“AI deployment will add $15.7 trillion to global GDP by 2030.”
– Kai-Fu Lee, AI Superpowers: China, Silicon Valley, and the New World Order
While 2030 is still over a decade away, it’s evident that Artificial Intelligence (AI) and Machine Learning (AL) will continue to play a major role in FinTech as well as the financial services industry in 2019. Given that AI and ML are being extensively used and enjoy high acceptance across industries, we wanted to take a look at how the adoption of AI and ML by FinTechs has been up until now. We also set out to understand who has been more aggressive and are at the forefront of the adoption and/or development of AI/ML technologies for their businesses.
For this article, we studied a list of ~350 unicorns globally, taking a close look at two distinct categories of AI and ML unicorns: 1. FinTechs that have been heavily leveraging AI and ML (through in-house development, partnerships and/or deals) to solve their problems.
2. Core AI and ML companies catering to FinServs.
To begin with, we took all the 50 FinTech unicorns and put them through a filter to sort out the ones taking significant advantage of AI and ML tech. We then arrived at a list of 39 FinTechs. Analyzing those, we found their combined valuation and discovered that FinTech unicorns worth ~$110.18 billion are heavily leveraging AI and ML technologies to solve their problems.
Similarly, we took a list of ~350 unicorns globally, and after carefully sifting through them to understand how many of them have a core AI and ML focus, we arrived at a list of 32+ unicorns with a core focus on AI and ML. We put these further through our filter and found that 26 of these unicorns are core AI and ML companies catering to FinServs, and have a combined valuation of ~$66.04 billion.
We then divided the combined valuation of both sets separately by the number of companies in each category to arrive at the average valuation. Accordingly, we found that FinTechs leveraging AI and ML seem to have an average valuation of $2.82 billion, while that of core AI and ML companies catering to FinServ stands at $2.54 billion.
Based on this analysis, we can see that FinTechs heavily using AI & ML technologies to address and solve their problems as well as enhance their products & services, have a slightly higher valuation in comparison with their core AI and ML-focused counterparts that address the requirements of FinServs – this is reasonable, given a number of considerations including cost and time parameters when it comes to in-house development of AI and ML tech, as also the availability of trained talent equipped to keep up with dynamically changing technologies in the space.
Research further shows that over the years, there has been positive growth in the number of new AI and ML FinTech startups emerging in the market and increased VC funding as well. According to insights by ANZ, by 2021, global AI investments will reach $58 billion, of which $10 billion is projected to be invested by FinTech alone. It is evident that we cannot ignore the highly significant impact of AI and ML tech companies on the global FinTech landscape.
What’s more, the use of AI and ML in global banking is estimated to grow from a $41.1 billion business to $300 billion by 2030. Estimates further suggest that up until 2023, North America will remain the largest market for AI banking technology. However, by 2030, APAC is set to become a $98.6 billion market, in contrast to North America, estimated to reach $79 billion. In recent years, an increasing crop of AI unicorns have been coming from Asia.
According to Prakash Mallya, Managing Director, Sales & Marketing Group, Intel India, “We believe Artificial Intelligence (AI) will have a significant impact in India and globally in the coming years. About 90% of global data was created in the last couple of years, but only 1 to 3% of this data has been analyzed. The AI and analytics journey are just at the beginning, and there is immense opportunity to derive value from the rapidly increasing volume of data.”
AI and ML truly stand out as among the most era-defining technologies in financial services across a range of segments. Advanced technology, in conjunction with a growing abundance of data, has helped give rise to innovative business models with core AI and ML companies – many of them unicorns – catering to FinServs. Promising players around the globe now use AI and ML to solve some of the major problems for customers in the banking and financial services industry.
As we move forward, we can expect the lines separating AI, ML, and big data to blur, spurring on further development – this will also improve existing financial products and services. Speaking of which, with digital transformation plus customer experience as a high priority, many banks are now banking on AI and ML to deliver next-generation service to their customers. Some of the largest financial institutions are looking at FinTech partnerships, investments, and/or in-house development, to leverage the application potential of these technologies.
In an interview published by Microsoft in 2018, it was stated that “banks, financial institutions, and insurers should put all of their efforts and resources into AI and machine learning because it will provide their customers with more personalized recommendations, which is what people are used to.”
It goes on to state that “If you’re in the financial industry, AI should be on the very top of your priority list.” Moreover, it is indeed, increasingly being given priority. AI and ML have a vast range of use cases, right from bots, recommendation engines, and conversational interfaces, to real-time fraud detection, profiling, insights-based trading, and more. As we’ve written about in an earlier article on AI as a tool for transformation, all these use cases can be broadly categorized into four major categories: Front-Office (customer-focused), Back-Office (operation-focused), Regulatory Compliance, and Trading/Portfolio Management.
So, as we’ve seen, 39 out of 50 FinTech unicorns are focusing on AI and ML and creating value. We’ve also observed that 32+ unicorns overall are core AI and ML companies – this goes on to show the importance of AI and ML, and it is certain that this will bring a profound change in terms of how technology will help deliver better financial services, in the times ahead.