INSIGHTS FROM THE PROFILE EU PROJECT WHERE TO POSITION DATA ANALYTICS IN THE CUSTOMS PROCESS AND PERFORMANCE IMPROVEMENT CONSIDERATIONS:

1

Prof. dr. Yao-Hua Tan (Delft University of Technology)

Dr. Boriana Rukanova (Delft University of Technology)

MSc. Marcel Molenhuis (Customs Administration of the Netherlands)

Dr. Micha Slegt (Customs Administration of the Netherlands)

Jonathan Migeotte (Belgian Customs)

Dr. Mathieu L.M. Labare (Belgian Customs)

Dr. Toni Mannisto (Cross-border Research Association)

Dr. Juha Hintsa (Cross-border Research Association)

Customs PROBLEM

•  160 M customs declarations/year submitted by importers/exporters to Dutch Customs

•  Most of them have inaccurate data •  Price too low (Undervaluation) •  Incorrect Description of Goods (e.g. ‘Toys’)

•  Due to e-Commerce, Brexit declaration could increase to 450M/year by in a few years!!

•  This steep increase can not be solved by hiring more inspectors, only by more automated processing of declarations with IT innovation

•  IT innovation •  Collect extra business data (e.g. purchase order, invoice, container

packing list) to cross-validate declaration data •  IT infrastructure for sharing data in international supply chains •  Data Pipeline, Blockchain and Big Data analytics

2

Data Pipeline (Frank Heijmann, David Hesketh)

3

Consignor or Exporter

Consignee or Importer

Container/Carrier

Freight

Forwarder or 3PL

Freight

Forwarder or 3PL

EU Regulation

Country B

Port 1

Port 2

CARGO

3rd Country Regulation

Country A CARGO CARGO CARGO

Ph

ysic

al la

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Org

anis

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nal

la

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Dat

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Do

cum

ent

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“Internet for Logistics” developed in EU research projects e.g. CORE, CASSANDRA, ITAIDE

4

Global data pipelines already scaling-up e.g. TRADELENS Blockchain IT platform

Paperless Trade (Blockchain Network)

Export

Inland Transportation Port / Terminal Authorities

3PL Service Providers

Packing List

Export documentation

Bill of Lading

Shipping instructions

Commercial Invoice

Exporter / Consignor

Import

3PL Service Providers

Importer / Consignee

Inland Transportation Authorities Port / Terminal

Shipping Information Pipeline

Certificate of Origin

Dangerous Goods Declaration

ISF

Not exhaustive list of Events tracked by platform

Note: representative only; not all documents require Paperless Trade nor is this an exhaustive set of documents that could be processed by Paperless Trade

Advance declaration Customs

Clearance

Geography specific

certificate

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Cargo specific

certificate

Import documentation

Pre-paid invoice

Hyperledger Fabric

Data sharing and data analytics as next steps

•  “Get Data from the Source”; Customs should use more trade data to cross-validate accuracy of import/export declarations

•  Examples: invoice, purchase order, packing list •  Companies are willing and able to share their trade data via IT

platforms with customs •  Able; Most companies use enterprise information systems (e.g. ERP) •  Willing; if it provides less inspections (= “trade facilitation”)

•  Data sharing among customs administrations, as well as between Customs and other agencies nationally and internationally

•  Combining data from different sources can improve risk management

•  Data analytics as a next generation IT innovations for customs

5

Current research in the PROFILE EU-project

•  4 Living Labs for using data analytics in customs in different countries

•  Living labs pilot with data analytics based on: •  Internal customs data •  External government data from other customs or

other government agencies •  External data from eCommerce websites •  External data from data pipeline providers

Risk Analysis in the Customs Clearance Process  

8

Different Options of Where to position Data Analytics in the Customs Process  

9

Declara'ons

Riskrules

Notselected

Selected

Notselected

Selected

Truenega've

Falsenega've

Falseposi've

Trueposi've

Capturinginspec'onresults

1 2

3

DA?

DA?

DA?CountryA

Compare/Validate

Declara'ons

Riskrules

Notselected

Selected

Notselected

Selected

Truenega've

Falsenega've

Falseposi've

Trueposi've

Capturinginspec'onresults

1 2

3CountryB

4

DA?

Where to focus the performance improvements with Data Analytics  

10

Declara'ons

Riskrules

Notselected

Selected

Notselected

Selected

Truenega'veFalsenega'veFalseposi've

Trueposi've

1 23

??

Largeincreaseindeclara'onvolumes

?

Observations •  Decision points where DA benefits are most useful

•  Use DA to decrease False Positive inspections? •  Now typically 94% False Positives •  What if DA would improve that to 70% False Positives? •  Less ineffective inspections, hence increase customs efficiency

•  Needed to be able to process the huge growth in declarations due to

e-commerce and Brexit

•  Use DA to decrease False Negative inspections •  “catch more illicit trade”

•  Different types of DA innovation (e.g. different training data sets)

•  Customs Resource limitations constrain DA benefits •  More true positives also requires more customs staff

•  to inspect •  for administrative after processing (fines, reporting etc.)

•  Trade-offs have to be considered between DA innovation and customs resource limitations

11

12

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The business school that thinks

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developments force customs authorities to collaborate with

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different stakeholders and guest speakers who will provide you with

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ACADEMIC EXCELLENCE You will benefit from this programme’s unique content, which

is built on the strengths of faculties from three universities:

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EXECUTIVE MASTER IN CUSTOMS AND SUPPLY CHAIN COMPLIANCECombining safety, security and sustainability with compliance

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https://www.rsm.nl/master/executive-masters/executive-master-customs-and-supply-chain-compliance/overview/

THANK YOU!

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Prof. dr. Yao-Hua Tan, Delft University of Technology y.tan@tudelft.nl Program Director Master Customs and Supply Chain Compliance Rotterdam School of Management Scientific Coordinator EU projects PROFILE, PEN-CP, CORE, CASSANDRA, ITAIDE www.profile-project.eu www.pen-cp.net