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Data Driven
Tax Administration
Søren Ilsøe Overgaard
Technology, Data & Security
CTO / CDO / CISO, Senior Vice President
S...
16-11-2016 2
SKAT – consolidation of DK tax and customs
Employees:
12.000  6.000
Annual revenue:
1.000 billion DKK
State
...
16-11-2016 3
Danish Tax & Customs – how did it go?
Customers
one size fits all
>
>
>
IT
requirements
Customer satisfaction...
16-11-2016 4
Danish Tax & Customs – a new strategy
2000s – shared functionality
service-oriented landscape
> legacy / wate...
16-11-2016 5
Danish Tax & Customs – a new target architecture
SKAT IT
System Sources
Direct
Data Sources
Business
Operatio...
Business Targets:
Satisfaction
Tax gap
Claims
Resources
Cases:
KPI Dashboard
Management reports
Internal evalutations
Top ...
16-11-2016 7
Danish Tax & Customs – data-driven insight
Cases:
Call center >< skat.dk  identifying reasons to peaks in cu...
16-11-2016 8
Danish Tax & Customs – data-driven detection
Cases:
Negative VAT model  50% to 85% hit rate
Annual statement...
16-11-2016 9
Danish Tax & Customs – some good advice
- Focus on business needs and targets before buying new technology
- ...
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Data Driven Tax Administration - new strategy for big data, BI and analytics at Danish Tax and Customs

Description of the new strategy at Danish Tax and Customs, SKAT - "A Data Driven Tax with the Customer in Focus", resulting in a new target architecture for big data, BI and analytics that has been used in a number of cases and projects since 2015

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Data Driven Tax Administration - new strategy for big data, BI and analytics at Danish Tax and Customs

  1. 1. Data Driven Tax Administration Søren Ilsøe Overgaard Technology, Data & Security CTO / CDO / CISO, Senior Vice President SKAT, Danish Tax and Customs Administration
  2. 2. 16-11-2016 2 SKAT – consolidation of DK tax and customs Employees: 12.000  6.000 Annual revenue: 1.000 billion DKK State Tax Regional Tax Communal Tax VAT Real Estate Valuation Customs Vehicle Registration Debt Collection IT investment: 0,6  1,5 billion DKK 2005 2020Danish Tax & Customs
  3. 3. 16-11-2016 3 Danish Tax & Customs – how did it go? Customers one size fits all > > > IT requirements Customer satisfaction 69% (2006) 59% (2013) Project fail EFI: 800 MDKK ? Business distance to customers distance to data > > > Vendors 200+ systems development New challenges sharing economy, open transactions, disruption
  4. 4. 16-11-2016 4 Danish Tax & Customs – a new strategy 2000s – shared functionality service-oriented landscape > legacy / waterfall < 2015 – shared data business specific it solutions > transformation / agile < UCCICEEFI CAPTIA “A Data and Analytics Driven Tax with the Customer in Focus”
  5. 5. 16-11-2016 5 Danish Tax & Customs – a new target architecture SKAT IT System Sources Direct Data Sources Business Operations Business Development Data Clients Private Public Capabilities Business Intelligence Advanced Analytics Databank Process Automation Data Export Ad hoc Queries Cross-Public Distribution External Subscribers Big Data Platform DW classic EIM Ana- lytical tools BI tools Data Sources Cross-Public Cooperation “A Data and Analytics Driven Tax with the Customer in Focus” new tech exisiting tech
  6. 6. Business Targets: Satisfaction Tax gap Claims Resources Cases: KPI Dashboard Management reports Internal evalutations Top 25% performers Production reports 16-11-2016 6 Danish Tax & Customs – data-driven productivity
  7. 7. 16-11-2016 7 Danish Tax & Customs – data-driven insight Cases: Call center >< skat.dk  identifying reasons to peaks in customer calls Self-assesment forecast engine  auto-reminder to change your tax Segmentation analysis  customer insight Entrepreneur intro-meetings  effect evaluation Customer journeys  service process improvements Process monitoring  ensure correct processing Data quality/data governance  ensure data ownership, correct data Satisfaction rising 2014-2015: 59%  65%
  8. 8. 16-11-2016 8 Danish Tax & Customs – data-driven detection Cases: Negative VAT model  50% to 85% hit rate Annual statement detection  600 MDKK Money transfer project via BI  1.700 MDKK Tax Havens project via analytics  200 MDKK #PanamaPapers via big data  fast identification Customs  machine learning to score risk on shipments to DK Payments  flow monitoring, automated fraud detection Potential revenue: > 2-3 billion DKK Investment in new tech and projects: 20-40 MDKK ROI: 50x-150x
  9. 9. 16-11-2016 9 Danish Tax & Customs – some good advice - Focus on business needs and targets before buying new technology - Secure programme steering and stakeholder involvement - Involve data department in the idea phase - Prototype before you scale to large projects - Beware of the new legislation on use of personal data

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