: 524 CNP,40 PD, 82PCWC Premium: 70 CNP, 9 PD, 34PC

Subjects Prosecuted543 subjects were prosecuted399 were claimants/insureds65 were insureds only46 were professionals associated with the insurance system as company personnel or service providers

Prosecution FindingsGuilty or Equivalent 84%Pled Guilty 55%Continued without a Finding 19%Not Guilty 8%Not Disposed (Fled) 3%Other (e.g. filed) 5%

SentencesJail 205/471(44%)Jail to Serve 88/205 (43%)Probation 292/471 (62%)Restitution 272/471 (58%)Fines 175 (37%)Professionals have most Jail (59%) and most Jail to Serve (44%)

Source: Table 5

Sentencing Outcomes IISee Figure 5, p92 of PaperJail Time (to Serve) in months:Insured/Claimant 18.7 (12.9)Insured Only 25.0 (22.6)Professionals 24.7 (8.8)All 19.5 (13.1)IFB Sentences consistent with 1996 countrywide fraud convictions.

FraudstersPrior Convictions 51%Prior Property Conviction 9.6%Subsequent Offenses 29% +Subsequent Offense Prior to End of Fraud Sentence 19% + Conclusion: These are general purpose criminals not career insurance fraudsters!

Criminal Fraud DeterrenceGeneral Deterrence Mixed resultsSpecific Deterrence Good ResultsBig Deterrence There is nothing comparable to the Lawrence Deterrent

Insurance Fraud Bureau of Massachusetts2003 Lawrence Staged Accident Results In Death

IFB Joined w/Lawrence P.D and Essex County DAs Office to form 1st Task Force

Insurance Fraud Bureau of MassachusettsResults 2005-2006 Total Cases referred to Pros.244 Total Individuals Charged528

20052006Case Referred to Prosecution70117Total Individuals Charged155248

TYPES OF FRAUDWORKERS COMPENSATION

Employee Fraud

-Working While Collecting -Staged Accidents -Prior or Non-Work InjuriesEmployer Fraud

-Misclassification of Employees -Understating Payroll -Employee Leasing -Re-Incorporation to Avoid Mod

NON-CRIMINAL FRAUD?

NON-Criminal Fraud Deterrence Workers CompensationGeneral Deterrence DIA, Med, Att Government OversightSpecific Deterrence Company Auditor, Data, Predictive Modeling,

Employer Incentives (Mod, Schd Rate)Big Deterrence None, Little Study, NY Fiscal Policy Institute (2007)

CA SIU Regulations (2006)

FRAUD INDICATORSVALIDATION PROCEDURESCanadian Coalition Against Insurance Fraud (1997) 305 Fraud Indicators (45 vehicle theft)No one indicator by itself is necessarily suspicious.Problem: How to validate the systematic use of Fraud Indicators?

Underwriting Red FlagsPrior Claims History (Mod)High Mod versus Low PremiumIncreases/Decreases in PayrollChanges of OperationLoss Prevention VisitsPreliminary Physical Audits Check Yellow PagesCheck Websites

Claims Red FlagsDescription of Accident vs. Underwriting Description of OperationDescription of EmploymentLength of Services/SupervisorPayKind of WorkCopies of Payroll ChecksClaims vs. Payroll

Auditing Red Flags

Be Aware of Prepared DocumentsCheck Original FilesCheck Loss ReportsCheck Class DistributionEstimated Payroll Compared to Audited PayrollPrior ClaimsChanges of Operations

POLICYEstimated PremiumAudited /Adjusted Premium

WORKERS COMPENSATION PREMIUM TERMINOLOGYPayroll - All CompensationClassification Rate - Based on Type of Job (Risk of Injury)Mod - Multiplier Based on Claims History

WORKERS COMPENSATION PREMIUM FORMULAPayroll x Classification Code x Experience Mod

TYPES OF PREMIUM FRAUDPayroll MisrepresentationClassification MisrepresentationModification Avoidance

Case Study Lanco ScaffoldingLanco RepresentationsSmall scaffolding operationLimited accounting recordsOutside accountant prepared and possessed tax recordsPremium of $28,000

Lanco Scaffolding, Inc.

Chart4

1984000

1660000

294500

831000

Lanco Scaffolding Payroll Scheme Financial Impact

Old

$ Paid$ OwedWC PaidWC Evaded

WC$225,282$2,209,217$28,052.00$222,558.00

IRS$145,000$256,000$28,879.00$303,926.00

DOL$153,000$326,000$39,003.00$274,575.00

$30,019.00$294,303.00

$28,486.00$282,971.00

$35,804.00$272,090.00

$35,039.00$333,512.00

$225,282.00$1,983,935.00$2,209,217.00

Old

$ Paid

$ Owed

Lanco Scaffolding Payroll Scheme Impact

New

WC$1,984,000.00

Labor Union$1,660,000.00

Carpenter's Union$294,500.00

IRS$831,000.00

New

Lanco Scaffolding Payroll Scheme Financial Impact

New (2)

WC$1,984,000.00

Labor Union$1,660,000.00

Carpenter's Union$294,500.00

IRS$831,000.00

New (2)

Lanco Scaffolding Payroll Scheme Financial Impact

Sheet2

Sheet3

AUDIT PROCESSAuditor spends 2-3 hours on site, reviewing records provided by the insured (payroll, tax records, jobs)Auditor compares these with insurance records (claims history, prior audits, loss prevention reports)

INSURANCE RECORDSAudit Reports

-Work Papers-Supporting Documents from InsuredClaim/Loss RunsUnderwriting Documents

-Agent-InsuredLoss Prevention Reports

BAD AUDIT

GOOD AUDIT

SIU INVOLVEMENTWhat is the Issue?Referrals can be OptimizedReview Company FilesSurveillanceInterview AgentInterview InsuredInteract with Fraud Bureau

REFERENCESCanadian Coalition Against Insurance Fraud, (1997) Red Flags for Detecting Insurance Fraud, 1-33.Derrig, Richard A. and Krauss, Laura K., (1994), First Steps to Fight Workers' Compensation Fraud, Journal of Insurance Regulation, 12:390-415.Derrig, Richard A., Johnston, Daniel J. and Sprinkel, Elizabeth A., (2006), Risk Management & Insurance Review, 9:2, 109130.Derrig, Richard A., (2002), Insurance Fraud, Journal of Risk and Insurance, 69:3, 271-289. Derrig, Richard A., and Zicko, Valerie, (2002), Prosecuting Insurance Fraud A Case Study of the Massachusetts Experience in the 1990s, Risk Management and Insurance Review, 5:2, 7-104Francis, Louise and Derrig, Richard A., (2006) Distinguishing the Forest from the TREES: A Comparison of Tree Based Data Mining Methods, Casualty Actuarial Forum, Winter, pp.1-49.Johnston, Daniel J., (1997) Combating Fraud: Handcuffing Fraud Impacts Benefits, Assurances, 65:2, 175-185.Rempala, G.A., and Derrig, Richard A., (2003), Modeling Hidden Exposures in Claim Severity via the EM Algorithm, North American Actuarial Journal, 9(2), pp.108-128.