Identifying Non-Compliance
through Data Analysis
Stan Shrosbree
Fiscal Affairs Department (PFTAC)
International Monetary Fund
April 20, 2016
Having adequate data to identify non-compliance
and quantify potential revenue losses including due
to tax expenditures are increasingly more important
issues for tax administrations to address. Better
knowledge of these issues between the ministry of
finance / treasury and the revenue administration
through data interrogation provides a good base for
identifying potential opportunities to treat noncompliance and broaden the tax base. This session
will provide participants with a better understanding
of using data to improve taxpayer compliance,
revenue administration and tax collection.
What is tax non-compliance?
•
Tax noncompliance is a range of
activities that are unfavorable to a state's
tax system. This may include tax
avoidance, which is tax reduction by legal
means, and tax evasion which is the
criminal non-payment of tax liabilities.
• Using data is crucial to identifying noncompliance
Non–Compliance and Risk Management ..
What is the Revenue cost of Noncompliance … the tax gap?
• Broadly defined, the tax gap is the difference between
the taxes that would be paid if all obligations were
fully met in all instances, and those that are actually
received and collected. As a concept, it can encompass
revenues lost to tax evasion, taxpayer error, and unpaid
liabilities. It includes both domestic and international
dimensions.
• Like many other countries - PICs don’t know what the tax
gap is?
• However most PIC’s acknowledge that there is a big
gap and something can be done about it through
introducing efficiencies with a focus on identifying and
treating risk through using data
Some experiences in the Pacific ….
• IMF/PFTAC have been working closely with
PICs to raise the importance of using DATA
to understand the tax base and …
– Using the data to identify risks and
– Develop Compliance Improvement Strategies
• This is a new area for most PIC Revenue
Administrations with good progress being
made
• This is the future!
Revenue Administrations (RA’s)have
Data ..
• The question is ….
– What data have we got?
– What data from external parties do we have
access to?
– Do we use it to maximum effect to improve
compliance?
– Have we got sufficient staff in Revenue
Administration to interrogate the data?
– How can the data contribute to a
Compliance Improvement Strategy
– Does the law allow it?
Data Matching – a good example (SARS)
Demutualisation of SANLAM and OLD MUTUAL
A further milestone achieved in the current financial year concerned the
demutualisation of Sanlam. Research conducted by SARS showed that
about 30% of SARS’s debtors would receive free shares from
Sanlam. The High Court granted an order allowing SARS to freeze the
free shares of those taxpayers who defaulted in paying their
outstanding tax. This project has resulted in an amount of R150 million
in outstanding taxes being collected. At the end of March 1999, SARS
was in possession of 11.5 million shares of defaulting taxpayers.
Potential shareholders of Old Mutual were also warned that their
shares would be withheld until they paid any outstanding taxes to
SARS. As a result, SARS collected a further R59 million during March
1999. It is expected that the revenue generated from this source will
increase further. (SARS Annual Report)
Result USD 42 M
Macedonia – data matching
• Data matching between
– Health Fund
– Pension Fund
– Unemployment Fund
• Large non-compliance trends
• What was the solution?
– A new integrated collection model by the RA
• What was the result?
– An additional 8 per cent of revenues collected
in 2009 and revenue streams retained after
that
Serbia – GPRS Cash Register System
• Fiscal cash registers enable wireless connection to Tax
Administration by an integrated GPRS terminal. These
devices support centralized management of cash
registers in a customer sales network and are aimed at
businesses recording the correct cash sales
• Analyses done to compare sales to:
– Sales per the VAT return
– Bank deposits
– Financial statements
• Massive variances found – a big compliance issue
• How did the TA fix this problem?
Serbia – Fixing the Cash Register problem
•
•
•
•
•
•
•
A campaign
Keep your receipt and fight tax evasion
TV adverts and general advertizing
Till slips drawn on a TV show
First prize a car!
Massive support by the general population
Sales increased substantially
Another data matching story …
• Dividends taxable in South Africa information obtained from neighboring
countries tax administrations
• Interest from investments made in SA
taxable in SA – neighboring states
• Industry Partnership Doctors and Dentists
RA – Examples of Sources of Data
• Internal
• External
•
•
•
•
•
•
•
•
•
•
Register
Returns
Payments
Case Work
Intelligence
Banks
Telco
Traders
Other departments
Social Media
Big question – how accurate is the data
and can we use it?
• Many Revenue Administrations have
neglected keeping their data bases accurate
–
–
–
–
–
Corrupt data
Data not captured correctly (taxpayers and staff)
Industry codes incorrectly reflected
Misclassification of goods
Non active taxpayers in the system for example ..
• Should they be deregistered or followed up
• Debt – is it recoverable?
• A corrupt data base frustrates compliance
management and increases RA costs and a
major contributor to “wasting time”
Data Integrity – Completeness and Quality
Some Data Management Issues
Governance and Data entry errors – Outliers/ anomaly
staff and
Accessibility
detection
customers
Structure/ or lack
Fraud & intentional
Misclassification
–
of
or unintentional
e.g. Goods,
error
Matching records –
sectors
data integration
Timeliness/ Real
Completeness/
Time
Storage
missing data
Risk Management Cycle(OECD
Model)
Operating
Operating Context
Context
Identify
Identifyrisks
risks
Monitor
Monitor
performance
performance
against
againstplan
plan
Assess
prioritise
Assessand
andprioritize
prioritiserisks
risks
Analyze
Analyse
Analysecompliance
compliancebehaviour
behaviour
(causes,
(causes,options
optionsfor
fortreatment)
treatment)
Determine
Determinetreatment
treatmentstrategies
strategies
Plan
Planand
andimplement
implementstrategies
strategies
Evaluate
Evaluate
compliance
compliance
outcomes
outcomes
• • Registration
Registration
• • Filing
Filing
• • Reporting
Reporting
• • Payment
Payment
Clean data allows RA’s to better ..
• Apply the Risk Management
Cycle to
–Identify Risk
–Understand Risk
–Calculate Risk
–Manage Risk (Treat the risk)
17
What capability have PICs got to analyze
data?
• The larger RA’s are fast building this
capacity with the smaller tax
administrations yet to develop
• Most PIC’s have IT systems in place
that provide the data
• However ….
– Little capacity to interrogate data
• Staff profiles/shortages
• Tools
Using data effectively
Data
Analysis
$$$$$
19
Data … Modern Revenue Administration
Data
Data Analysis
Effective and
Efficient Tax
Administration
International
Benchmarking
Tools
Performance
Management
and
Measurement
20
Does this data on flights explain
risks – Ebola?
21
All Risk is Relative …
22
Determining Risk Treatment Strategies – a
balanced approach
Key points
• Compliance programs need to
provide a graduated response to
compliance behavior – make it easy
for those who want to comply and
applying credible enforcement to
those who don’t.
Enhanced capacity to influence
taxpayer compliance behavior often
comes through strategic alliances
and partnerships with other
agencies, industry bodies and tax
advisors.
Acting at all time with integrity and in
a manner perceived to be fair and
reasonable will encourage voluntary
compliance.
Sustainable improvement in
compliance can only be achieved by
influencing and changing social
and personal norms.
Treatment needs to address the
underlying drivers of compliance
behavior (taxpayer surveys).
The most effective strategies are
likely to be multi-faceted and
systematic
Key products
A compliance program covering the
current planning period.
Products and tools tailored
specifically to clients to be targeted
through the compliance program.
Carrot and “Fork” approach?
Understanding Revenue Risks –
where do they originate from?
•
•
•
•
•
•
•
•
Tax Evasion
Tax Avoidance
False Claims
Error
Poor service
Bad debt
Customs & Excise
Internal controls
25
Institutional Capability
• Do PIC Revenue Administrations and
Ministries of Finance understand NonCompliance and the steps needed to get
taxpayers to comply more fully?
– An understanding of how to identify non-compliance
through data interrogation is emerging
– However, there is little understanding of what type of
RA organizational structure and staff are required to
facilitate improved compliance
• Traditional RA structures are out of date and cannot
accommodate new ways of work required by modern data
driven Revenue Administrations
What is Needed to Apply Data Analyses?
People
Process
Models
Rules
Intel
Results
Technology
Where to Start: Look at the data and context
Purchases
Examples of Risk Rule Areas
• Registration
– Multiple registrations at
same address
– Frequent changes of
address, directors
– Unusual age of directors
• Filing
– Nil returns with evidence
of activity from other
sources (internal and
external data, business
intelligence)
• Accuracy
– Turnover/ GPM/ losses
outside of normal range
for sector or region
– High/ many expenses
claimed
– Profits relatively low
• Payment
– Late/ declining payments
– Balloon payments
– Increasing arrears,
amount and age
– Debt within groups
Data analyses will provide us with a
picture that profiles our taxpayers
Good taxpayer:
Compliant, not
risky
Bad Taxpayer:
Not compliant,
risky
Unknowns: ?
Data Analysis: Start small
• Registration
– Using third party information to identify registrants?
• Filing
– Analyze current filing data and a plan to get
delinquent taxpayers to file?
• Payment
– Analyze and develop a plan to facilitate payment?
• Correct reporting
– Third party information – a new range of audit types?
• Measure and communicate the results
– Key stakeholders including the MoF and Treasury
– Taxpayers
FAD’s Fiscal Assessment Tools
RA-FIT
RA-GAP
TADAT
32
Revenue Administration’s Fiscal Information Tool
Purpose and Benefits
• RA-FIT provides the platform for a
single international revenue
administration (tax and customs)
data gathering tool
• Encourages and supports
performance measurement to
developing countries
• Used to establish key baselines and
identifies key risk areas for revenue
(tax and customs) administration
• Makes aggregated data & analysis
available to member countries
• Improves the quality of Technical
Assistance delivery
• Status Update.
33
RA-FIT – Revenue Administration
Fiscal Information Tool - Current Status
Rounds of RA-FIT
• Round 1: Paper published:
•
http://www.imf.org/external/pubs/ft/dp/2015/fad1501.pdf
• Round 2: Platform currently live,
includes online data gathering,
analysis and data
dissemination, results due end
2015. Includes Customs module,
Spanish and French option.
• Round 3: In design phase, with
other partners, due for launch
mid 2016. Common question set
• Aim to repeat RA-FIT annually.
Administrative Areas Covered by RA-FIT
• Arrears
• Dispute Resolution
• Institutional Arrangements
• Return Filing
• Revenue Statistics
• Staffing and Office Network
• Taxpayer Registration
• Taxpayer Segmentation
• Taxpayer Service
• Vat Return Filing
• Verification/ Audit
Where to from here?
Work together towards:
• An integrated and better understanding of noncompliance and how it can be addressed by Ministries of
Finance/Treasuries and Revenue Administrations
• The need to understand old traditional and the needs of
“new” Risk Based Revenue Administration
• How can we maximize voluntary compliance and reduce the tax
gap?
• What RA structures and resources are needed?
• What will the return on investment be?
• How can we work smarter and not harder?
The outcome of working smarter in RA ..
• Thanks
Task
• You have returned to your home countries
and briefed the Ministry of the Importance
of using data to improve Revenue
Administration…..
• The Minister wants you to design a Data
Management Strategy for implementation
ASAP
• Each group to prepare a PowerPoint for
the Minister – he only has 10 minutes
Group 1
Group 2
Group 3
Group4
Some tips …
think about data matching, internal
and external data, sharing
between Ministries, resourcing,
tools …..