Data Analytics, Data Sharing, and Privacy

Ronda Kent and Virginia Rone International Colloquium on Financial Management

September 2017

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Overview

• Introduction to the Bureau of the Fiscal Service in the U.S. Department of the Treasury

• Data Analytics

• Data Sharing and Usage

• Privacy in the U.S. context

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Bureau of the Fiscal Service

Our mission is to promote the financial integrity and operational efficiency of the U.S. government through exceptional accounting, financing, collections, payments, and shared services. The Bureau operates and maintains systems that are critical to the nation’s financial infrastructure, such as the disbursement of payments to the American public, revenue and debt collection, and the borrowing of funds necessary to run the federal government.

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• Fiscal Service disburses almost 87% of the federal government’s payments.

• Our recipients are a global community, living domestically and abroad, in rural and urban areas.

Fiscal Service Plays a Critical Role in the Disbursement of Federal Payments

On behalf of over 200 Federal agencies, Treasury made 1.18 billion payments valued at over $3.3 trillion in Fiscal Year 2016.

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• Agencies take many steps to safeguard federal payments and ensure that the right payment gets to the right person at the right time for the right amount. – Agencies ensure the accuracy of payment data, which is the

foundation of data-centric internal controls to detect and prevent improper payments.

– Agency subject matter experts execute controls to ensure that payments meet program and legal criteria for disbursement.

– Agencies trigger Fiscal Service processes to reclaim or recover improper payments.

• Our agency partners are a critical component in creating a successful program protecting the integrity of federal payments.

Fiscal Service Supports Agency Efforts to Safeguard Federal Payments

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Safeguarding the disbursement of federal payments.

• As the government’s disbursing officer, Fiscal Service has well established authorities regarding federal payments and occupies a unique position to protect the integrity of federal payments.

• The Payment Integrity Program ensures a robust set of internal controls and data centric electronic tests are executed throughout the payment lifecycle.

• The Program consistently seeks new and innovative ways to provide valuable data and insight to support federal agency management, law enforcement entities, and the oversight community to strengthen agency payment processes.

• In doing so, the Payment Integrity Program aids in the prevention, detection, and recovery of improper payments, payments affected by fraud, waste, and abuse, and other payment anomalies.

Fiscal Service’s Payment Integrity Program

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Payment Integrity Occurs throughout the Payment Lifecycle

Verify payee eligibility

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Review InvoicesAgency compiles list of payees or

payments

Payment Lifecycle

Capture transaction data from all disbursement and post-payment activity for

analysis

Integrity Controls

Pre-Award

Act on agency death and non-entitlement

notifications

RecurringBenefit

Tax Refund

Grant

Vendor

Misc

Disbursement

Process enrollments / changes

Process change in paymcnt delivery

mechanism

Fiscal Service processes lists of

payments

Ag

en

cy C

ertifica

tion

C

Confirm payee continued eligibility

Funds Received by payee

Continuous improvement through data analytics, coordination with law enforcement, and customer engagement

B

Payee non-receipt claim, payment is returned, or stale

dated check

F

Pre-Payment Payment

Preventing and recovering improperpayments by verifying payee eligibilityand debt status

Using electronic testing to ensurepayment files and data are valid

Safeguarding the delivery of payments

Obtaining authorizing official approval of the correctness and legality of payments

Processing post-payment exceptions to recover improper payments and deter fraud

A

D

C

B

Post-Payment

A

Identify debtors for

offset

F

Reconciling and reporting payment and post payment information

AF

E

E

B

Validate bank routing

numbers

Payment Types

Pre-notification

B

D

A

Utilizing retrospective analyses, advanced analytics, and agency engagement to improve the payment process

G

G

The Role of Data Analytics in Payment Integrity

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• Data analytics can be defined as using data to develop insights and drive informed decision-making. Analytics can: o Help to separate normal business practices from anomalies

o Expose risk even within large data systems such as those operated by government

o Detect and prevent improper payments, such as payment errors, as well as payments affected by fraud, waste or abuse

o Improve government transparency and citizen trust in government

o Data analytics also can be used in a predictive manner to prevent improper payment errors by implementing “payment integrity checks.”

Role and Uses of Data Analytics

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• Fiscal Service recently partnered with an agency to develop and test four payment integrity checks for the agency’s payments to vendors.

• Payment Integrity Check #1: Vendors that temporarily change to a new bank account.

Payment Integrity Checks: A Case Study

What risk is detected? Switching bank accounts may indicate intentional rerouting to collaborators in a fraud scheme, an attempt to receive multiple transactions for the same work, or other deviations from normal practices.

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• Payment Integrity Check #2: Detecting duplicate vendors

Payment Integrity Checks: A Case Study

Expected Relationship between Vendor Records and Key Attributes

Duplication Indicated by Shared Key Attributes Duplication Indicated by a Mixture of Shared and Differing Key Attributes

What risk is detected? The presence of duplicate vendor records may increase agency's risk of making duplicate payments, resulting in improper overpayments.

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• Payment Integrity Check #3: Detecting duplicate invoices

• Payment Integrity Check #4: Unusual invoice amounts

Payment Integrity Checks: A Case Study

What risk is detected? Duplicate invoices may represent double billing of products or services to the same or different vendors, and increase an agency’s risk of disbursing an improper payment by way of overpayment. Similar integrity checks could be created based on duplicate purchase orders, payments, or invoice line items.

What risk is detected? Identifies very high and very low invoice amounts which have a low probability of occurrence relative to the normal range of payments. May be an indicator of an event or an activity occurring that is outside standard practices, potentially fraudulent, or otherwise improper.

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• Data analytics can be used as a retrospective assessment to evaluate the effectiveness of internal controls. For example: o Fiscal Service analyzed federal loan data to identify borrowers

who were ineligible to receive a loan because the borrowers were deceased or owed a debt to the federal government at the time of loan issuance.

o The agency-customer will use the information provided by the analysis to identify root causes of internal control failures.

Data Analytics and Internal Controls

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Data Analytics and Supporting Law Enforcement

0

20

40

60

80

100

120

140

160

180

Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May June

Alteredby IssueMonth

Alteredby PaidMonth

Subject #1 arrested

subject #2

subject #3 arrested

Postal Carrier suspended

Fiscal Service

Altered Treasury Checks

Data Sharing and Privacy

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• Sharing data is foundational to using analytics to protect the integrity of payments. – An agency may need to share data with Fiscal Service for

analysis.

– Fiscal Service must be able to share results with the agency

– Sometimes multiple data sources need to be compared to detect anomalies or problems with a payment recipient’s eligibility

• Data sharing takes place in a complex landscape designed to protect citizen privacy by establishing processes for approving how data and the results of analysis can be used.

Data Sharing Is Critical for Analytics

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• Data sharing takes place in a complex landscape designed to protect citizen privacy by establishing processes for approving how data and the results of analysis can be used. o For example, the Privacy Act of 1974 adds procedural requirements,

such as signing a Computer Matching Agreement, for agencies to follow when engaging in computer-matching activities.

o Other laws also govern data sharing. For example, the Internal Revenue Code restricts the sharing of tax data.

Context for Sharing Data Is Complex Process

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• Three key challenges can create barriers to sharing data: o Legislative challenges such as the complex legal

landscape o Technological barriers such as limited interoperability or

difficulty extracting data from legacy systems o Organizational cultural resistance such as the tendency

to avoid risk by simply saying no to sharing data

Challenges to Data Sharing

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• Data analytics is a key tool in protecting the integrity of federal payments.

• Using this tool in the federal context requires knowledge of the legal landscape to ensure compliance with privacy requirement.

• Successfully navigating this landscape and implementing effective analytics projects require knowledgeable staff.

There’s no magic toolkit that can make data analytics work for you except for the skills of your analysts and experts.

Closing Thoughts

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Contact Information Ronda Kent Assistant Commissioner Payment Management Bureau of the Fiscal Service Department of Treasury Ronda.Kent@fiscal.treasury.gov 202-874-5319

Virginia Rone Deputy Assistant Commissioner Debt Management Services Bureau of the Fiscal Service Department of Treasury Virginia.Rone@fiscal.treasury.gov 202-874-6185