Information Management in Government Leveraging Big Data

Transcription

1 Information Management in Government Leveraging Big Data Kevin Redmond Central & Eastern Europe Information Management Executive 1 March 18, 2014

2 Governments must lead in the face of global challenges Accelerated globalization Continued economic and budgetary pressures Increased expectations of government to deliver on mission and services Rising environmental concerns Increased threats to public safety Pressure for transparency and accountability 2

3 Enable government organizations to significantly improve operations and outcomes With big data More reliable understanding of target or area of interest Police Transportation Revenue Management & Tax Compliance Health and Human Services Video Satellite/Aerial Imagery Current Events Sensors National Borders & Security , Fax Social Media GPS Geospatial, sensor, social media and videodatatohelp connect the dots Proactively detect and deter fraud, errors, and abuse Massive Amounts of Internal Data Defense Real-time delivery and analysis of mission-critical data 3

4 Why is Fraud a Problem? $108 billion Estimated total U.S $47.9 billion Estimated U.S. Medicare improper payments" in improper payments in FY Key Business Drivers Pro-actively detect & deter fraudulent activities 3.4 billion Estimated benefit fraud UK in $3.9 Billion U.S. unemployment benefits paid out erroneously 4 Enhance investigative process with new insights Reduce time to conduct & complete investigations Reduce overpayments 1. Improper Payments Overview 2. U.S. Office of Management and Budget Budget Targets Fraud and Errors in Social Programs Wall Street Journal, May 5, Reduce fraudulent claims Close the budget gap 4

5 Big data helps social program organizations fight fraud, abuse and errors by optimizing their processes with new insight and new capabilities What if we could reduce benefit overpayments and duplicate payments by using big data analytics to identify fraud before payments are made? What if we could improve fraud identification...by pulling intelligence out of unstructured data such as medical or caseworker notes? What if we could improve efficiency and save taxpayer dollars by using big data analytics to reduce critical fraud analyses from weeks to hours What if we could improve fraud investigations by finding clues in social media, geospatial and video data What if we could improve real-time information sharing across agencies and private industry with ad-hoc queries of data sources such inpatient, Rx, financial records, death notices, and crime data? 5

6 Fighting Social Program Fraud, Abuse and Errors Drives Agency Improvement Sample Values Payment Accuracy % Money Collected Per Case % Reduction in # of Successful Appeals % Reduction in # of Improper Payments % Client Successful Outcomes % Reduction in # of Multiple IDs issued % Productivity Reduction in # of Untouched Cases % 6 *Source: IBM Client Engagement, Project Studies

7 Social Programs Fraud Detection requires a robust information foundation Create and maintain a comprehensive a information foundation to supply accurate and secure information for insight and action Protect and Secure Enterprise Data Ensure that all entity and activity information used by fraud analysts is trusted Trusted Information for Big Data and Warehousing Integrate and govern relevant information across the enterprise Act on a Trusted View Create and maintain a single view of all citizen information across the enterprise Application Efficiency for Archiving Data Warehouses Protect citizen and associated information 7

8 Uncovering Improper Payments When weeks of analysis failed to uncover improper payments, the Big Data analytics engine did it in 4 hours and led to a $140 million payoff A major Government Medical & Social Benefits Agency s 360O view of member benefits history and entitlement resulted in savings from identification of improper payments worth over $140M. Fraud, Waste and Error Contributed to a 35-fold improvement in savings and cost-avoidance 8 8

9 Information Management Software Government of France CNAF Challenge Extensive ambiguous data about citizen, applicant and provider identity Data resided in 123 delivery branches in France, each had different versions Each time a citizen applied for a different family benefit, CNAF asked for information they already had. Systems did not share data between branches, did not have up-to-date data between silos and were administratively inefficient. Due to siloed systems, inadequate data matching and privacy restrictions -- data updates were prone to error and deliberate attempts by citizens to defraud the system. Solution IBM InfoSphere MDM Server Foundation Provides the integration, quality and master data functionality to manage an analytical understanding of citizen information IBM InfoSphere Entity Analytic Solutions Business Benefits Gained a rapid understanding of citizens, applicants and providers across multiple programs, cases and locations: Increased effectiveness of providing right service to eligible citizens and recipients Reduced level of improper payments to ineligible persons Creation of a repository containing citizen information for shared use across multiple Government of France organizations IBM Corporation