Global data wars

Transcription

1 Global data wars

2 It changes the rules for markets and it demands new approaches from regulators. Many a battle will be fought over who should own, and benefit from, data. The Economist May 17

3 Data is fueling the latest industrial and economic revolution. By 2020, half of the Fortune 500 will be connected to open and automated information exchanges to enable rapid provisioning of data services for governance and product development. 48% of Data Executives are commercialising their data - that s up from 32% last year. Open Data can help unlock $3-5 trillion in economic value annually across seven sectors in the United States alone.

4 Data will be the single biggest driver of microeconomic and social reform in the next two decades.

5 Privacy vs. Innovation Privacy Security Identity Trust Governance Consent Transparency Innovation Data Sharing Collaboration Open Innovation Liquidity Value

6 Global landscape Unconscious trade-off between Privacy and Innovation China is showing the world what s possible Country Privacy vs Innovation China P I Europe P I USA P I Leading light economies attempting to demonstrate mature models and UK P I leverage to win global trade (UK, SG) Singapore P I Policy settings have significant implications for domestic settings and global trade India/ Indo?

7 Where does Australia sit in all of this?

8 Australian position very progressive foundations Consumer Data Right and Open Banking framework economy wide and long term Consumer control over information Consumer choice in banking Smart implementation creates opportunity to further enhance architecture for data economy Control Choice Core opportunity: Maximizing INNOVATION while minimizing systemic RISK in the digital economy delivering better outcomes for citizens. P I P I Confidence in the use and value of data Confidence Convenience Consumer convenience in managing money 8

9 These foundations will have long term implications for the architecture of Australia s Data Economy Foundation long term impact from decisions taken now Need for connected strategy Digital ID, KYC Transfer, Open Gov, CDR, Data Sovereignity Trade implications the nature of the rails will determine trade flows Creating the foundational framework that is most attractive potentially lay down the rails for the future data economy in many markets

10 Core architectural principles for building a data economy

11 Architectural Principles Secure / Private by design Tokenization of PI as the default Shared infrastructure to manage an ether of PI (decentralized, tokenized, encrypted, sharding) Elimination of honey pot approaches Minimizing replication / flow of raw data from high-security to low-security environments Modular approach to development

12 The Mature Model for Citizens Joint Ownership Joint Consent Joint Reward Right to be deidentified Neither the consumer not the corporate has outright ownership of the data. Granular, clear consent with permitted-use methodology. Consumers can easily trade up/down their level of consent Economic rights to value consumer data are transparent and shared consistently & fairly Consumer identity is tokenized and consumer protections can be enabled through a detokenization process

13 How to align around the opportunity

14 10 Priorities for succeeding in the Emerging Global Data Opportunity 1. Develop a national strategy to win 2. Create the Central Statutory Authority for data 3. Embed secure/private by design principles in the architecture of the data economy 4. Connect all data related policy to the national strategy 5. Create the world s best practice policy and legislation (modern privacy laws) 6. Public and private sector collaboration 7. Development of a vibrant ecosystem of data product developers 8. Increase focus on data for social good' 9. Capitalize on export opportunities 10. Connection to AI

15 What is at stake Productivity Gains and Microeconomic Reform Export Growth in Technology Social Reform Foundational basis for development of an AI Industry Greater Security Industry Development

16 Applying these principles to Open Banking in Australia

17 Lessons learned from UK and implications for AU Open Banking Going first positives and negatives Limited to just banking we should have bigger ambitions Raw data flows as only option technology offers more Mandated technology solutions mandate outcomes and let markets solve for technology Trade strategy a smart play 17

18 What are the big things left to play for in Open Banking Reciprocity and derived data Accreditation thresholds Permitted use taxonomy 18

19 How do you get more innovation with less risk? Raw data access Data moves to algorithm Security thresholds Output only Algorithm moves to data 19

20 The role of middleware in the system more innovation, less risk ENABLES COMPETITION AND SUPPORTS INNOVATION Low cost/security accreditation Reduction in systemic data risk (security) Algorithm to data (secure environment) INCREASES CONSUMER PROTECTIONS IN BANKING Improved AML and fraud detection Middleware: Provider of customer services to fintechs (e.g. customer controls) Auditability Secure Platform Facilitation of secure digital identity Responsible lending 20

21 How Reinventure is investing to build out capability for the Data Economy

22 4 main areas of investment in data economy Connecting data for relevance Banking Infrastructure for Data Long tail of data needs to be aggregated Connecting across domains and driving common taxonomy Enabling data to flow like money with the same trust, security, privacy and governance Critical enabler of new ideas Slyp Application layer enablement AI applications that make use of well governed access to data A.kin Protecting data assets As increasing proportion of our digital assets become exposes online, they need to be protected from asset stripping

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