More Related Content Similar to Preventing Tax Evasion & Benefits Fraud Through Predictive Analytics (20) Preventing Tax Evasion & Benefits Fraud Through Predictive Analytics1. Preventing Tax Evasion &
Benefits Fraud through
Predictive Analytics
Ian Pretty | Senior Vice President,
Tax & Welfare, Capgemini
June 4, 2014 | SAS Analytics Frankfurt
2. 2
BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Areas to be covered today
! Why should Tax & Welfare Agencies be concerned?
! The impact of technology on Fraud & Error
! How can Tax & Welfare Agencies respond?
! The Capgemini response
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Is there really a fraud and error problem?
It is estimated that
approximately €100 billion
in total is involved in the
wrongful
non-payment of VAT within
the EU Member States
each year
Source: EU MTIC Report
Shadow economies are
estimated to have
accounted for £880 billion
in lost tax in the EU
between 1999 and 2007
Source: tax justice network
It is estimated that MTIC
VAT fraud contributed
between £0.5 billion
and £1.0 billion to the
UK VAT gap in 2010-11.
Source:
HMRC report (2012) Measuring tax
gaps 2012; Tax gap estimates for
2010-11.
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Do Governments agree that there is a problem?
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
new modelling tools & techniques
So why does better Fraud Management matter?
So why does
better Fraud
Management
matter?
new & more data
growing demand for and
expectations of public services
shorter reaction times
growing use of digital
identity theft
Industrialization
of Fraud
growing complexity
growing fiscal deficits
reducing costly
investigations
internal Fraud
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BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Typically we see 4 types of behaviour
Large
Businesses
& HNWI
Relationship
based monitoring
to protect
Compliant
Make it simple to get
tax right
Casual avoiders
Risk based
campaigns to recover
and deter
Deliberate
evaders
Full enquiries
to recover & deter
Criminals
Investigate
& prosecute
or disrupt
Value at risk
Riskofnon-compliance
Low
High
Low High
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BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
How Governments respond in a digital, data and analytics driven
world will determine how they protect revenues
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Section 1
How will Technology
impact the fight
against
Fraud & Error?
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
We are all aware of the rise of ‘Big Data’...
Many PBs
of data
every day
25+ TBs
of log data
every day
12+ TBs
of tweet
data
every day
30 billion
RFID tags
today
(1.3bn in
2005)
100s of
millions of
GPS enabled
devices sold
annually
4.6 billion
camera
phones
world wide
76 million
smart meters
in 2009…
200m by 2014
2+ billion
people on the
Web at end
2012
80%Of world’s data
is unstructured
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
…but it is how you analyse that data that will be key to
future success
Business
“Business” – it is the use of
analytics to directly target a business
issue or process and as such is sold
to the Business. Examples are
customer retention, increasing wallet
share, fraud reduction…
Business Analytics is the uses of advanced analytical techniques to find
trends and predict future outcomes which are used to optimize
business processes, customer interaction and manage risk and fraud.
Analytics
“Analytics” – it makes extensive
use of data, statistical and
quantitative analysis, explanatory
& predictive modeling, and
fact-based management to drive
decision making.
Governments will have to become data-driven, analytics-enabled organisations
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Moving faster to an analytics enabled world means a shift in our
Big Data thinking
Each business
area can have
their own analytics
on the same data
Each area can
get their own
insights
The Business
Data Lake
provides a
place to land
the big data
Big data is driven by
business use cases
Business
Data Lakes
Insights can then be shared across the business
12. 12
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
So we will need data lakes to support this new world of analytics
Store everything
Govern only the common
Encourage local
Treat global as a
local view
2
1
3
4
Business
Data Lake
It’s all about insight at the point of action
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
But Governments will also have to operate in a digital world
with increased risks for fraud and error….
Beginning of
Web Session
Login Transaction
and Logout
Pre-Authentication Threats Post-Authentication Threats
DDOS Attacks Phishing Attacks Parameter Injection Man in the Browser New Account Registration Fraud
Account Takeover Fraudulent ReclaimsVulnerability Probing Risking Intelligence Gathering
Password
Guessing
Disruption and/or
Intelligence Gathering
Theft of information and/
or Money
Nation States – Hacktavists – Organised Criminals
News > UK > Crime
Source: http://www.independent.co.uk/news/uk/crime/cybercrime-boss-offers-a-ferrari-for-hacker-who-dreams-up-the-biggest-scam-9349931.html
Cybercrime boss offers a Ferrari for hacker who dreams up the biggest scam
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
…meaning they will need to think data, analytics and digital
Source: Capgemini Consulting-MIT Analysis – Digital Transformation: A roadmap for billion-dollar organisations (c) 2011
Iterative Transformation Roadmap
DigitalEngagement
DigitalGovernance
Digital Building Blocks
Customer
Insight
Operational
Process
New Business
Model
Customer
understanding
Customer touch
points
Improved
compliance
Worker enablement
Performance
management
Process
digitisation
Global collaboration
New outsourcing/
partner models
Digitally modified
business
Digital Capabilities
Tax Investigators
Channels
Tax Policy
Process Innovation
Customer Knowledge
Culture
Partnership Network
Brand
Strategic Assets
Digital Investment
Skills Initiatives
Transformative Digital Vision
Use of new analytical
capabilities & tools
Using
cross-government &
third party data
sources
Real time identify
verification and data
validation
Digital by default –
intervention by
exception
Bilateral and
multilateral exchange
of data
Mobile access to data
& tools
Near real time
dashboards
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Digital will fundamentally change the tax administration model
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Section 2
How should Tax &
Welfare Agencies
respond?
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Tax and Welfare Agencies will need to move from ‘checking’
to ‘risk based’ analytics....
Up-front data
matching accuracy
and eligibility
checks
Pre-emptive and
initial risking
Synthesis of risk
and case
prioritisation
Sophisticated,
algorithm-based
response
Compliance rules Risk rules Risk score Risk-based treatment
Individual reports
income ‘A’ and
compliance rule is used
to compare it to known
income value ‘B’
reported by employer
Individual reports
income ‘A’, risk rule is
used to assess the
propensity to risk, e.g.
by comparing income to
possession of assets
Individual triggers
multiple (risk) rules
which are combined into
single risk score that
enables the Agency to
differentiate between
the level of risk between
individuals
Individual triggers
multiple risk factors and
based on predictive risk
score, this individual is
treated differently
CharacteristicsExample
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
...which means risking using advanced analytics to link
multiple data sets and generate a risk score.....
Historic Approach
Looking for data matches to prove
fraud and error
Leading practice model
Spotting likelihood of an event
through multivariable analysis
Outlier analysisEntity Network Analysis
Hybrid risk modelling approach
Location Demographics
& behaviour
Income Assets Funds
Multiple data sources brought together
X
X X
X X
X
Data set 1 Data set 2
Data match/ mismatch triggers
risk rule
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BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
...and an analytics–based risk methodology
Compliance activity
WHAT
is happening?
WHO
is doing it?
WHY
are they doing it?
HOW
to respond?
Understanding the type
of non-compliance
(simple error; evasion;
avoidance;
underreporting income)
Understanding the
characteristics of the
taxpayer or benefits
group (segment)
Understanding the
reasons (low level of
services; complicated
legislation; criminal
attack)
Understanding the best
option (targeted
compliance campaign;
preventive action;
better information/
service; penalties)
Analytical insight
Client
Segmentation
Behavioral
Analysis
Predictive
Modelling
Campaign
Design & Mgt
Risk Rule Design
& Mgt
Anomaly
Detection
20. 20
BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Section 3
Trouve: The Capgemini
answer in
partnership
with SAS
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Back to Mr. Hyde
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Trouve applies new sources of data and advanced analytics to
create an end to end risking & interventions process....
Prioritized
(risk based)
flow
Large scale
Data
Networking
& Network
Analysis
High Analytical
Performance
Data
Visualization
Applying
insight
across the
value chain
Measurement
and Continuous
Improvement
Applying
analytics
internally
(workforce,
case
management)
Building a
citizen
centric view
Hybrid
Analytics
Models
Advanced
Campaign
Management
Receive Understand Interact Review
23. 23
BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
...and enterprise capabilities to improve compliance outcomes
Filing /
(Re) Payment
request
Calculation
Assessment
Payments
in/out
Pre-reg
Registration /
Application
Reconciliation
Compliance & Debt
Enforcement
Businessoperatingmodel
Solutionarchitecturelayers
Downstream risking
Debt Management
Internal Fraud
Upstream risking
ID assurance
Voluntary compliance
Tailored solution to deliver
new capabilities and maximize value
Design Develop Deploy
Organization
People &
Skills
Processes
Technology
Business
Services
Information
Systems
Capabilities For more information about TROUVE visit: www.capgemini.com/trouve
Debt Management
Information Mgt
Work and Workforce management
Investigation and AuditCampaignsProfiling and Risking
Performance Management
Strategy and Policy
Set Risk
Policy / Strategy
Set Service and
Channel Strategy
Simulate Policy /
Strategy
Develop Policy /
Strategy
Monitor Legal
Compliance
Manage Customer
Service
Manage Yield
Effectiveness
Manage Resources and
Workforce Efficiency
Profile Citizens
Prioritize Risk
Validate Citizen
Identity
Identity
Registration
Risk
Identity
Returns
Risk
Identity
Repayment Risk
Identity
Compliance
Risk
Identity
Debt
Risk
Set Channel
Selection Rules
Design Campaign
Execute
Campaign Case
Record / Verify
Response
Profile Citizens
Investigate
Non-
Compliance
Find ‘Ghosts’
Investigate
False Passes
Detect Internal
Fraud
Pursue
Compliance
Case
Pursue Internal
Case
Assess debt
risk
Set work
priorities
and allocate
Manage
Case
Worklist
Manage
Contact
Worklist
Set Resource / Skills strategy
and capacity
Set Data
Acquisition and Mgt
Policy
Select/Model new
information sources
Monitor Data
Quality
Import and Check
External Data
Prioritize debt
Create
inventory of
debt
Monitor
Insolvencies
Pursue Debt
Case with the
Citizen
Administer
Insolvencies
Set
workflow
rules
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
The functionality of TROUVE addresses the requirements
of the future compliance model
Downstream Risking & Case Management
Operates outside of operational processing. Extends the capabilities of post processing compliance to maximise money yield
and money recovery based on optimising available resources.
Upstream Risking & Case Management
Uses predictive models to identity high risk transactions to withhold services such as payments or repayments and initiates
interventions.
Protecting Online channels from ID Theft
Using transaction monitoring and the application of identity assurance within the transaction to prevent ID Theft
Uncovering Internal Fraud & Collusion
Applies the analytics techniques on internal operational and customer data and to identify anomalies in behaviours that
signal fraud, either individual working alone or collusion with external fraudsters.
Improving Debt Management
by understanding customers attitudes and behaviours we can determine the optimal treatment strategy balancing cost and
business results. An integrated feedback mechanism leads to a continuous improvement.
Supporting Voluntary Compliance
maximizing the use of digital communication channels, methods and campaigns to drive up voluntary compliance via
targeted & tailored service, eliminating the need for compliance activity
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Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Client Concerns Method
But we also know that each client has a different
starting point
Client Situation
! Requirement identified but there is no clearly
articulated vision or high level design
! Vision and High Level design exist – unsure
of where to start and in what order
! Concerns remain about clarity and progress
! Will it work at all and if so will it be scalable
! Desire to start to build initial components
quickly
! Value Discovery
! Target Operating Model and
detailed Roadmap
! Business Assurance
! Proof of Concept/Pilot
! Design & Build Fraud
Management System
I need to
do something
I have a Vision
Show me it works
I get it.
When can we start?
Am I on the
right track?
26. 26
BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
Case study: Implementing the strategic risking
solution for HM Revenue & Customs
! Capgemini supported HMRC to design, build, deploy and run their strategic risking
tool – Connect
! Takes information from 28 different data sources
! Cross-matches one billion internal and third party data items
! Uncover hidden relationships across organizations, customers and their
associated data links (bank interest, lifestyle indicators and stated tax liability)
! Connect uses analytical and ‘spider diagram’ visualization tools
! HMRC analysts produce target profiles and models to risk assess
transactions and generate campaigns and cases for investigation
! Automated feeds into HMRC’s case management system
! Streamlined risk and intelligence operations are delivered by with
40% fewer staff. Connect produces in minutes what previously took months of
research, or was simply not possible to do manually or on a volume basis
! Skilled staff concentrate on tackling aggressive evasion rather than correcting
errors, which historically took much time and which is now tackled in other ways.
£
In total HMRC has recovered £2.6bn additional tax yield to date,
through the use of Connect
The project has won
several awards:
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BIM
Copyright © 2014 Capgemini. All rights reserved.
Preventing Tax Evasion & Benefits Fraud through Predictive Analytics | May 2014
! Proven success stories in
UK, Netherlands and in the
Financial Services Sector
! £2.6bn additional tax yield
to date for HM Revenue &
Customs.
! Partner to 35 Tax & Welfare
globally
! Understanding of the Tax
business process
! Compliance Framework
! End to End solution
! World’s foremost provider
of Business Information
Management (BIM)
services.
Our capabilities
Register
/Change of
Details
Process
Application
/Return
Establish
Liability
/Benefit
Manage
Payments
In/out
Reconcile
Investigation
/Audit/
Enforcement
Receive
Customer
Submission
Enforcement
/Debt
collection
/criminal
proceedings
Prevent Protect Uncover Resolve
Feedback
Prove
An integrated approach takes a holistic approach on which to base a business strategy that develops and deploys common
capabilities actively managed to deliver the best business outcome.
Prevent transmission of
incorrectinformation – either
error or fraud
Protect againstincorrect
/repayments/repayments through
the identification and management
of risks
Identify that fraudulentor
non-compliantactivity has
taken place
Provide evidence to prove
the case so that the authority
can take remedial action
Successful
resolution through
recovering the monies
or securing criminal
prosecution
Infrastructure
Data Sources
Data Preparation
Data Linking/Networking Creation
Analytical Environment
Network Visualisation
Risk Model Management
Analytical Capability
Execution Ability
Investigative Capability
Case Management
Enterprise
Compliance
Capabilities
! Strategic global partnership
with SAS on Fraud
management solutions
! BIM Centre of Excellence
in India
! Business & Solution
Architects
! Local footprint.
Delivery capabilityDomain expertise
SAS CoE
! Dedicated lab for all
SAS products
! High performance
servers installed
! Hands on
experience for
building proof of
concepts
! Build better
knowledge
infrastructure to
share and learn SAS
! Premium
partnership
agreement with SAS
Report generation
& delivery
Predictive models,
scorecards,
segmentation, decision
trees, web analytics
Forecasting
optimization,
social media,
solutions
Value Proposition
Skills
! Analytical
consultants
! Business analysts
! Statisticians
! Tools experts
! BI architects
! Data architects
! MDM experts
! Change experts
! Quality experts
! Process leads
! Domains
Analytics Maturity Assessment
Specialized skill pool
Cloud based offering
Analytics CoE to support
the known requirements
of today and the
unanticipated needs of
the future
Easy to use and relevant
scorecards and reports
that enable greater
visibility into operating
and financial metrics
Ad-hoc sales, marketing
and functional reporting
for a streamlined,
integrated and automated
operation
Solution
Social Media Analytics
Marketing Campaign Analytics
Big Data Analytics
KnowledgeIntensive
ResourceIntensive
Proven value
28. The information contained in this presentation is proprietary.
Copyright © 2014 Capgemini. All rights reserved.
Rightshore® is a trademark belonging to Capgemini.
www.capgemini.com/bim
About Capgemini
With more than 130,000 people in over 40 countries, Capgemini
is one of the world's foremost providers of consulting, technology
and outsourcing services. The Group reported 2013 global
revenues of EUR 10.1 billion.
Together with its clients, Capgemini creates and delivers
business and technology solutions that fit their needs and drive
the results they want. A deeply multicultural organization,
Capgemini has developed its own way of working, the
Collaborative Business Experience™, and draws on Rightshore®,
its worldwide delivery model.