“Let’s do the right thing from the very beginning because the right structure will stand the test of time.”
AI is a revolution
Chapter 6 Artificial Intelligence (“AI”)
The Emerging Payments Association (EPA) Asia is a commercial membership association of payments industry influencers. EPA Asia is part of the growing EPA global network. It runs more than 30 events each year, delivers eight projects annually to drive change, helps to connect the ecosystem, encourages innovation and profitable business growth. The EPA’s vision is for Asia is to be the regional Knowledge Hub for payments innovation. As it sets out to be the most influential trade body in emerging payments, the EPA’s mission, to collaborate to innovate, has the potential to improve lives everywhere.
“The revolution in deep learning has been very profound. It definitely surprised me, even though I was sitting right there.” Sergey Brin, Co-Founder, Google
Analytics is a broad term
Analytics is a broad term that can be better understood in terms of degree of difficulty and degree of value:
- Inputs (low difficulty, low value)
- Descriptive analytics help us to understand what happened in hindsight
- Diagnostic analytics help us to understand why it happened to gain insight
- Outputs (high difficulty, high value)
- Predictive analytics help us to understand what may happen and to apply foresight
- Prescriptive analytics help us to shape the future to optimise the outcome
AI helps to deliver the higher value, higher difficulty analytics.
AI is an even broader term – we need a taxonomy
Artificial intelligence technologies and tasks include the following:
- Machine learning
- Natural language processing
- Computer vision Robotics
- Distributed artificial intelligence
- Evolutionary algorithms
- Expert systems
An algorithm is not in itself AI.
Governance framework for the adoption of AI
The governance framework for AI needs to establish the right structure now in order to withstand the test of time. It needs to sit on a framework of ethics and morals in order to assess the boundaries of authority. Otherwise how will we know that ultimately the humans are still in charge? What if the AI is in charge? How do we prevent a range of bad outcomes from unintended consequences due to poor substitution or black box processes right through to hyper-automation and hostile AI?
Leaders in AI Adoption
AI brings a lot of benefits and can be integrated into the core strategic business. Early adopters will benefit more than late adopters.
Foundational AI Skills for Everyone
Do we regulate the legal actors (the humans and corporations) or the outcomes they deliver?
You cannot regulate “the tech”!
You can regulate the driver of the car, or the manufacturer of the car, but not the car itself.
We must understand the marriage of ethics and governance. Ethical and trusted AI will meet regulatory outcomes. So let’s do the right thing from the very beginning. We must be very aware of bias, especially gender and racial bias.
If we ask the rights questions, we can get the right answers. But you cannot ask the right questions if you are not already educated and informed on the topic.
Role of Regulators
Are the regulators ready to regulate in this area?
Regulation is often said to be “lagging.”
If something goes wrong, trust is broken. But we should not be regulating the fear of what AI could do. We should be regulating on what it actually does today which is whatever its masters tell it to do.
Customer-focus and the product life cycle
AI is in the toolbox and we have to learn how to use it. Can technology be a force for good to enable and mitigate against human failures?
Complexity is the enemy of transparency. Biases can thrive unchecked inside black boxes. There is a clean sheet opportunity for neobanks and fintechs to use technology for financial inclusion. Technology is a powerful gateway to inclusion. While there are problems, and AI is still in its infancy, there is also a “fat middle” where we can start.
Computer says “No”
The AI is not (yet) very good at positive discrimination via nuancing and justifying exceptions. It is excellent at cutting through volumes of data very efficiently and, to do that, most of what it has to do is to exclude rather than to include.
There are some high profile fails from big tech. Financial data is highly sensitive. The repurposing of data, for a use other than that for which it was initially harvested, can be especially problematic.
Board Member with International Experience in Fintech, Governance & Artificial Intelligence 🌐 Speaker, Author & Investor
Clara is a technology strategist specialising in financial services. Her focus is the strategic adoption of AI for business growth and profitability.
Internationally recognized for her expertise, advising Boards of leading financial institutions, think-tanks, and governments, Clara also mentors AI startups on technology development, funding, and scaling.
Named on global lists of leading women in Fintech, she is also the Chair of the Non-Executive Directors Board’s special committee on Best Practice for AI Adoption (UK). Clara advised World Economic Forum’s 4th Industrial Revolution Centre (US) on AI for Boards, the UK’s APPG AI(UK), the Ministry of Internal Affairs special commission on AI (Japan). Clara was invited as a member of the EU AI Alliance.
Clara is a frequent speaker at leading conferences like SIBOS, Money 2020, Innovate Finance Global Summit, AI World, SCxSC, Fin/Sum. She has been invited as a guest lecturer by leading universities like the University of Oxford’s Center for Technology and International Relations and MIT. In 2019 she was invited to join the teaching team at the Oxford AI course.
Her academic interest sits at the intersection of neuroscience, AI and wealth management. Prior to 2014, Clara served in leadership roles in European asset & wealth management, is a member of the Chartered Institute for Securities and Investment (UK), has a Certificate in Investment Management (UK) and holds a Master’s degree from the University of Oxford.
Kimberley Cole (CIM, MAICD)
Intelligently Connecting. Helping the world’s knowledge seekers, builders and sharers amplify the impact of business insights.
An award winning, Hong Kong based, Global Senior Executive with 25+ years Sales & Marketing Leadership experience. I am a firm believer in constant innovation inspiring purpose company wide both in generating business & attracting & developing high-performing teams.
Focused on customers, I have built successful and solutions-oriented organisations to meet changing market needs that produce strategic growth. My regional and global marketing roles provide a solid foundation to further expand my Senior Management capabilities & customer-focused strategy. This is further enhanced by my Product Management experience, ensuring an end-to-end enterprise view from development to go- to-market.
I have a proven track record of success and ability to identify & tackle a wide range of business challenges. I have always worked very closely with my clients, offering them superior customer focus & insight.
Creating innovative industry networks ‘Women in Finance Asia’ & the global ‘Risky Women’ network for professional women in Risk, Regulation and Compliance. I am the Chief Risky Woman and the host of the podcast series, ‘Risky Women Radio’.
In 2015, I co-founded ‘Trust Forum Asia’ to fight slavery & have continued to develop platforms to engage businesses to take action via the launch of the ‘Stop-Slavery Summit’. Previously I was the Chair/Co-Chair of the ‘Women @ Thomson Reuters’. I am also Non-Executive Director of the ‘Fair Employment Foundation’, an organisation dedicated to fixing a broken recruitment system for Domestic Workers in Hong Kong & The Philippines.
I was named one of Cranfield’s ‘FTSE 100 Women to Watch’ in 2013/ 2014, ‘AmCham Hong Kong Professional of the Year’ 2015 & was a finalist in the ‘Telstra Asia Business Women of the Year Awards in 2016’.