Data Mining Solution Using Data Mining Analytics to Support Fraud Detection in CalWORKs Stage 1 Child Care.

Slides:



Advertisements
Similar presentations
QA Reports & PPS Reimbursement Worksheet
Advertisements

From the eyes of an Administrator A general overview of e-CFunds Administrative Site, including navigation and exploring the features of this powerful.
Where Does Waldo Work? T raining Webinar Sponsored by AFP and HEP June 23, 2010 Terry Handler, T. Handler Consulting.
Chapter 12 Decision Support Systems
The 4 T’s of Test Automation:
Decision Support and Artificial Intelligence Jack G. Zheng July 11 th 2005 MIS Chapter 4.
ITRS Roadmap Design + System Drivers Makuhari, December 2007 Worldwide Design ITWG Good morning. Here we present the work that the ITRS Design TWG has.
Health Plans and Hospitals: Working Together to Prevent Readmissions - A Collaborative Approach to Transition Management July 30, 2013 Hosted by the RARE.
Joint Investigation Protocols Convening Presented by: Theresa Costello, MA Emily Hutchinson, MSSW The National Resource Center for Child Protective Services.
National Association of State Auditors
Copyright © 2012 California Department of Education, Child Development Division with WestEd Center for Child & Family Studies, Desired Results T&TA Project.
Illinois Department of Children and Family Services, Pathways to Strengthening and Supporting Families Program April 15, 2010 Division of Service Support,
Receive a Process Application Task. Navigate to the Document Search page to View the Application.
Compliance Monitoring Orientation. Monitoring Components Focus Site Review/Fiscal Monitoring SPAM.
1 Targeted Case Management (TCM) Changes Iowa Medicaid Enterprise October 14, 2008.
1 EEC Board Meeting May 10, 2011 Child Care Development Fund – State Plan for Federal Fiscal Years 2012 and 2013.
Webinar: June 6, :00am – 11:30am EDT The Community Eligibility Option.
Overview of the Green Infrastructure Section of PWSAs Feasibility Study Presentation Charrette No. 3: April 19, 2013 Presenter: Ross Gordon, PE, CFM, LEED.
Introduction Lesson 1 Microsoft Office 2010 and the Internet
Internet Rechartering Update System Enhancements October 1, 2010.
Management Plans: A Roadmap to Successful Implementation
SERVICE MANAGER 9.2 PROBLEM MANAGEMENT TRAINING JUNE 2011.
1 Title I Program Evaluation Title I Technical Assistance & Networking Session May 23, 2011.
Introduction to Homeless Management Information Systems (HMIS)
1. 2 August Recommendation 9.1 of the Strategic Information Technology Advisory Committee (SITAC) report initiated the effort to create an Administrative.
“The Honeywell Web-based Corrective Action Solution”
XProtect ® Professional Efficient solutions for mid-sized installations.
Inter-Agency Child Protection
IV-E Waiver June 2006 Los Angeles County Department of Children and Family Services.
1 Welcome to the Title I Annual Meeting for Parents
Copyright 2001 Advanced Strategies, Inc. 1 Data Bridging An Overview Prepared for DIGIT By Advanced Strategies, Inc.
Barry Sandison Deputy Secretary, Health and Information Department of Human Services Data: creating value for service delivery.
Module 12 WSP quality assurance tool 1. Module 12 WSP quality assurance tool Session structure Introduction About the tool Using the tool Supporting materials.
Chapter 13 The Data Warehouse
Accessing Assessment Results Copyright © 2012 Schoolnet, Inc. All rights reserved.
InterACT 2007 Welcome to Highmark Primary Offices in Pittsburgh & Camp Hill along with satellite offices throughout the USA 18,500 Employees 4.6 Million.
LOCALISING CHILD POVERTY TARGETS: A TOOL KIT FOR LOCAL PARTNERS.
1 Child Care Regulation Legislative Audit Bureau January 2010.
RStat: Release 1.2 Ali-Zain Rahim, Strategic Product Manager March 18, 2010.
Subsidized Guardianship Permanency Initiative. SG Introduction Focuses on improving permanency outcomes for children in out-of-home care through a comprehensive.
Determining Your Program’s Health and Financial Impact Using EPA’s Value Proposition Brenda Doroski, Director Center for Asthma and Schools U.S. Environmental.
Fundamentals of Information Systems, Second Edition
Community Planning Training 1-1. Community Plan Implementation Training 1- Community Planning Training 1-3.
DiscoverU Plan. Discover. Share. dartmouth ∙ digital arts ∙ computer science ∙ native american program.
What is Business Intelligence? Business intelligence (BI) –Range of applications, practices, and technologies for the extraction, translation, integration,
UI Integrity/ Improper Payments Joint Federal/ State Task Force October 14, 2011.
CS490D: Introduction to Data Mining Prof. Chris Clifton April 14, 2004 Fraud and Misuse Detection.
© 2010 IBM Corporation © 2011 IBM Corporation September 6, 2012 NCDHHS FAMS Overview for Behavioral Health Managed Care Organizations.
Striving for Quality Using continuous improvement strategies to increase program quality, implementation fidelity and durability Steve Goodman Director.
Louisiana UI Integrity Task Force October 24, 2011.
Linkages Program Mark Twain Mark Twain.
June Release 3.2 June 23 rd, Person Management Workers will no longer receive an unnecessary pop-up when editing an address on the Person.
October 14, 2011 South Carolina Integrity Strategic Plan.
Building and Recognizing Quality School Systems DISTRICT ACCREDITATION © 2010 AdvancED.
5 - 1 Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved.
Public Health Performance Standards District System Assessment Karen O’Rourke, MPH Joan Orr, CHES 2009.
Chapter 5: Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization DECISION SUPPORT SYSTEMS AND BUSINESS.
Tom Torlakson State Superintendent of Public Instruction Family Fees For Part Day California State Preschool (CSPP) California Department of Education.
Data Mining BY JEMINI ISLAM. Data Mining Outline: What is data mining? Why use data mining? How does data mining work The process of data mining Tools.
Software Architecture Evaluation Methodologies Presented By: Anthony Register.
Second-Order Integrated Developmental Database Systems: EHDI Applications Craig A. Mason, Ph.D.Shihfen Tu, Ph.D. University of Maine Centers for Disease.
Whole Child Connection™ Bob Seemer, President & COO ets, inc. System Overview Winter, 2010 ets, inc.
Copyright © 2001, SAS Institute Inc. All rights reserved. Data Mining Methods: Applications, Problems and Opportunities in the Public Sector John Stultz,
Linkages Fiscal Process Calaveras County Demographics n46,843 Estimated Population n n14.2% Unemployment Rate July 2009.
Preparing for the Future with Decision Support Systems Copyright © 2001 by Harcourt, Inc. All rights reserved.
Do Not Pay Business Center- Using Analytics to Help Agencies Prevent Improper Payments JFMIP May 2016.
Completing the circle: concurrent planning and the use of Family Finding, Blended perspective meetings, and family group decision making processes.
Technology & Analytics
Tuolumne County Adult Child and Family Services
(Improper Payments Prevention Initiative)
Presentation transcript:

Data Mining Solution Using Data Mining Analytics to Support Fraud Detection in CalWORKs Stage 1 Child Care

Data Mining Technology Data mining is a reiterative process of selecting, exploring and modeling large amounts of data to identify meaningful, logical patterns and relationships among key variables. Source: Data Mining 101: How to Reveal New Insights in Existing Data to Improve Performance Insights from a webinar in the SAS Applying Business Analytics Series Originally broadcast in June 2010

Project Background DPSS’ Data Mining Solution (DMS) is a computer application that employs pattern detection and predictive analytics to detect and prevent fraud in public assistance programs, such as our CalWORKs Stage 1 Child Care Program. A Board Motion introduced by Supervisor Antonovich on May 29, 2007, provided the Department of Public Social Services (DPSS) the vision to utilize cutting edge technology, such as data mining and predictive analytics, to ensure and maintain the integrity of the County's public assistance programs. A successful pilot was completed in 2008 which evaluated the effectiveness of using data mining technology to detect potential fraud in the CalWORKs Stage 1 Child Care Program. The DMS Agreement was approved by the Board on December 22, 2009, for SAS Institute Inc. (SAS) to design, develop and implement the data mining technology for Los Angeles County to target fraud in the CalWORKs Stage 1 Child Care Program. The DMS Application was implemented on May 2011 by DPSS to target fraud in the CalWORKs Stage 1 Child Care Program. The Board Approved an Amendment to the DMS Agreement on May 15, 2012 to extend the data mining technology to In-Home Supportive Services (IHSS) Program.

Project Objectives and Key Milestones DMS Application is hosted in Cary, North Carolina by SAS OnDemand The SAS Fraud Framework tracks: CalWORKs Stage I Child Care Participants with children requesting assistance from the County; Providers that care for children while the parent or guardian go to work or school; and Employers on record providing employment for the participants who attempt to defraud the County of Los Angeles by obtaining payment for falsified services. Using state of the art data mining techniques the DMS application: Prioritizes referrals from Alternate Payment Program agencies (APPs) Consolidates data for investigations Shows networks among providers and participants Streamlines / optimizes searching of County data sources Capable of integrating with existing workflow and case management systems Displays results using the advanced visualization application Uses statistically designed risk measures to predict collusion activities

Project Data Sources Data Preparation Efforts Historical data from 2001 to Present Data was (cleaned/matched/consolidated/geocoded) monthly from DPSS and external data sources to generate dozens of variables for data mining models including: Data Focus: Participant and Provider CalWORKs Stage 1 Child Care Child care utilization, request and provider files Welfare-to-Work activity tables from the GEARS system Child care licensing files LEADER Case and Individual tables for participant records Data includes known cases of fraud and alleged fraud LEADER Fraud cluster tables to identify participants referred/prosecuted for Child Care and other fraud types External Data Sources State employment, employer and Income& Eligibility Verification System (IEVS) & New Hire (NHR) files Dun and Bradstreet employment file In-Home Supportive Services (IHSS) participant and provider files

Anomaly Detection Risk Assessment Operational Outcome Alert Score Rules/Pattern Recognition Anomaly Detection Predictive Model Hot List - (e.g., Providers & Employers with known fraudulent activity) Social Network Linkages Operational Outcome Prioritized by Alert score Monthly High Risk Report Drill-down into case detail Further drill-down into Alert detail Launch into other ad-hoc analyses Alert Score Base score Plus or minus depending on value of components

Utilization Process Triage View High risk Alerts are generated based on the comparisons between CalWORKs Stage 1 Child Care cases and the typical profile of fraudulent CalWORKs cases Designated Triage Workers (DTWs) are assigned to conduct comprehensive case reviews based on these Alerts Referrals are initiated to Welfare Fraud Prevention & Investigations (WFP&I) Section Case action reviews result in one or more of the following outcomes: termination of benefits, overpayments, reduction in benefits, share of cost and/or fraud referral Investigator View DMS provides tools and the capability to the DPSS WFP&I team to assist in their detection, prevention, and investigation of fraud in the CalWORKs Stage 1 Child Care Program The Social Network Analysis allows WFP&I to identify suspicious cases for preliminary earlier investigation Provide access to participant’s 10-year historical data across Programs

LA County Fraud Framework – DMS Log on page All Users have been assigned a User ID to access the DMS Application. Log On Page

CASE VIEW SELECTION Case View Select DMS Case View Selection The DMS Application has two different views within the database when your User Id is an Administrative Role. Investigator Role – WFP&I Investigators will access the Investigator View to review all assigned Referrals/Investigations. Triage Role – Triage Supervisor and the Triage Designated Workers will access the Triage View to review all cases assigned a Risk Score with a Trigger Rule that indicates a likelihood of Child Care Fraud. Case View Select

Triage View Triage View Triage View Triage Reviewer’s see a list of cases that do not have open investigations for fraud. This list guides the Triage Reviewer in deciding which of the cases need a fraud referral. The list is sorted by the predictive model score that indicates the likelihood of child care fraud. Designated Triage Workers are assigned a set of cases to review on a monthly basis and make referrals to WFP&I if fraudulent activity is detected or they will make a District 2 Way Gram referral to Line Operations to review the case records for Overpayments and Over Issuance or Unreported Income. Trigger Count – Number of factors, identified by LA County, that indicate a high risk of fraud; examples include an excessive driving distance or a child care provider being an In-Home Supportive Services (IHSS) consumer Trigger Codes – Reasons underlying the trigger(s): A – New address every two months (on average) C – Child care received, but no child under age 13 D – At least one leg of the Participant – Provider – Employer distance determination is considered excessive H – Participant address is the DPSS office and child care is Type 1 or 3 I – Child care provider is an IHSS consumer N – Child care is received, but there is no corresponding component or employment S – Self-employment reported After the detail review of the case records by the Designated Triage Workers, each worker will document the case records with notes on the Comments Tab indicating that fraudulent activity was not discovered, so the case records are Dismissed from the Triage View or document the case record that a Fraud Referral was initiated to WFP&I. Triage View

Investigator View Investigator View Investigator View The Investigator view displays the active investigations assigned to the Investigator File Number, with the Investigation Start Date which tracks the Statute of Limitation on prosecution of the case records with the District Attorney. The Referral Number assigned to this investigation record and any Companion cases related to the Parent case number. The Cases display provides an overview of the investigations that an investigator needs to review, including a participant’s name and identification numbers, the investigation start date, the assigned investigator, the referral number, and a Companion investigation group number. List items are sorted by Investigation Start date, the cells for which have a colored background that corresponds to the time remaining on the statute of limitations. Investigator View

User Interface Participant Details The Participant Detail pane provides a quick view at the participant case record information related to residential address, family members, providers, employment, source income and benefits and prior welfare fraud historical records. Participant Detail Page The Participant Detail pane provides a quick view of a participant, with details such as age, sex, and periods of Child Care Program use. The most recent address and phone number are provided with hyperlinks to online mapping and search tools. Selecting a hyperlinked address opens a Google Map. To review details specific to a particular case, users either select a case and then select Participant Profile (in the menu bar) or double-click a selected case. The case view defaults to a profile that contains detailed information for a participant. When the profile opens, the Timeline and Provider tabs are selected by default. Participant Detail Pane contains current information Tables of information associated with the case, organized into tabs (lower tabs of the UI): Providers - Paid tab Providers - Authorized tab Address tab Employment tab Component (Welfare-to-Work) tab Income and Benefits tab DPSS Actions tab WFP&I History tab Graphs help users visualize the details of the case being reviewed (upper tabs of the UI): Timeline tab – Displays the graphical view of the case activities listed in the tabs to provide a visual look of concurrent activities in every item’s occurrence in time related to the cases details. Street map tab – Shows participant’s home, provider, and work locations on a finely detailed map. Hovering the mouse over the line connecting two nodes displays the distance between the two nodes, which indicates the travel distance between their Employment and Provider activities on a graphical travel distance viewer with identification on how many miles are driven between each point. Relationship tree tab – Shows information about family members and unrelated associates who may be in the household. Hovering the mouse over the icons will provide more detailed information for each member on the Relationship tree. Risk assessment tab – Displays the case risk score (from the predictive model) and provides specific details on key factors that are inputs to the model and others that are triggers or rules defined by LA County. Comments tab – Allows users to record notes about the case and review notes that have been posted by others. Social Network – Displays a network of connected participants, providers, employers, and phone numbers, centered on the selected participant. Participant Detail Page

Timeline Graph Timeline Tab The Timeline tab is a graphic representation of the data from the Provider, Address, Employment, Component, Income and Benefits, and DPSS Actions tabs This graph provides a brief, color-coded view of each data source, as well as a quick method for seeing when each event occurred. Timeline Graph Timeline tab – Displays the graphical representation of the case activities listed in the Provider, Address, Employment, Component, Income and Benefits, and DPSS Actions tabs to provide a visual look of concurrent activities and every item’s occurrence in time related to the cases details. Timeline Tab

Street Map View Social Network Map View Street Map View The Street Map tab displays a geographic map of all the provider service, home (residential, not mailing), and work addresses associated with a case. Users can adjust the time slider to view a specific point in time. The data for this map comes directly from the Provider, Address, and Employment tabs. Social Network Map View

Relationship Tree The Relationship Tree tab shows a participant’s family, household members, and other relatives. Users can adjust the time slider to view the tree over time. Relationship Tree Relationship tree tab – Shows information about family members and unrelated associates who may be in the household. Hovering the mouse over the icons will provide more detailed information for each member on the Relationship tree. The participant appears at the top of the diagram. Lines connect the participant with known relatives. The type of the relationship is noted for each connection. Blue and pink person icons indicate the relative’s gender. Each person’s date of birth, approximate age at the time of the time slider, and Person ID (PID) is displayed. Hovering the cursor over a relationship tree member displays an information box with more detailed information (for example, undocumented flag, in home flag, on aid). Relationship trees along the time slider exist only on the last day of months in which a new relationship is added. Relationships are never removed. Relationship Tree

Risk Assessment Risk Assessment tab contains a list of key fraud indicators for a participant. The tab contains two parts: the Predictive Model section and the Triggers section. Risk Assessment Tab The Predictive Model section contains the results of a statistical model. The Value for the Overall Risk component is 1000 times the expected probability of fraud. Users may see the list of Components that comprise the model. The items in Value correspond to model values in Score and add to the Base Risk Score (always 50) to determine the Overall Risk Score. The probability of fraud doubles with every 10-point increase in the Overall Risk Score. For example, a case with a score of 70 is four times as likely to be fraudulent as a case with a score of 50. Note: Model inputs may be trimmed to a fewer number in any given month without notice. Risk Assessment

Social Network Analysis The Social Network Analysis provides a graphical view of the Participant case record centered on the graph with all the connections within the database of other Participants, Providers, Employment activities and Phone Number connections to the CalWORKs Stage 1 Child Care Participant. Social Network Analysis Social Network Analysis tab - provides a graphical view of the Participant case record centered on the graph with all the connections within the database of other Participants, Providers, Employment activities and Phone Number connections to the Participant. This tool provides the WFP&I Investigators a visually look of all the connections and all the corresponding cases to the current Investigation of a case record. The Social Network Analysis functionality allows investigators and reviewers to explore the relationships among investigated consumers, their associated employers, their associated child care providers, and other consumers receiving Stage 1 Child Care. Network tool provides a zoom in and out capability to view the diagram details in more closer visual view. Tool provides the capability to group the nodes when the User has identified some kind of fraudulent activity connection between the parties. Network provides a time line graph to review historical activities of the Participant status in relation to all activities connected. The history of the relationship may be explored using the time slider function. The relationships are displayed as a social network analysis diagram, centered upon the reviewed or alerted consumer. The investigators and reviewers may expand the diagram to show relationships to other consumers and their providers and employers. Links among these entities are established by direct relationships between the entities, shared addresses, phone numbers, or other personal identifying information. Known fraudulent entities are indicated by special colorings. The location of all entities may be plotted on a map, which also varies over time. Legend Social Network Example

Participant Detail Summary Report in PDF Format PDF Summary Report Allows the Users to review all the case information on the Participant record selected and create a PDF Summary Report as a hard copy for the case file for prosecution filing. PDF Summary Report 18

Holistic Approach to Program Integrity From May 2011 through July 2013, the following actions were initiated: * 28 Cases have been referred to the District Attorney for felony prosecution * 405 DMS fraud referrals initiated for investigation Triage-Initiated: 311 WFP&I-Initiated: 94   * 753 Referrals to DPSS case workers for follow up action resulting in: Fraud referrals for reasons other than child care fraud Denial/Termination/Reduction of various public assistance benefits Overpayments Cost Avoidance The Department expects DMS to result in tens of millions of dollars in cost savings/avoidance and efficiencies over the life of the project through overpayment collections, court ordered restitution, earlier fraud detection and discontinuance of associated benefits, as well as all around improvements in the fraud investigative processes for the CalWORKs Stage 1 Child Care Program. The use of the data mining technology in the CalWORKs Stage 1 Child Care Program, In-Home Supportive Services (IHSS), and other County’s public assistance programs for fraud detection and prevention is expected to result in new fraud referrals, early detection of fraud and increased efficiency, all leading to cost avoidance. The Data Mining Pilot achieved an 85 percent (85%) accuracy rate in detecting collusive fraud rings. The results of the Pilot show that the use of data mining software as a fraud detection tool would have enabled cost avoidance in three areas: (1) New fraud referrals, resulting in an annual gross cost avoidance of at least $2.2 million; (2) Early detection of fraud, resulting in an annual gross cost avoidance of $1.6 million; (3) Increased efficiency, resulting in an annual gross cost avoidance of $3 million. The total annual gross cost avoidance in these areas would, therefore, have been at least $6.8 million. Furthermore, the results indicated that the cost avoidance could possibly increase with additional data sources and further utilization of additional predictive fraud detection models not included in the Pilot.   The potential exists for additional cost avoidance, as the use of DMS technology is expanded to other public assistance programs.