Session Title Goes Here

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SNAP Recipient Trafficking Meets Data AnalyticsSuzy Cole, SNAPMike McKenzie, Wisconsin DHSSteve Lowe, Washington DSHS

49th Annual ISM ConferenceSeptember 2016

SNAP Basics

• What is it? • How is it set up?

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Congress

Food and Nutrition

Act

FederalRegulations and Policy

Retailers

States

Recipients- Applications, Eligibility,

and Benefits- Fraud Investigations

- Program Disqualifications

Fraud Happens

• Not all Fraud is Created Equal

$$

– Trafficking is one type of SNAP fraud • How do we improve the outcomes with

limited resources?

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Our 3-Part Data Analytics Project

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BPR

Analytics

Implementation

Data-driven approach to detecting and preventing trafficking

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Objectives & Benefits

Increase effectiveness of fraud detection efforts

Identify likely predictors of trafficking

Identify new insights and emerging trends

Support prioritization of referrals and investigations

Individual Attributes & Behaviors

Relationships Between Individuals or Groups

Analyze Data to Identify Trafficking

Behaviors & Characteristics

Prepare Data in Integrated Datamart

Receive State and Federal Data

State Data

Federal Data

Integrated Datamart

Analytics Model Examples

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Determines the influence of the most important factors in order to assign a risk value to each recipient case.

Identifies individual characteristics from eligibility information and transaction behaviors that were statistically different for traffickers

Identifies interaction between different entities, such as common individuals, organizations, dates & times

Identifies patterns, natural groupings or ways to classify data so that it leads to better understanding of data. Assists anomaly detection.

Digit Analysis by Benford’s Law identifies certain patterns of transaction amounts associated with trafficking stores

Benford’s Law

Univariate AnalysisMultivariate Analysis & Model Build

Social Network Analysis

Clustering Analysis

Important Notes about Data Analytics

Data security is paramount Lead Lists are a Starting Point Validation Requires: Knowledge of the population Thorough Investigations

No Disqualifications without Due Process Goal is to find ways to best use limited

resources to improve outcomes

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Examples of State Projects as a Result of this Process

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Client Education & Trafficking Deterrence

Identified New Trafficking Trends

Improved Investigative

Process

Establishment of New Investigation

Methodology

Next Up

• Mike McKenzie – Wisconsin DHS

• We will leave time for questions at the end

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Wisconsin Department of Health Services

Office of the Inspector GeneralFraud Investigation, Recovery &

Enforcement Section

Moving Forward in Our Recipient Integrity Efforts

Presented by Mike McKenzie

∗ Prior to creation of OIG in 2011 Wisconsin was not investigating DQ Retailer referrals from FNS

∗ Trafficking team started developing a process in April 2013

∗ By June 2013 we were investigating our first referrals

∗ As of September 2014 we had investigated 1200 cases and suspended 156 individuals from SNAP for intentional program violation

Disqualified Retailer Referrals

Late 2014:∗Circuit Court decision overturns

IPV decision by our Division of Hearings and Appeals

∗We can’t continue to pursue DQ retailer referrals for recipient unless we can support our allegations with better data

Disqualified Retailer Referrals

But the timing is good…

Disqualified Retailer Referrals

∗Wisconsin selected from Midwest Region ∗Strong support for program integrity efforts∗Contract with Accenture∗Project provided a Business Process Review

and Data Analytics Proof of Concept∗POC was focused on trafficking

FNS Anti-fraud Project

∗This predictive model reflects analysis of recipient data, EBT transactions, and investigations data.

∗Assigns a label to each case:∗ “Has characteristics of known

traffickers” or ∗ “Does Not have characteristics

of known traffickers”.

FNS Anti-fraud Project

Pros:∗Model is capable of analyzing

multiple variables together, such as using eligibility and spending behaviors as inputs.

∗Allows for the analysis to be updated as trafficker’s behavior changes.

∗More “scientific”

FNS Anti-fraud Project

Cons:∗complete investigation is still a

critical process in preparing a case;

∗We currently have to depend on Accenture to “scrub” the data and provide lead lists

∗More “scientific”

FNS Anti-fraud Project

Next Steps∗Testing the new process now on

DQd store∗Pre-hearing conference∗Administrative Hearing

∗Retailers that are also recipients∗Did they report their income?∗Stocking shelves with SNAP

benefits?

FNS Anti-fraud Project

For more information contact:michael.mckenze@wisconsin.gov

THANK YOU!

21DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

Data AnalyticsSNAP Trafficking Meets Data Analytics

IT Solutions Management (ISM) Conference Phoenix, Arizona September 2016

Steve LoweSenior Director, Services and Enterprise Support Administration Office of Fraud and Accountability

Getty Images/iStock

22DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

Washington StateA pioneer in data analytics

Thurston

Grays Harbor

Mason

Jefferson

Clallam

Whatcom

San Juan

Island

Kitsap

Skagit

Snohomish

King

Pierce

LewisPacific

Wahkiakum Cowlitz

Clark

Skamania

Yakima

Klickitat

Kittitas

ChelanDouglas

Okanogan Ferry Stevens Pend Oreille

Grant

Benton

Franklin

Walla Walla

Adams

Lincoln Spokane

Whitman

Garfield

Columbia

Asotin

23DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

DSHS SecretaryPatricia Lashway (Acting)

Services and Enterprise Support

Administration

Office of Fraud and Accountability

Research and Data Analysis Division

WASHINGTON STATE

Office of the GovernorJay Inslee, Governor

Getty Images, iStock

24DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

Housing and Urban

Development Public Housing

Authority

School Outcomes Preschool – College

Internal

Arrests Charges

Convictions

Incarcerations

Community Supervision

Dental ServicesMedical Eligibility Medicaid, State OnlyHospital Inpatient/ OutpatientManaged Care Physician ServicesPrescription Drugs

Hours

Wages

Housing AssistanceEmergency ShelterTransitional HousingHomeless Prevention and Rapid Re-housing Permanent Supportive Housing

Public HousingHousing Choice VouchersMulti-Family Project-Based Vouchers

External

Administrative Office

of the Courts

Employment Security

DepartmentDepartment

of CorrectionsWashington State Patrol

Department of Commerce

Health Care Authority

WASHINGTON STATEDepartment of Social and Health Services

Integrated Client Databases

Nursing Facilities

In-home Services

Community Residential

Functional Assessments

Case Management

Community Residential Services

Personal Care Support

Residential Habilitation Centers and Nursing Facilities

Medical and Psychological Services

Training, Education, Supplies

Case Management

Vocational Assessments Job Skills

Child Protective Services

Child Welfare Services

Adoption

Adoption Support

Child Care

Out of Home Placement

Voluntary Services

Family Reconciliation Services

Institutions

Dispositional Alternative

Community Placement

Parole

Food Stamps

TANF and State Family Assistance

General Assistance

Child Support Services

Working Connections Child Care

DSHS Juvenile

Rehabilitation

DSHS Economic Services

DSHS Aging and Long-

Term Support

DSHS Developmental

Disabilities

DSHS Vocational

Rehabilitation

DSHS Children’s Services

Child Study Treatment Center

Children’s Long-term Inpatient Program

Community Inpatient Evaluation/ Treatment

Community Services

State Hospitals State Institutions

Assessments

Detoxification

Opiate Substitution Treatment

Outpatient Treatment

Residential Treatment

DSHS Behavioral Health and Service

IntegrationMental Health and Substance Abuse Services

Education Research Data

Center

De-identified

Births

Deaths

Department of Health

Washington State Social and Health Services Integrated Client DatabasesEstablished and Maintained by the DSHS Research and Data Analysis Division

JULY 9, 2015

25DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

Criminal caseload at the height of the backlog (Nov 2015)

• 4,198 cases were open:

Example

16%

Severe Mental Health Problems

1%

Dead

1%

Alzheimer’s or Similar Form

of Dementia

<1%

Over 75 Years or Under 18

<1%

Developmental Disability

<1%

Adult Protective Service Cases

26DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

Local Housing Agency Investigations

Example

27DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

Web tool identifies fraud cases by location

Example

. . . by DSHS Region . . . by Legislative District

. . . or by County, Zip Code or Age

28DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

USDA and Washington State

Example

Fraud Cases of Store Owners on Benefits

STORE DATA

CLIENTDATA

29DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

Precautionary Tales

Prioritization

Predictive Analysis

Future Plans

30DSHS | Services and Enterprise Support Administration | Office of Fraud and Accountability ● SEPTEMBER 2016

uestions?CONTACT:

Steve Lowe 360.664.5767Senior Director, Office of Fraud and Accountability

DSHS Services & Enterprise Support AdministrationLoweSM@dshs.wa.gov

QUESTIONS?Steve LoweSenior Director, Office of Fraud and AccountabilityWashington DSHS Services & Enterprise Support ManagementLoweSM@dshs.wa.gov

Michael McKenzieChief, Fraud Investigation, Recovery and Enforcement SectionOffice of the Inspector GeneralWisconsin Department of Health Servicesmichael.mckenze@wisconsin.gov

Suzy ColeProgram Analyst, Program Accountability and Administration DivisionSupplemental Nutrition Assistance ProgramSusan.M.Cole@fns.usda.gov

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Post Session Housekeeping

• RATE this session in the conference app• To download the conference app search for APHSA Events

• VISIT the vendors in the Exhibit Hall during Breakfast and the Networking Breaks to learn more about the solutions presented throughout the day.

• DONATE to Childhelp – the ISM Technology for a Cause campaign to raise $10,000 to help stop child abuse in Arizona and across the country.

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See you again soon

THANKS FORCOMING