What business really needs

Principles behind our conversation Approach Strategic Operational Operating efficiency Driving shareholder value Revenue growth Why do businesses need data? Practically how could data collaboration impact current business process? Capital efficiency Responding to regulation and risk Risk & Expectations

Global market dynamics are causing mass disruption across industries Business is hard pressed to disrupt or be disrupted Global market dynamics A new breed of opportunity, a new breed of competitor Threats from innovative alternate products A new breed of customer – empowered, informed, engaged The blend between product, service and insight Global regulatory pressure in response to Financial Crime, Anti-terrorist threats and Anti-money laundering

Observed business investment in global megatrends Preparation for tomorrow’s market – a blur between product, service and insight Global market dynamics Observed megatrends Disaggregating forces – the pervasive use of digital connectivity to coordinate and mobilise large volumes of consumers to fundamentally disrupt traditional services A new level of personalisation comes to retail products, breaking the grip of stagnant, standardised products and experiences. Next generation of process externalisation – the API economy The embedding of artificial intelligence, machine learning, social sentiment into customer touchpoints, and back-office operations and processes Automated advice management, consumer engagement and social trading

Data is becoming a vital differentiator Data is the new oil Data is becoming a vital differentiator Global market dynamics Observed megatrends Enhanced information about customer Enhanced information about market Businesses that can augment their products and services with insights are likely to succeed in the future market. Collaboration around data between Private and Public sector provides an opportunity to enable our economy to be more competitive. Enhanced information about competitive landscape Enhanced information about risk

Some pragmatic opportunities to collaborate Focusing on shareholder value Streamline customer on boarding – ask fewer questions, allow data to fill in the blanks Operating efficiency Enhanced data quality – all businesses are grappling with inconsistencies in data Revenue growth Practically how could data collaboration impact current business process? Capital efficiency Risk & Expectations

Some pragmatic opportunities to collaborate Focusing on shareholder value Hyper tailored customer experience - embed information and intelligence into customer experience Operating efficiency Hyper personalised product offerings Revenue growth Practically how could data collaboration impact current business process? Improved market research for the identification of new market opportunities Capital efficiency Development of new innovative products and services by leveraging shared data Risk & Expectations

Some pragmatic opportunities to collaborate Focusing on shareholder value Operating efficiency Deduplication of financial crime, anti-terrorist and anti-money laundering processes Collaboration between government, regulatory bodies and business to better manage SA’s risk Revenue growth Practically how could data collaboration impact current business process? Capital efficiency Risk & Expectations

Identified business challenges Wait what about the obstacles? Challenges to opening up are not technical, they are cultural. The principal concern among business is that giving away data gives away value and provides advantage to sharp-eyed competitors. Businesses feel overwhelmed by their own data, and the processes for managing and leveraging data. They feel that to share they first need to get their “own house in order” Business say they are not in the information business, but they know they have loads of data and to participate in the data economy will require too much effort and resources Opening or selling data will create too much of an administrative & regulatory burden and endanger customer loyalty. SLIDE KEY INSIGHTS: Challenge perceptions and culture. Not exploring this will be detrimental to businesses in the future.

What could it look like – the data exchange Models related to open data initiatives Fully and unconditionally open data Data that is open for consumption but with limitations for reuse A combination of open data and high-quality, low- cost data sources Publicly available data as part of the business model No legal obligations to producer Attribution Freemium use Syndicated licence Commercial terms and conditions SLIDE KEY INSIGHTS: Open data in its raw form holds little value, elaboration of this data, through augmentation and advanced analytics can be powerful Demos:

Practical example – Panama papers Leveraging Open Data Using Panama (off-shore leak data) and corporate registries to identify financial crime activities SLIDE KEY INSIGHTS: Open data in its raw form holds little value, elaboration of this data, through augmentation and advanced analytics can be powerful Demos:

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