Reduce Accidents & Costs through Data Mastery

1. Reduce Accidents & Costs through Data Mastery National Council of Self Insurers Annual Meeting, May 24, 2010 Clearwater Beach, Florida

2. Agenda for the session • Introduction of Speakers and the purpose of the session • Define the scope of the business issues concerning cost explosion and the role of data mastery • Discuss the Fraud mentality, its roots and steps to combat it • Under-utilized Fraud/Abuse compliance and Performance Audits • Organization for data mastery and analytics

3. Use of Insurance statistics for NCSI • The same general business issues concern Self-Insurers and Insurance Companies • Self-Insurers tend to be more advanced than Insurance companies at identifying and controlling risk events • Consequences of missed opportunities and increasing costs are more severe for self-insurers • Self-insurers are more likely to use specialty vendors to provide critical services normally provided by insurance companies

4. Use of relevant, accurate data is key “In the next five years, there will be big winners and big losers in the insurance filed based on the data battle. Early movers will be the winners, they are winning now and if you are not there, you’re losing ground now”. Tom Johnson, Hartford Chief Actuary, 2006 • The essence of a successful strategy is being better prepared to understand what has and will happen. • This need leads to constant demands for additional granularity and agility of data systems • Winning at this game requires good business instincts. Excelling over time requires those instincts to be informed and challenged by intelligent, accurate information

5. Critically Important Business Questions • Where should I focus my management attention? • Where can my team’s efforts produce the greatest amount of positive change in the organization? • How do I benchmark my performance against expectations or my peers? • How do I assess the validity of my past decisions and what do I need to change? • Can I get all the information I need to perform this assessment on any issue or opportunity?

6. Why use Fraud Data? • Most self-insurers have initiated cost-containment policies affecting processes that are known and customary, but fraud is harder to identify and measure. • In a broad sense, fraud is an intentional deception made for personal gain or diminish another person or organization. The chief motive in insurance fraud is financial profit. • For the purposes of this session, we will use these definitions: • “Hard Fraud”: Intentional deception to convince someone that an event or consequence happened when it, in fact, did not. • “Soft Fraud”: Attempt to deceive someone of the extent of the damage or injury arising out of event that actually did happen through exaggeration or lying.

7. Soft Fraud is the Nexus of Cost Explosion • The principal activity of soft fraud is “build-up” (i.e. less treatment than actually given, more disability or pain than actually experienced, etc). • The FBI estimates that US insurance fraud accounts for more than $40 billion a year or between $440-700 per U. S. family • They also estimate that $6 billion of the $80 billion appropriated for rebuilding after Hurricane Katrina was the result of fraud. • Abusive “build-up” in US auto-injury claims added $4.8 billion to $6.8 Billion (13% to 18% of the total) in excess payments in 2007 (Insurance Research Council, Nov. 2008)

8. Additional Fraud Data • Insurance Fraud is second only to tax evasion as the most costly white-collar crime, costing $30 billion a year (National Insurance Crime Bureau) • Over 1/3 of people injured in auto accidents exaggerate their injuries, costing $13-$18 billion a year (Rand Institute for Civil Justice) • WC Fraud costs $5 billion a year (National Insurance Crime Bureau) • Healthcare Fraud alone costs $54 billion a year (Coalition Against Insurance Fraud)

9. So What can Self-Insurers do? • Present and exercise a strong corporate anti-fraud philosophy that is preached by and lived up to by management. • Identify the behaviors that indicate costly or fraudulent behaviors • React publicly to the activities that contribute to those behaviors • Determine measurement criteria and metrics that provide insight into where and when these activities are prevalent. • Determine the data needed to support the metrics and build a database • Secure feeds from all sources (internal and external) to support the analysis (more later in the presentation)

10. Why do so many data store projects fail? • The sequence of activity is incorrect. • Data is extracted and stored from accessible sources • It is stored in hierarchal indexed database that may not be optimized for reporting • Then information and reporting requirements are developed and handed to IT for development • The correct sequence is: • Develop the information and reporting requirements • Identify the data and the level of grain needed • Identify a DB structure that optimizes reporting • Build it, either internally or use an outside product

11. The Fraud Mentality MG (R) Evo Riguzzi

12. Attitudes toward Fraud • Nearly one in four Americans say it’s ok to defraud insurers (Accenture, 2003). About 8% said it is “quite acceptable to bilk insurers”. Two out five people are “not very likely” to report someone who defrauded an insurer. • Nearly 10% of Americans would commit insurance fraud if they knew they could get away with it. (Progressive Insurance, 2001) • 40% of Americans said it was OK to pad a claim to make up for premiums already paid (Insurance Research Council, 2000) • 20% of employed workers say they are aware of fraud in their workplace (Insurance Research Council, 1999)

13. What triggers this attitude • Reciprocity: They’re stiffing us, so I am stiffing them • Anonymity: Everyone is doing it so I am not likely to get caught • Fear of Consequences: or rather, the lack thereof. Most insurance fraud is not severely punished, little or no serious jail time. • Everyone gets off easy: Employers want to take criminal action; prosecutors are less willing to take them on and civil actions are too expensive.

14. Additional Triggers • Organized Crime Activity.

15. Fraud and Build-Up Consequences • Company Consequences • Public Consequences This is an education process for all, employees and management.

16. Under-Utilized Fraud/Abuse Compliance & Performance Audits Michael Koss

17. TPA/Self-Administered Compliance • Assess Adjudication Process • Confirm proper provisions are being administered • Assess timeliness and accuracy of benefit payments/denials (including medical) • Assess internal controls of approval, data integrity • Confirm that claims are documented for priors • Verify recorded statements and transcriptions for witnesses • Assess process used for all categories of recoveries • Assess use of outside investigations

18. Operational Reviews • Evaluate internal administration procedures and controls • Assess records management and retention policies and practices • Assess records management and retention policies and practices • Assess disaster recovery plans • Review internal standards and self-reported performance metrics

19. Ancillary Service Vendor Focus Reviews • Facility re-pricing functions • Pre-authorization process • Peer Reviews • Case Management • Legal Services • Investigation Services • Broker Considerations

20. Audit Follow-Up Recommendations • Collect/Analyze data for Benchmarking • Identify best practices for service levels • Review contract deliverables for financial penalties for non-compliance with key performance criteria • Specifically address strategies to reduce fraud and associated costs in your risk management plan

21. Cost Reduction through Data Mastery Robert Lynch Michael Koss Evo Riguzzi

22. What is Data Mastery? • Celent describes the term as “any initiative to extract useful business information from raw data through data consolidation and analysis, utilizing technologies like data warehouses, unified presentation layers, business intelligence and some elements of CRM”. • Information Builders says that data mastery is much more than the organized gathering of information. “Business users at every level have the need to analyze consistent, conformed data along every relevant dimension to gain insight into success factors at the point of decision.”

23. How does Data Mastery work? “ Most companies have implemented executive dashboards, frequently deployed down to middle management and even individual employees to monitor business performance. But these analytical applications should be aligned with business processes to achieve a complementary result” (Pat Saporito, Best’s Review, May 2010)

24. The Haddon Matrix • An example of the type of versatility and complexity for which self-insured entities are looking is the Haddon Matrix. • The Haddon Matrix is an established methodology for cataloging data concerning accident circumstances and resultant injuries. It is relevant to all organizations and can be used to organize risk factors, exposure factors, loss causes and preventive measures. • The matrix looks at the event in three phases: • Pre-Event: contributing to the likelihood that a damaging event will occur • Event: influencing the chance of injury/damage occurs • Post-Event: influencing the chance of mitigation or complete recovery

26. Use of Strategy Map

27. How does the strategy map help? • It links goals and objectives from the strategic level to the lowest operational level. • It links business processes with associated business rules to achieve consistent evaluation and increase business agility • It coordinates business process management with good business intelligence as a component of process design • You can now determine what data and dimensions are needed to evaluate, track and react to changing business environments

28. Conclusion All participants

29. Key Activities to consider • Corporate public positions on fraudulent activities have to be backed up by real-life activities and, if needed, prompt action. • An involved, caring management who lives up to the public principles of the organization can go a long way to resolving issues of fraud • Policies and procedures that actually support proper conduct by employees or prompt reporting and provide positive reinforcement • Continuous operational and claims audits

30. Don’t Rely just on good faith: Create a data environment to check on those issues that you care or worry about: • Define your issues first. Break them down into activities that can be measured with data you own • Determine what metrics or measures will best analyze the issue and define the problem • Determine how many people will see the metric and standardize/define the measures • THEN, after that is done, design you data warehouse or Operational Data Store (ODS)

31. Thank you! What are your questions? • Robert T. Lynch, Solution Manager, IBI • Phone: 516-659-9851 • E-Mail: Robert_Lynch@ibi.com • Michael Koss, Solution Manager, IBI • Phone: 631-942-1837 • E-Mail: Mike_Koss@ibi.com • Evo Riguzzi, Principal, Optima Investigations • Phone: 1-800-355-3225 • E-Mail: eriguzzi@optma-security.com