EXECUTIVE SUMMARY. A systematic approach for combating enrollment fraud

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EXECUTIVE SUMMARY A systematic approach for combating enrollment fraud OCTOBER 2017

Enrollment fraud is a serious and growing problem The proliferation of identity fraud and new ways of enrolling in health insurance through digital brokerages, public exchanges and other channels means health plans must be ever more vigilant in the fight against enrollment fraud. Even victims of the opioid abuse crisis have been preyed upon, with so-called patient brokers fraudulently enrolling consumers in generous out-of-state plans to draw treatment dollars. 1 Meanwhile, the Government Accountability Office continues to find enrollment in Affordable Care Act plans vulnerable to fraud, with all 15 fictitious identities tested approved for coverage. 2 It s clear enrollment fraud isn t going away, and perpetrators have developed increasingly creative ways of exploiting plans using stolen or fictitious identities or other nefarious means. Often subject to data breaches themselves, health plan leaders know how easy it is for identities to be compromised. They must step up their efforts to guard against the financial losses, negative press, compliance problems and other challenges that can result from fraudulent enrollment. Is your member enrollment process leaving you exposed? When marketplaces directed 11 applicants to provide supporting documents, GAO submitted fictitious documents as follows: For 5 applications, GAO provided all documentation requested. GAO s undercover testing for 2016 found that the healthcare marketplaces eligibility determination and enrollment processes remain vulnerable to fraud. The marketplaces initially approved coverage and subsidies for GAO s 15 fictitious applications. For 8 applications, GAO used new fictitious identities to test verifications related to identity or citizenship/immigration status and, in each case, successfully obtained subsidized coverage. For 3 applications, GAO provided only partial documentation. For 3 applications, GAO did not provide any documentation. A data system that can pinpoint aberrations such as unexpectedly high broker commissions or discrepancies in enrollment data is a key first line of defense. Coverage retained for all 5 applicants. Coverage retained for all 3. Coverage terminated for 1, retained for 2. LexisNexis verifies identities enrolling for health benefits via exchanges and traditional channels to help health plans avoid fines and unnecessary broker commissions. Our solution leverages robust identity data sources, our LexID proprietary linking technology and HPCC computing platform to confirm people enrolling are who they say they are. For more information, call 866.396.7703. 1 Source: Results of Undercover Enrollment Testing for the Federal Marketplace and a Selected State Marketplace for the 2016 Coverage Year. GAO Report.

A systematic approach to fighting enrollment fraud Enrollment fraud can be effectively targeted with a systematic approach to pinpointing and addressing risk. Such an approach involves: Detection: A data system that can pinpoint aberrations such as unexpectedly high broker commissions or discrepancies in enrollment data is a key first line of defense. Suspect or unverifiable names, addresses, dates of birth or other identifying information are red flags that the enrollee might be a fake. A robust referential database of consumer information is a critical component of effective verification and risk assessment. Checks and balances: Stakeholders must be systematically warned of possible fraud and abuse through alerts and other tools. This is part of building a culture of accountability that acknowledges, addresses and ultimately reduces risk. Analysis and investigation: When data systems flag risk, companies must devote resources to follow-up. Data analysts, investigators and compliance auditors all play a role in acting on suspicious enrollments. Fraud Prevention Detection Checks and balances Analysis and investigation 2

Unlock the keys to identity verification Enrollment identity verification starts with basic enrollment data: name, address, Social Security number, phone number and date of birth. LexisNexis allows this information to be checked against a database with hundreds of millions of consumer records, including death records, credit header information and much more. The output is a risk score, calculated based on how much of the identity data could be verified. If most was verified, the enrollment profile is low-risk. If little was verified, risk of fraudulent enrollment is higher, and follow-up is necessary. LexisNexis Health Care allows this information to be checked against a database with hundreds of millions of consumer records. Accompanying data comes in the form of risk indicators and additional demographic information such as alternate addresses, last names and other data if relevant, allowing plans to update their records where appropriate. Risk indicators show precisely where the risk is, permitting the score to be considered in context. Is it possible that a change in marital status resulted in a data mismatch? This is a different scenario than a Social Security number associated with multiple identities. In both cases, the plan has key insight into risk and the appropriate action needed to address it. What does enrollment integrity look like? Enrollee profiles should be subject to a three-pronged integrity assessment: Validation: Is the data real? Does the Social Security number exist? Can the phone number be called? Does the mailing address meet Postal Service standards? Verification: Do the data elements (name, date of birth, etc.) all belong to a single person? Identification of suspect enrollment: Are there multiple identities associated with a single SSN or address? Are there discrepancies, such as a SSN issued before the date of birth? 3

Start addressing risk today Health plans that are ready for a more robust strategy for fighting enrollment fraud need only engage internal stakeholders and commit to a systematic approach. Identity verification simply requires enrollment data and a robust referential database. The scores and risk indicators generated from the verification process give investigators the information they need to pursue questionable enrollments. And with a verified member population, health plans can be confident they are serving members who need it and protecting the company against negative publicity and a loss of public trust, compliance headaches and potentially millions of dollars in losses. Sources: 1 Armstrong, D. and Allen, E. (2017) Desperate for addiction treatment, patients are pawns in lucrative insurance fraud scheme. Stat. Retrieved September 11, 2017 from https://www.statnews.com/2017/07/07/opioid-insurance-fraud/ 2 Government Accountability Office. (2016) Results of undercover enrollment testing for the federal marketplace and a selected state marketplace for the 2016 coverage year. Retrieved September 1, 2017 from http://www.gao.gov/assets/680/679671.pdf For more information, call 866.396.7703 or visit risk.lexisnexis.com/healthcare. About LexisNexis Risk Solutions At LexisNexis Risk Solutions, we believe in the power of data and advanced analytics for better risk management. With over 40 years of expertise, we are the trusted data analytics provider for organizations seeking actionable insights to manage risks and improve results while upholding the highest standards for security and privacy. Headquartered in metro Atlanta, LexisNexis Risk Solutions serves customers in more than 100 countries and is part of RELX Inc., a world-leading provider of information and analytics for professional and business customers across industries. For more information, please visit www.risk.lexisnexis.com. Our healthcare solutions combine proprietary analytics, science and technology with the industry s leading sources of provider, member, claims and public records information to improve cost savings, health outcomes, data quality, compliance and exposure to fraud, waste and abuse. LexisNexis and the Knowledge Burst logo are registered trademarks of RELX Inc. Copyright 2017 LexisNexis. NXR12180-00-1017-EN-US