Data sharing is undergoing a fundamental shift - from enabling operations to creating new economic and social value for both organisations and their customers. An example of this shift is Singapore’s newly-launched Trade Data Exchange, SGTraDex, which is expected to unlock over S$200 million in value annually when fully developed.
According to the OECD, data access and sharing can help generate social and economic benefits worth between 1% and 2.5% of GDP, equating to about S$12.3 billion for Singapore.
To address the growing need for responsible data sharing, the Association of Banks in Singapore (ABS) launched the Data Sharing Handbook for Banks and Non-Bank Data Ecosystem Partners on 30 August 2021. Developed over 15 months in close consultation with ABS SCDM members, ecosystem partners, MAS, IMDA and PwC Singapore, the Handbook provides a strong foundation for banks and ecosystem partners to make the most of their data. It is a helpful resource for responsible, lawful and secure data sharing. It builds on IMDA’s Trusted Data Sharing Framework, with a sharper focus on data sharing between banks and non-bank ecosystem partners and the risk management considerations required for banking data.
The three steps across the data sharing journey make up the iterative framework that organisations can use. As the handbook mentions, the depth and level of detail required at each stage depends on the maturity of each party involved, as well as the nature of the data sharing engagement and type of data being shared. However, detailed consideration of laws and regulations and alignment with data sharing principles is important at all stages of the journey.
Source: Data Sharing Handbook by ABS
PwC Singapore has empowered clients across industries to navigate the potential obstacles to data sharing and identify key elements that can facilitate their data sharing journey. The newly-launched Data Sharing Handbook helps us support the journey further, with a clear common language being set for data sharing in Singapore.
1. Formalise and industrialise the data sharing journey including establishing and communicating clear, robust principles.
2. If a use case requires the exchange of sensitive data, organisations can explore emerging privacy preservations techniques (PETs) and models to improve the privacy and security of that information. These can include techniques such as altering the data itself, controlling and granting selective access, or even codifying the data sharing through a trusted, decentralised transaction layer like blockchain.
3. To improve the likelihood that the data is fit for purpose, data sharing participants should share important metadata early and often in the process.
4. Finally, when it comes to the negotiation of regulatory and legal obligations, organisations should identify appropriate legislation and distill those requirements into clear guidance for their lines of business to act on.