Décryptage par EY
The case of Healthcare
- AI is able to put everything in its context
- AI will anticipate everything
- AI quantifies everything (e.g. we can identify on which cell we can modifiy the gene)
With the help of AI, we can monitor health data and put it in context (e.g. health profile) and can recommend treatment and anticipate desease.
Watson: monitoring data, put it in context, and then assist.
- Hospital/Clinic staff who are doing the job today have to adapt and understand AI.
- Financial analysts are losing jobs.
« The AI phenomenon is across the economy, going up, and disrupting white collars. »
- It is moving too fast and we need to quickly discuss what we can do with it
–>Accelerate collaborative initiatives such as OpenAI
« We’re augmenting individuals »
There will still be human touch (e.g. empathy and risk, social equation)
- Humans decide when it’s possible : what data is available, when we plug or unplug the system.
- Question of data ownership (IoT – e.g. who owns the health data? who owns the home data which monitors my activity to drive energy consumption)
- New concepts will appear, incl. ethical (e.g. crash management for autonomous vehicules)
« We need to discuss these concepts now as we are building those models. »
Enabling the digital payments lifestyle
- Foundations: Visa, Mastercard etc. sat together and agreed on tokenisation that permitted everything.
- Risk: How can we mitigate risk ? Making sure we can scale digital payments.
- Connectiviy: The explosion of connected world introduces great complexitiy that we have to manage.
Foundation principles :
- Security: tokenisation provides level of’security required and renders payment and transaction information useless if compromised
- Transparency: the payment experience should be seamless, branded and intuitive to give the consumer piece of mind
- Accessibility: e.g. Samsung Pay, Google Wallet and Microsoft agreed to use mastercard platform and standards
- Privacy: ensure data and personal information from digital devices solely for the intended purposes
Where we are now:
- Wearables and unattended retail
Where we are heading:
- Conversational and contextual commerce (e.g. in your car or in your home).
- Chatbot : engage customers
- AI and robotics: augmented retail thing
Mastercard announces partnership with GM and Watson for C&C commerce in a car
Accelerating Technology Trends and Drive Opportunities
NFC Applications Growth – Same technology for several usages
Biggest Challenge : Bringing the Ecosystem Together
« You are your own password »
- Ease of use: wearable device reduces friction. Identification authentification and validation are automated.
- Example of use case : biometrics validation through digital identity
- How do we make it useable and easy to use.
Transformation from Collaboration
Example of Marstone, a white label wealth management platform.
« Marstone is a contemporary, user-driven, digital investment advisory that enables everyone to take control of their finances with easy-to-use, feature-rich tools. We focus on the needs and expectations of busy wealth managers, as well as the changing requirements of a new generation of clients and investors. »
Transformation is coming from collaboration. Especially with AI companies.
Highlight of Trends
– Blockchain and AI will not change business models. However RegTech will reduce costs where spending is out of control. The key trend here is recognition.
–>Shift on RegTech, focus on recognition
– Financial instituitons are becoming tech companies.
– AI economy: it is difficult from a scientific standpoint. You can hire best coders and they can’t solve it. You need to solve things in a way that is not done yet.
– Natural language: it’s about ease of use, and simplicity ! It is how to deliver AI experience.
– Innovation is not coming from financial market players
– Distributed ledgers are driving new economical players, beyond financial institutions. Different blockchain environments can be used.