Strategic Plan of Korea Customs Service for 4th Industrial Revolution

Yonghwan CHOI, Deputy DirectorInformation Planning DivisionKCS

Ⅰ. Background

Ⅱ. Major Breakthrough Technologies

Ⅲ. KCS’ Experience and Roadmap

Ⅳ. Conclusion

Ⅰ. Background

Progress

“ From Industry 1.0 to Industry 4.0 ”

Ⅰ. Background

Progress of UNI-PASS

Simple

On-line

Statistics

EDI

Clearance

System

Internet

Clearance

System

Smart

Clearance

System

[1st Generation]

[2nd Generation]

[3rd Generation]

[4th Generation]

Simple Statistics Business automation Business enhancement Business intelligence

2016

2005

1992

1974

Ⅰ. Background

Leveraging Industrial Revolution Technologies

Global Trade: BLOCK CHAIN + AI + BIG DATA

Blockchain Platform Financial

Transaction

Ⅰ. Background

Domestic e-commerce im/export trends

Background: Explosion of Ecommerce

Domestic/International E-Commerce Im/Export TrendsInternational e-commerce market share

Ⅰ. Background

※ Korea Statistics Bureau ※ Source : U.S. eMarketer, Jan. 2018

Worldwide e-commerce transactions

Export Import

6.2

14.911.5

15.5

20.817.3

26.8 20.4(USD100 mil.)

1.915

2.3522.86

3.418

4.058

Unit : USD 1 tril.

Background: Workload vs. Workforce

Budget

Personnel

Efficiency

Matters..As E-commerce grows,

ICTTechnologies

Smuggling

Volume of

small

parcels

Revenue

Collection

Entry

Barriers

Ⅰ. Background

Cargo + Passenger

Background: DATA

All data lead to Customs !

Monetary

Import/

Export

Passenger

Origin

Company

Tax

Ⅰ. Background

Ⅱ. Major Technologies

Major Technologies of revolutionⅡ-1. Major Technologies of 4th revolution

Key Technologies for Customs

Audit Surveillance Information FTA

Big Data

AI

Blockchain

IoT

Cloud

Open API

Ⅱ-1. Major Technologies of 4th revolution

Ⅲ. KCS’ Experience

Overview: Definition

Public Blockchain

A technology that allows people who do not know each

other to trust a shared record of events.

Ⅲ-1. Blockchain

Business efficiency / Reduced errorsNo paper doc. exchange / No errors when manually

entering data / Real-time information exchange

Confidentiality / Transparency in tradeInfo sharing only with authorized parties / Provision

of integrated visibility to stakeholders

Scalability / Security (Immutability)

Cross-border trade

Bank Exporter

Importer

Shipper

Port Inland transporter

BC case1: Export Clearance Blockchain

Current Status and Improvements

Ⅲ-1. Blockchain

AS-IS TO-BE

Legend Paper doc Linked

Bank/

InsuranceKCS

Customs

BrokerTerminal

Inland TransporterExporterImporter

Airline/Shipper

Forwarder

Export clearance logistics service

(Data Pipeline)Exporter Importer

Airline/Shipper

Forwarder Terminal

Bank/Insurance

Inland

Transporter

Legend Paper doc Linked Disconnected info

Customs Broker

BC case1: Export Clearance Blockchain

CertificatesKCS E-Clearance System

Declaration +

Trade Documents Data exchange

Customs/importers

IT companies

‧ Im/Export manifest consolidated

‧ Import manifest & Import

declarationImporters

Airliners

Shipping company

Export M-B/L / Export

loading

declaration

Forwarder ‧ Export H-B/L- Inland Transport

InformationTransporters

‧ Export declarationCustoms

brokerFinance/

Insurance

‧ L/C/

Cargo insurance

Terminal‧ Cargo entry / release

Exporters‧ Contract, Trade document

Blockchain-based

Export clearance &

logistics services

(B2B+B2G)

Blockchain-based Im/Export Clearance Services

Ⅲ-1. Blockchain

BC case1: Export Clearance BlockchainⅢ-2. Big Data

BC case2: B2C & C2C (E-commerce)

AS-IS TO-BE

Register order

info

Re-register

order info

Transmit order info

(file, email)

Transmit order info

(file, email)

Manual

completion of

clearance list

Register order info

Transmit order info

(file, email)

Buyer Offline process

Human errorsEcommerce

Operator

Online

mall

Delivery

agent

Express

shipper

Customs

1 2 3 54 6

1 2 3 54 6

1 2 3 54 6

1 2 3 54 6

1 2 3 54 6

1 2 3 54 6

1 2 3 54 6

Ⅲ-1. Blockchain

Disconnected data Risk of forgery &

falsification

AS-IS TO-BE

C/O issuance and submission in paper document form Issuance and exchange of Blockchain based e-C/Os

Exporter

Korea

ImporterKCS

Counterpart

Customs

1 Export declaration

C/O issuance application

C/O issuance

2

3

5 Imp. Declaration

C/O Submission6

(in paper)

C/O delivery (in paper)

(Express shipping, mail)3

* e-C/O (Electronic Certificate of Origin) : C/Os which are electronically issued and distributed

Data pipeline for C/O issuance and exchange

Ⅲ-1. Blockchain

BC case3: G2G (e-Certificate of Origin)

E-Government Platform (Blockchain)

Exporter ImporterCustoms

1 Exp. declaration +

C/O issuance application

e-C/O issuance2

4 Imp. Decl.

(C/O submission exempted)

e-C/O transmission (block sharing)3

e-C/O transmission

(block sharing)

KCS

Korea Counterpart

Implications of Paperless Trade

Need to convert to digital clearance and logistics documents

※ Source : The Economist, ‘The global logistics business is going to be transformed by digitalisation’, May 14, 2018

The Economist, ‘The The digitisation of trade’s paper trail may be at hand’, May 14, 2018

Ⅲ-1. Blockchain

Expected outcomes from establishing the blockchain

Qualitative effects Quantitative effects

Ⅲ-1. Blockchain

Overview

Definition of Big Data

Ⅲ-2. Big Data

Overview: Why Big Data?Ⅲ-2. Big Data

AS-IS TO-BE

Internal data

External data (Irregular)

Used data

Unused data

Repetitive&Manual

Intelligent crackdown of illegal acts

Relying on personal competence

Limitations of data processing /

analysis

A lot of time is required for

preprocessing

Enhanced proactive detection

Integrated analysis environment

for data

To save time from searching data

Main Challenges Value creation through big data

Overview: Why Big Data?

As-Is(Existing

data)

To-

Be(Big data)

Value creation of Customs through big data

Enables to provide optimal clearance and

logistics services

Enables work and services which used to be

unviable

Enables data based decision-making for

policies

Enables real-time analysis and prediction of

signs of anomalies

Improved productivity from intelligent work

(minimized manual work)

Ⅲ-2. Big Data

KCS’ Approach

1

2

3

4

Preparing Big-data development process

Fostering internal big data experts

Strict data quality management

Prepare big data analysis infrastructure

Ⅲ-2. Big Data

KCS’ Approach : Training Internal Experts

16

24

100(Persons)

`17

`18

`19~`21

16 40

16 24 60 (20/year)

Ⅲ-2. Big Data

Comparing SI project with big data project

KCS’ Approach : Development Process

Ways to move forward KCS’ big data project

System planning

Collection of related data(internal + external)

Repetitive tests/pilot project analysis

Exploring new values

Service development and operations

Continuous activity

Feedback

Big data project

System planning

Budget planning & funding

Selection of implementer

Development

Service operations

One-time project

SI project

Verification cycle for task effectiveness

Observation

HypothesisTest

Big data project type

Hypothesis & test

Pilot project

Actual project

Infrastructure expansion project

Big data operations project

Ⅲ-2. Big Data

Best practices3: FINDER modelⅢ-2. Big Data

Implications

Implications

Compliance(Security)

Facilitation

Safety & security without effecting

simplified clearance

Preventing tax evasion without

more labor force

Analyzing the behavior for better

system without further requirement

Ⅲ-2. Big Data

Expected effects from establishing big data

Qualitative effects Quantitative effects

Ⅲ-2. Big Data

Overview: Definition

What is “Artificial Intelligence (AI)” ?

“… every aspect of learning or any other

feature of intelligence can in principle be so

precisely described that a machine can be

made to simulate it. …”

Artificial Intelligence

Source : “Stanford Innovators”

John McCarthy, 1927-2011

Ⅲ-3. AI

KCS Approaches

How to Make AI?

Phase 1. Training

Phase 2. Inference

Algorithm

DataExpert

Database Algorithm Model

New Data Model New Insight

Ⅲ-3. AI

KCS Approaches: AI X-Ray

Short Demo

Ⅲ-3. AI

KCS Approaches: Adoption of AI-based Smart Clearance System

AS-IS TO-BE

Due to excess workload, cursory selectivity/audit occur.

Excess daily workload per person

Cursory P/L audit

Use of AI for simple, repetitive, consuming work

Resolve excess workload

Shift to field-centric work

Im/E

xport

decla

ratio

n

Decla

ratio

n

acce

pte

d

P/L audit1P/L audit2P/L audit3

∨

Ⅲ-3. AI

Implications

Qualitative effects Quantitative effects

Ⅲ-3. AI

Ⅳ. Conclusion

Conclusion

Crime & Trade have no borders.

More the Better (Data Volume & Quality Control)

Many PoCs, Case & Pilot Studies

Domain Knowledge

International Tools & Framework

Network Effect

Must

ImplementationCooperation

Ⅳ. Conclusion

Co-Work Plan

Policy collaboration Case

Block Chain Based e-C/O Linkage

Sharing Big Data Analysis Model

Sharing AI Business Model

Sharing new technology application guidelines by Korea

Customs Service

Linkage system

Sharing Model

Guide-Line

Ⅳ. Conclusion

Yonghwan CHOI, Deputy DirectorInformation Planning Division

yonghwanc@korea.kr