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Dan KaneshiroSenior Policy AnalystOFFICE OF MANAGEMENT AND BUDGET
BRIDGING THE GAP FROM ENTERPRISE RISK MANAGEMENT
TO ACHIEVING MISSION OBJECTIVES: FRAUD RISK MANAGEMENT
Council of the Inspectors General on Integrity and Efficiency (CIGIE)2019 Federal Audit Executive Council (FAEC) Annual Conference
September 6, 2019
Value Proposition of ERM: “Two Things”
2
One of the value propositions of Enterprise Risk Management (ERM) is even in early stages of maturity, it can drive the following two things:
1) Risk-Informed Discussions2) Risk-Informed Decisions
PRESIDENT'S - -~---
MANAGEMENT AGENDA
A-123: Enterprise Risk Management Model
3
Overview:• 7 Cyclical Components
• Establish the Context• Identify Risks• Analyze and Evaluate• Develop Alternatives• Respond to Risks• Monitor and Review• Continuous Risk
Identification and Awareness
• 3 Enterprise Components• Communicate and Learn• Extended Enterprise• Risk Environment/Context
Illustrative Example of an Enterprise Risk Management Model
Communicate and Learn
1. Establish Context
4. Develop Alternatives
2. Identify Risks
3. Analyze and Evaluate
5. Respond To Risks
6. Monitor and Review
A-123: Fraud Risk Management Requirements
4
• Risk Profiles – Agencies must include an evaluation of fraud risks including: • Fraud as defined by the GAO Green Book.• A risk-based approach to design and implement financial and administrative
control activities to mitigate identified material fraud risks. • Fraud risk may be organized under the operational objectives of the risk profile.• Agencies may determine that they have low likelihood or impact of fraud.
• GAO Fraud Risk Framework – Agencies should adhere to leading practices when: • Establishing entity level controls. • Establishing risk tolerances in disaster situations.
VII. Other Considerations.• Agencies must consider fraud risk in strategic plans and ensure appropriate
officials receive training on fraud indicators and risks related to:• Conducting Acquisition Assessments.• Managing Grant Risks in Federal Programs.
III. Establishing and Operating An Effective System of Internal Control.• Establishing Entity Level Control.
• Managing Fraud Risk in Federal Programs.
PRESIDENT'S - -~---
MANAGEMENT AGENDA
Integration with ERM: Fraud Working Group
5
FRAUDJoin the FRDAA-WG
PRESIDENT'S - -~---
MANAGEMENT AGENDA
TODAY
Risk Appetite and Risk Tolerance
6
Risk Appetite
• The broad-based amount of risk an organization is willing to accept in pursuit of its mission/vision.
• Established by the organization’s most senior level leadership
• Serves as the guidepost to set strategy and select objectives.
• Acceptable level of variance in performance relative to the achievement of objectives.
• Established at the program, objective or component level.
• Management considers the relative importance of the related objectives and aligns risk tolerance with risk appetite.
Risk Tolerance
PRESIDENT'S - -~---
MANAGEMENT AGENDA
Establishing Tolerances in Disaster Situations
7
The GAO Fraud Risk Management Framework includes an example of Risk Tolerance and Risk Matrices in the Context of Natural Disaster Assistance which both aligns and complements current guidance in A-123 and M-18-14.
• A-123 and M-18-14: “Risk tolerance reflects a Federal manager's willingness to accept a higher level of fraud risks and may vary depending on the circumstances of the program.”
• A-123 and M-18-14: “When determining risk tolerances in disaster situations, managers must weigh the program's operational objectives against the objective of lowering the likelihood of fraud.”
PRESIDENT'S - -~---
MANAGEMENT AGENDA
As-<.<"SS
Example of Risk Tolerance and Risk Matrices in the Context of Natural Disaster Assistance When res~ to natural cfs;Jsten. an =1ssi5tancE- pt"C93m h.H various contro4 xtiv.aie to JffVent and detect &--..lld.ffnt appicaticns. fer it!. serv.cM. which indudi! pn:Mding inanci.JI .ass.istanc@ fer t'l!fflporaty housing to p@Ople whose homes_,. d.>maged o, de5l!oyed_ Mln"llers may gen..-.ly defino liN,ir nsk 1011,r:11,c,, os -.,.,., loW" with rog•rd ., providing b!fflpOraty houoing ~ ., po,,nti>ly hudulont applicants Thoroloro. th@y _.• 31 applic.>nts to ll'lde<go a homo in<pOdion to vo,ify d"""'II" ptior to lho prowi<i<>n of any-. <inco lh• Wl<podi(,n< 3N! a eontrol .>etiviy !hat p,o-. • 119' i..01 of conainty tll.lt lhe a<si<tY>Ce i< acru,lyoc,ing 10 those in need
H DW'ft@r. ~ rroy h.Jv@ a hV'ff fraud nsk tolennoe, wch as "'low. raffler th.In ~@ry low. · for IMking p.3yments to po~nblly fr.JucMent iJPplicant:s d the nilnciJ.J.ls liw in ;i seventy darnagtd Mf'll. since individuals "' iwse areas are likefy to h;JIH!! iJl'I urg@fll ne@d" fer tmlpoc.-y hciusng; assistmc@_ In such CSwmstances. managers may weigh rh@ pn,gr,m's o!hor oporaticnal obi@cliv• of upodiliou<ly prnvidirlg .. .,.tan<:@ ag,.,,., lh• objodivo of bwomg tho ikolilood 01 fraud. bKause acliwit:M 10 lowel" tn@ risk rel~ to fraudulenl .Jlll)lic.Jtions. such .;as, conduc:b\g inspections. m.r, c.JUSe
[email protected], service_ GivM a ,ow• fra.\lCI riY ~ .n appos@d to "v@l'Y low.• .:1 ~ may dt!eid@ tc ~ or forego home insptdions. which may M timt,.OOllSlffling cw difficult 10 conduct in in.JCOl!Ssible .Jr@as. Instead,. the manag« may aBoc.rie rHCU"Ces tD a control acilvlly With ii lawll' lewl of cerbmty than c sp@'CbOm,. such as usng gPospatial imagery 10 identify severely d.Jmaged .arus and mate eigbllity determinaoons_
F",gure 3 lllusirat2s concepis desailed so far w~ a two-dmen~ nsk mamx. a oonvnon tedlmque m.111\ligers m.iy
employ 10 visu-Jly plot nus acawd"9 "'thff lilehhood •nd impact_• As notod. lhe spocaicmelhodolc,gym.,._. use lo .sw,;s lraud mks COi) •"'Y· This pa,tiQlbr -,di-,. uwn,j for•~ """'®ols who •re l<nowlodgeable i>bcx,t • pfog-r.-r1, sud'1 as -tlont 1ft • .still' respon.sl>le for mplementng conb'd itetiYIWS, ind for helping rtliin.t~ undersbnd me link be1Wet-n speafic nsb i1nO their mp.x:t.,. The fnl: matrix 1Hus1ra.:es a mk to+er.100e of "very ~ ~ dw second rnatnx sllow> • 1ow'" ml< l<lleraric:e, •> di>als>ed ,n !he exampe -~. S... the '1>esogn ilOd lmplemenr soaion for fw1hor diswSSXJR on ~ respan.s,es 1D fraud ri5b lhai e-ithir exCi!Ed or ara wrttwi the: nsk toleranar:.
Figure 3: Example of TWOsDimensional R,sk Matrices 1/wy low risk tole~ nce
Impact tm~ct
Net TOltr.anC:. ==-==-:-:
~~~g,lt'.Jstr..e8'10Cl, ff"..b .se r-~0R1,a,e~o:1:.ed:on a ~t.ea:c.ae lrl;JI:~ ndlcs~~M>a~r.;liOlrll:l-f'lq!'sl'~U.i!Ul:.lt.at ~ lll tM.ICll'!f'tlffl~Ye1h!ll"O'::tO ~loCICCl'.at1:ll'llioe~7'URUCCf'U,eQ.ffl~l'ci4'-~~1ot1~e'.atl'allllnbblaRf~ ~l'rl._ 'ilbcnt?:Uwtpoc:ea l:19tt1Cr, i-;r-..agcncm~Ol'tm'r..i"'A: 'mC'J~ !WW" IIIPP"ur:t MOIICl:r"~~CCMHr ~ ft:D
1>=.~ n ~ t111t.".l'l:~OCW"e'o!~r .r...aum1r.11.nomm.~r:r«n't!IID:r!$oelftfflnst::li, ~H1ot'•~1nC1cnoo-..e » wuir:,zc~ucn .W',~~tr~ c,,~so!'ne:t.! {~ GAO--W-i'IW0,7.o7l
l ._r$C "'"1s-O ~~fQl',r.-~:;:.ft1J'hl",IOr-::a,, ;\ICl.i-; ,i;n'ey;. • c~«i~~~tricr~'t:q~nQl:~~m'l~lrtc~ a e ttl«Mtorfull )fl'W!!x:taflM !r:!!IIIJO"l'I:~ c:ratldfl~ ~~!il'l'!e'ltlN.t ~CHe l'!,l!>vYlt "'1e1N1Jat.1o1~m~~ 8IOtt l ~fnbt'Wttef~eJ1.MI! /'drct:t~~t:nl)'JQtllhwd~U M:ICOl'lhl~s-=-anai IQfflCJ.
A Frame,<011< tor Man.,_.. ~ Fral.l.l R s l.; n federal Program. I GAO.I~ 14
8
The House With a Basement and an Attic
Innovation
Compliance
Non-Compliance
Efficiency
PRESIDENT'S - -~---
MANAGEMENT AGENDA
The Red Iceberg
9
QuestionsDan Kaneshiro [email protected]
Together We Can Be More EffectiveIn Addressing Improper Payments
including Fraud
September 6, 2019
BUREAU OF THE •
Fiscal S~!Y.t~c~ U.S. DEPARTMENT 0
L E A D ∙ T R A N S F O R M ∙ D E L I V E R12
Program Integrity
Focrus of the ~ Antifraud Playbook
~ Enterprise Risk Management (ERM)
Page 13 L E A D ∙ T R A N S F O R M ∙ D E L I V E R
The Antifraud Playbook Contents
16 Antifraud Plays Organized into Four Phases
https://cfo.gov/fraudprevention
Program lntegrit~f The Antifroud
Plo\:Jbook Phased Approach
Page 14 L E A D ∙ T R A N S F O R M ∙ D E L I V E R
Play 5 Think Like a Fraudster
Fraud Risk Map Example Fraud creates "leaks" of funding, reducing a vailable f unds for legitimate activities
SCHEME
The payroll staff prolongs the pay of
a n employee who has just left the
agenc!:I, ond alters the payment
record so that the direct deposit
information is replaced with bank
account information of his/her own.
ACTORS
r-----------7
The Nonfinancial Impact of Fraud
Fraud encompasses the loss of an!:Jthing of value, even
non-financial value - such as Pl/ -which can create other risks, such
as reputotionol, compliance, or operational failures and challenges.
L ____ _ ______ ..J
FRAUD RISK ENTRY PO INT
Pa!:Jro/1 Records
Payroll Staff
SC HEME
FRAUD RISK ENTRY POINT Time Sheets
Employees pad time sheets.
usually in small enough
increments to escape the
notice of supervisors.
FRAUD RISK ENTRY POINT
Payro/f System
0 -Employee
ACTORS
0 -SCHEME
The payroll staff creates a fake employee in
the payroll records and falsifies the
payment record so that the direct deposit
information is replaced with bank account
information of his/her own.
ACTORS
Page 15 L E A D ∙ T R A N S F O R M ∙ D E L I V E R
Play 6 – Discover What You Don't Know15
GAO Guidance
ldentif\j
inherent
fraud
risks
Assess likelihood
ond impact of inherent
risks
Determine
fraud risk
tolerance
Determine
and prioritize
residual
fraud risks
Document
program's
fraud risk
profile
Pla!,Jbook Checklist
D Leverage !-JO~ff Fraud Ri~k Map (Sec PlaH 6) to urdcmtcnd the p otentia l cntrH p•~ints for fraud □ Id entify !jOUr p rf-rf:!rred ri,-;;k o~:::=,e,-:.sm~rH Lf:!chniq1J~ (s~~ K;.,~l Point~) (Jnd -
o G other informution on the cont rds u n d prucest-es i11 pk.ice o Determ ine if a nd hov-.' t he controls a nd processes in place could be exploited or
o:.;i r i:;LJ11wer1ll:!d
o Determ ine the likeliho,:id and impact oi given sch emes being successful
For ex,:im ple, yo1.1 could condl1ct foc1.1.::: groL1ps •Nith stakeholder!: t hat know t he con-:rols and fJroc;er.-i-.:.f:!i-.:. r l;:!k1L1;:d lo 1111:! I ruLJJ ◊(..: hl;:!r111;:!Q ~CJll pl-:;11 Lu 0 :-:;r,,1;:l:,r,, o r1d di~{.:l11:,i-.;. tt,E:;> -:.:<;ri lrol:-:; ~irid
proccsse~ i n p lace rc btod t o t h o fraud !:.cherncB ident ified, t h ~ ~tr:mgth of t hose controlB, cmd Lhi? p.;.::.li?n lial liki?lifwod c111d impzx:L o ( LhP- ,c;ch ic;m-?..s.
0 Doc1,.1ment 1:he 1·esul1:s c t ~our ri:::;k o s:::;e :::;:::;rnen1:. 1--or exo r11ple, !:JOlJ con docu-rr1:=nt finol lik!::!,lihoo d •ond impact sc:::rcs for givc·n f ~aud s,:hcmcs in -ocditbn to an~ identified ccntrob ,sppB in !-jOLir r rOlJd Ri.sk lv1op (See llluslr{Alion) .
D Trcnslcte :he truu<J scherm:'!s into spi::H.:ific ~i~h=.. ~o r ex.ornple, it th1::! truud scheme !:,lOU were di:.cuss.in2 rclotcd too contractor ovcrbilling for services. the specif ic risks ~JCU migh: i :::lc'lt ify ind ude
o C cntroctors bill for g cods. or services t hot wc~c nc•t provided. v..-hich results in finoncio l Ii~,::.::. lo l hl;! OSJl:!r·v!:J
o Ccntroctors overbill for gc,od s o r servicef;; that were p rovided, whic'l re:,ult s in financic l lo,c;s lo l h8 ogar~cu .
l ! lE:!J:;E:!.:::;p E:!vilir..; ri 1:>ko .:::;l,ou ld olisin lo nu~ lrol1ti l::iGlll;!rllt!O 0-s-:::.ei::1:>t>tl, bul t.:.:.111 ou l Ll 1e spt!-:..:i f iv rii:;k a:.so ciot ed •uith the f;;Cfieme. In the examples above. t he r i!:k ,...,e identified wos .;i nonc·a 1 lo$s, bu l i l con be onuLhing fjCJLJ mou di~CU~iS Or id~n Liru in U(;ur o :;;~il':'~~:~men l a~ 0 pCJler"'ili:·JI risk or t he p•o rticular fraud :.chcmo.
D Prioritize r isks b ased on t he rcsu It!:. of t he •:JSsessmont . Fer cxa m pb, !-jOU can p ricritiz.o rk;b:, con bf? lKJSf!d on likf:!l ihocd and impac l ::.corf?.S or ::;;lra tegic p ri~)r itie:,;_
Not e; \·V~ reo;.;u mmemJ focusing o n re~iduul ri!;;k!;; ot t hi!;:; t-iosie becuus~ tho~e ure t he risks !JCU
1r,•·11 be focugod on 11itigoting. sec Kq .i Poi nts.
C Establish thrcBholds above which t he -~omp oncnt (Sec :,la ~ 8) ~ow a r•o a!:.:::C!:.!:.ing focb it i!:: nf:!c:~s::.o r u, (rnm o c:o:~L n r r Hf)1J lo Linne, .sLnnrlr,o in L, Lo n vn id o nd v•A'lfJL ~J:"'. tJ nrP. willin:3 lo o:-:c~pl o r ~h o rF:t i n te r m ~ o t tr,;.11.1c ri:'-:,k.
NGloP.-'. You will noP.-vf:!r 9eL to "t.i?'O" f-aud, .so uou m :)fJ di?c ici? not Lo dediCfJLe rf?Sf;.ur ce,,:, Lo r i-sk,,:, t hot on:! J eernecJ unli kelu or low-impocl
D Document prioritizod risk.:i includin2 kcH p ieces of infonY1o tion such as the likeli hood ::wd
imp•:.:Jct ~cor e , t.he e)rist i-19 c::.mtrols, ur,!d id en : i ti!:1d !:_lo p s. oncJ r!:!:::.ponse - :.,r rniti9ct ion
activitic:. - !;-JCU 1;vil l p ut in place to addrc :i:. the risk.
0 D ocument U,;Nr lro i...JJ ri.:::;k p rul i le l>o:;;ecJ 011 uv ~ir riQk .uleror,vf:!, priori li/eJ riQ<Q -:..ir1J (;-.,t>ru ll
rc~ults cf t he c~3cs~rncnt pro::::c~B.
L E A D ∙ T R A N S F O R M ∙ D E L I V E R16
Payment Integrity Center of Excellence
VISIONto be a trusted Governmentwide partner to provide actionable business insights and solutions
that transform how Government agencies approach identification, prevention, stopping, and
recovery of improper payments and related fraudulent activity.
GOALSImprove the integrity of Government-wide financial transactions by providing business insight
and solutions that assist Government agencies in identifying, preventing, and recovering improper
payments.
MISSIONto provide Governmentwide partnership, guidance, and solutions that aid in the prevention of
improper payments and fraud, waste and abuse.
VISION
MISSION
GOALS
L E A D ∙ T R A N S F O R M ∙ D E L I V E R17
Payment Integrity Stakeholders & Services
• Investigative Analysis Support • Case Referrals · • Expert Witness Testimony • Prosecution Support • Training
OPERATIONAL SYSTEMS
STAKEHOLDER ENGAGEMENT & PARTNERSHIPS
/\G!:t\:Cll:S
BUSINESS INSIGHT
DATA ANALYTICS
• Non-Receipt Claims • Reclamations • Misdirected Payments • Automated Enrollments • NACHA training
• Payment and Post Payment Analysis • Data discovery • Manage Check Forgery Insurance Fund • Support check to ACH conversion
CUSTOMER DRIVEN
SOLUTIONS
FUNDS RECOVERY
L E A D ∙ T R A N S F O R M ∙ D E L I V E R18
Payment Integrity Throughout the Payment Lifecycle
1
2
3
4
5
6
Identify Improper PaymentsIdentify the payment or payee that should not be paid
Prevent (Pre-Award, Pre-Payment)Prevent the award or payment before sending to Treasury
Recall (At time of Payment)Hold for further analysis or cancel payment before disbursement
Recover (Post-Payment)Request recovery of funds from the Financial Institution
InvestigateRefer for investigation if criminal activity is determined
ShareShare outcomes and discoveries with stakeholder community
Identify people who shouldn’t be paid & payments that should not have been made
I
I
I
------------ =--------~~--,",ftL'' -:fi!=~~~:;["~;:-.~!-¥.!~.£~
L E A D ∙ T R A N S F O R M ∙ D E L I V E R19
Payment Integrity Solution Lifecycle
Repeatable process for development of Payment Integrity Solutions
0 UNDERSTAND BUSINESS PROBLEM
Collaborate with customers, understand business needs
~ DEVELOP CUSTOMER-CENTRIC SOLUTION
~ Develop innovative analytical solutions with business insights
e 0 0
IMPLEMENT SOLUTION
Provide actior1able arid tangible outcomes lhal solve opfm-itional busirn~ss problems.
MEASURE VALUE
Evaluate results and effectiveness of process improvements
IMPROVE
Share best practices witt1 stakeholders tt1rough tn:iining and outreach
L E A D ∙ T R A N S F O R M ∙ D E L I V E R20
Payment Integrity Info-Apps In Action
Problem:Zip Codes identified as
“at risk” for theft
Solution:Zip Code / Check Number View
Problem:Apartment building
identified as “suspect”
Solution:Address View
Problem:SSN identified as victim of
identity theft
Solution:Payee View
Problem:Increased fraud suspected on
a given RTN
Solution:Bank View
Problem:Hurricane requiring monitoring
of a geographic region
Solution:Agency Geographic View
Info-Apps have
answers!
Agencies and IGs have Payment Integrity Questions…
------.-- -- ...... ...... ......... ........
L E A D ∙ T R A N S F O R M ∙ D E L I V E R21
Payment Integrity Info-Apps in Action
'
'
Users supply parameters such as date
and event range, agency, to monitor
' Info-App p rovides post payment monitoring and alerts for disaster event
User can drill down for a list of payees with uncashed or
returned checks
Monitor Payees Impacted by Natural Disasters .Beg.in Dale End Date Agt>Ol")' ALC
109ID 112011 11::1 109/1612018 ,~ !ALL v j 01000001 " 02020001 03000003 04000001 04000002 " 10025697
Evc-nl
LORENCE ~e,.,,,~ " July 18 CA. w .. lfiles
Hn~n V¢1Ca!OO Eas:I. Coast Sl0t1n HARVEY
'""" MARIA y
CA Muelsll08S
r 09011(11~ 091(12018 ~\ t\LLAl('S) lh.V.\Ull l lm.ll\.' lL'i 1,,_1..,, __ • ..,,_
~ .-::.:.=-
,.,..
" -'"" f!Jo)
M Ii;»
ii!«
" u u, if
.,.,,,, 1811014
1117-Z
=-Hh!
1!1tt Hl J,111~1
-•~.m " ......
..,.,1. "' ~,,., 11511+ u worm,
11, , 0 ... .. ,~,\\U( , u t11 .. , Lllll!IIIAl l<lll (i'f l~, m , .. ,
I I I S I $ !!f:: ..... ■Mi om - ••01
Check Relums b)' Ruson .. CflWG -, I eb
L E A D ∙ T R A N S F O R M ∙ D E L I V E R22
High Dollar Payments to High Fraud Risk Financial Institutions
Apply repeatable process and utilize core competencies
Problem
Agency discovered fraudulent large dollar payments disbursed to pre-paid debit cards:• Payees may be unaware of identity theft and payments made on their
behalf• Payments may be misdirected or unauthorized / non-entitled• Agencies may be unaware of high-risk RTN with high percentage of fraud
Solution
Info-App monitors high dollar payments to Financial Institutions with high risk of fraud:• List of FIs maintained through network of agencies and law enforcement• Identified payments over $5K to high-risk FIs• Identified fraud indicators (return reasons, non-receipts claims,
fraudulent enrollments)• Conducted payee profile analysis (Have other agencies paid this person
to the same FI?)
Results
Provided cross governmental payee profile risk analysis:• Conducted pilot with several agencies to test cross-government data
sharing• Analyzed fraud trends (RTN, geographic area, payment types)• Worked with agency stakeholders and IGs to identify, recover, and
investigate
L E A D ∙ T R A N S F O R M ∙ D E L I V E R23
Common Challenges
Seven Topics of Common Interest
Payments to the Deceased
Inter-Agency Benefit Eligibility
Payee Validation (Banking Info, Address)
High Risk Financial Institutions
Compromised Payees and Accounts
Payee Characteristics (DOB, DOD, Incarcerated, etc.)
Updates to 31 CFR Part 210
How can we partner to solve
Payment Integrity issues? // _______________ _
........... - t"t ~ ---------
w ·-----------• ~
L E A D ∙ T R A N S F O R M ∙ D E L I V E R24
Deceased Payee Analysis
How can we prevent Payments to the
Deceased?
Data Quality AnalysisEvaluate payees and dates of death to ensure consistent info
Recovery EffortsDetermine if funds were recovered from post payment events
Compile data sourcesUtilize multiple sources of deceased payee data
How big is the problem?Identify payments made after
date of death
Who is paying them?Identify agencies and
payment types
Evaluate eligibility rulesDetermine if payments to
deceased individuals were appropriate
Step 1 – Understand the Business Problem
t
t
t
0 0 0 0
t
t
t
L E A D ∙ T R A N S F O R M ∙ D E L I V E R25
What’s Next?
Participate in CAP Goal 9 Workgroups• Strategic Data Use• Monetary Loss – Root Causes
Provide subject matter expertise
OMB Workgroups
Initiate Customer Driven ProjectsApply repeatable Payment Integrity Solution LifecycleUtilize core competencies to execute solutionsDemonstrate tangible value through prevention and recovery
Implement Customer Solutions
Quarterly MeetingsReview cross government initiatives
Solicit agency requirementsShare best practices
Agency Partnership Engagement
DHS Anti-Fraud EffortPartnering to Prevent
and Address USG Fraud
Established a DHS OIG Anti-Fraud Plan
Launch of Specialized Units
Strategic Efforts:• Create a Culture of Anti-Fraud Measures• Work with DHS to Identify and Assess fraud risks• Implement internal and external mechanisms for
Preventing and Detecting fraud• Insight into Actions: indictments, convictions,
recoveries and future prevention
Questions
Overview
Mission: Proactively identify, investigate and prosecute fraud
schemes and corrupt activities that pose significant risk and major financial impact to DHS;
Develop expertise in every field office and provide highly specialized tools and other support to the field, enabling INV to conduct high impact fraud and corruption cases around the country.
Anti-Fraud Plan
Establish and maintain a multi-disciplinary team of fraud experts:
• Special Agents well-versed in conducting complex fraud investigations
• Forensic Auditors/Forensic Accountants• Intel Analysts• Data Scientists• Digital Forensic Analysts• Program Analysts • Admin Support Staff
Strategic Efforts - Culture
Collaborate with OIG Audits to help identify high-impact fraud and contract corruption (sensitizes OA to fraud schemes) Collaborate with OIG & law enforcement community to
identify latest schemes Review DHS OIG Hotline with “Big Fraud Perspective” Attend fraud conference/forums to identify latest
schemes Meet with DHS stakeholders to identify vulnerabilities Identify data sources that can be mined
Strategic Efforts – Identify & Assess
Implement a strong fraud awareness effort throughout DHS Partner with DHS Office of Chief Procurement Officer
and Heads of Contracting Activities Establish a close partnership with DHS Suspension and
Debarment Officials Develop Fraud Working Groups within DHSUse analytics to proactively detect significant frauds
and corruption
Strategic Efforts – Prevent & Detect
Strategically target, build and conduct major fraud and corruption investigations
• Work with law enforcement counterparts and DoJ to facilitate investigations and prosecutions
• Use specialized fraud expertise to enable DHS OIG field offices throughout the U.S.
• Utilize DHS Component investigative organizations to support fraud investigations
Strategic Efforts – Insight into Action
Case Study
Fusion Team Makeup – $100M benefits fraud
Senior Special Agent– Data Scientist (1)– Digital Forensics Analyst (1)– Intelligence Analyst (2)– Forensic Accountant (2)– Field Agents (multiple)
.... ..,,;
/)1,.-
·, tl y .. .,,,,.. . ~ ' ·
{omelancl "'ecurity
.....
. -;.
Case Study
Contractor Impersonation
• Fraudsters obtain legitimate solicitations
• Fax/Phone/Email and delivery address are replaced
• Sent to contractors• Fraudsters “accept” and take
delivery of products
Hom el an cl 1ecurity
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“There is no kind of dishonesty into which otherwise good people more easily fall than that of defrauding the government.”
- Benjamin Franklin
Questions and Discussion35
Contact Information
Office of Management And BudgetDan Kaneshiro
Bureau of the Fiscal Service Tammie JohnsonManagement and Program [email protected]@fiscal.treasury.gov304-480-7139
James Long