There are major themes driving the financial services’ future, encapsulated in the January, 2017 Financial Services Roundtable (FSR) FinTech ideas Festival (FIF).
The FSR, a Washington DC-based trade organization, represents approximately 100 top CEOs in financial services, with 92.7 trillion USD in managed assets and 1.2 trillion in annual revenue. This is close to the GDP of Canada at 1.6 trillion and would place FSR in the G20 in rankings. The entire industry is about 14 trillion in revenue. You will see familiar Canadian names in its members list such as BMO and TD.
The FIF is an invitation-only CEO-focused event with themes of: financial inclusion, future of the workforce, Internet of Things and big data, cybersecurity, blockchain, biometrics, and artificial intelligence.
What is machine learning
Requiring special focus and underlying everything (including all the FIF themes) is artificial intelligence (AI). AI through machine learning is impacting on a planetary scale.
Machine learning, with five main types, allows computers to recognize patterns in data and learn new tasks on their own, difficult or impossible, with direct programming. The school of machine learning getting much attention today is deep learning.
AI machine deep learning growing in importance
A good overview in deep learning is the now on-demand July 7th live presentation and Q&A session with the legendary Google Senior Fellow Jeff Dean. Jeff is the legendary scientist who has led major innovations in cloud computing, search, advertising, and deep learning.
There is the newly announced Microsoft Professional Degree comprised of the core data science skills to meet the demand of nearly 2 million jobs. These courses are free unless you wish certificate recognition.
Making the headlines this year was a deep learning computer mastering the champion Go player. The abstract strategy board game is a feat to happen in 2026 (and not the 4-1 match wins of DeepMind’s AlphaGo beating Lee Sedol in March, ten years ahead of predictions). And with the Internet of Everything, there are enterprises transforming and using the data deluge of more than 44 zetabytes (by 2020) or 44 billion terabytes, and machine learning is the key.
Chatbots in the millions
Today, no one owns the customer. The landscape is incredibly flat for consumers who are in complete control.
The proliferation of AI agents, advisors and chat bots are assimilating the data in mass providing predictive assistance to everyone. Facebook messenger already has close to 12 million. Thus, the power is in the consumer and they will own themselves treating all services as commodities and changing at the slightest whim where there are better benefits.
AI will deliver on consumer expectations that their experiences be mobile, personalized, customizable with 24/7 access, and with this evolving through embedded technology providing virtual and augmented reality and deep neural communications. With this seamless interaction and net promoter scores, customer loyalty is already much higher for Fintech startups.
AI inflection point changing financial services
AI is creating a digital quake where 80 percent of companies and jobs will need to change or fail.
It’s an unprecedented era of:
- Hyper time compression in the emergence of new disruptive innovations—measured in days and weeks rather than years.
- Extreme convergence of multiple domains: physical, digital, biological – where they are overlapping amplification of value.
- Exponential accelerating automation – triggered by smart sensors and the IoT (can be up to 11 trillion USD by 2025 according to McKinsey).
- Connectivity linked by a digital AI mesh – through the rapid deployment of machine learning.
The disruption is already happening with funds transfer, payments, banking, asset management, wealth management, and insurance.
AI proof points are everywhere
For this reason, AI features heavily in the best sellers 4th Industrial Revolution by Professor Klaus Swab, founder and executive chairman of the World Economic Forum, the Rise of the Robots by futurist Martin Ford, and with the Second Machine Age by MIT professors Brynjolfsson and McAfee. UBS talks about the implications of AI in their excellent white paper for the World Economic Forum with financial services listed in their chart detailing “sectors at risk of disruption by AI.”
There is the IBM Watson AI XPRIZE challenging teams from around the world to solve the world’s greatest challenges using AI with three finalist teams (perhaps even pure AI and robots) taking the stage at TED2020. These big challenges can involve the FIF themes of: financial inclusion, future of the workforce, Internet of Things and big data, cybersecurity, block chain, biometrics, and more. IBM Watson received special attention when demonstrated at the FSR collaborators meeting in June with much more to come at the FSR FIF in January 2017. The reason is due to the huge implications on the financial services sector.
There is OpenAI, a non-profit with 1 billion USD in funding, opening their OpenAI Gym to the world to experiment with machine learning and supporting open source (free) tools with virtual environments for testing.
Of particular interest to the financial sector are enterprise capable machine learning solutions and easy to use tools from Google, Microsoft, IBM, Amazon, and other major players. In addition, a proliferation of hardware solutions from NVIDIA, Movidius, IBM, Qualcomm, Samsung, and Chinese startup Horizon Robotics building chips.
The rise of digital assistants and chatbots (as seen by the movie “Her”) is here with Microsoft Cortana and Tay, XioIce in China, Amazon Echo and Alexa, Facebook M, Google Now/Home/Allo, Apple Siri. There are advanced robotics such as with Jia Jia from China, Hanson’s Sophia or Boston Dynamics’ walking robots, all possible due to AI and machine learning. Even a recent announcement this year indicating the specialized skills of data scientists can be commoditized via new tools.
Stay tuned for my next blog post where I dissect AI even further.