This document discusses opportunities for innovation in the data-centric economy. It notes that data is the lifeblood of business and its use is reshaping the economy through data analytics, machine learning, artificial intelligence and other data-driven services. Examples of opportunities include FinTech applications like lending, payments and wealth management. Developing into a smart city requires using open data policies and real-time traffic data to enable tools for urban management. Privacy, cybersecurity and trust are crucial considerations for policymakers seeking to support data-driven economic activities through regulations that maintain competition while fostering certainty and consumer trust.

1. Opportunities and
Policies for Innovation in
Data-Centric Economy
Fuji Xerox SPARK Innovation Expo 17 Nov 2016

2. the lifeblood of any business
in the years to come

3. Big data:
using structured and unstructured data
in innovative ways to promote efficiency,
productivity and to develop new product
offerings in a more meaningful way.

4. Commercialisation of disruptive
new data-driven services is
reshaping our economy
Examples:
• data analytics
• machine learning
• artificial intelligence
• data brokerage
• data marketplaces
• On-demand services

5. How to capture
opportunities?
E.g. FinTech

6. Lending
Payments/billing
Personal finance / wealth management
Money transfer
Blockchain/digital currencies
Institutional tech
Equity crowdfunding
InsurTech
◇FinTech’s definition continues to evolve
◇Technology continue advancing the banking, financial
services and insurance sectors
data

7. no smart city works without data

8. Hong Kong:
aiming at developing into a
‘Smart City’ in the years to come
use of open data policies:
enable software-driven urban
management tools

9. Smart grid, smart home, smart living

10. Real Time Traffic Data
across public transport

11. From BIG data to SMART data
with AI and machine learning
Create value by focusing on meaningful pieces of
information for more accurate decisions

12. UI that can read your mind
to suggest or highlight
actions that are relevant will
generate biggest value
Improve engagement and turning first time customers into repeat buyers.

13. 45%of online shoppers
are more likely to shop on a site
that offers personalised
recommendations
Source: Invesp

14. How can data improve eCommerce?
Predictive Analytics
Predictive Search
Targeted Recommendations and Promotions
Pricing Optimisation
Fraud Management
Inventory Management
Business Intelligence

15. How can the legal and policy
environment be changed to
support data-driven
economic activities?
Help incumbents evolve: build
collaboration and networks to
spur innovation
Maintain effective market
competition, ease of market
entry
Test in Sandbox: more
collaborative approach to
regulation, test first regulate later
Clarity in regulations: foster
certainty and consumer trust
Open data and API: in public
and private sector

16. Policy
Creating
market
demand
Talent and
capacity
building
Making
Data
Work
User-centric
mindset
Innovation-
friendly
regulations
Infrastructure
balance the needs of citizens, industries and new digital businesses
with globalised data-driven platforms and services

17. Crucial:
Privacy
CyberSecurity
Trust

18. Facebook: Charles Mok 莫乃光
Twitter @charlesmok
charlesmok@charlesmok.hk
www.charlesmok.hk