Ant Group: Growth, Privacy, and a Climate of Innovation
Why everyone needs to care about the Ant Group and what it means for the future!
With a pending IPO set for November 5, Ant Group is expected to raise $34.5 Billion USD, which would make it the largest IPO of all time irrespective of geography. This would put the Ant Group's valuation at over $300 Billion USD, higher than that of some leading US financial institutions such as Goldman Sachs and Wells Fargo. Such a figure is sure to put Ant at the forefront of business news for some time and pique the curiosity of many casual observers.
Beyond the exorbitant sums of capital, anyone with the mildest interest in innovation needs to care. Lots can be learned from Ant’s rapid growth, and it might perhaps inform us of the realities that lay ahead for all of us.
What is the Ant Group?
Ant Group is a subsidiary of Chinese Internet giant Alibaba Group. It was initially spun out as Alipay in 2004, which was the fintech payment processing arm of Alibaba, and payment processing is still the primary service offered by the Ant Group. Alipay enables individuals and businesses to send and receive payments online, quickly & securely. In fact, Alipay is the largest mobile and online payment processing platform in the world, servicing 1.3 billion active users and 80 million merchants. It’s estimated that Alipay processes over $17 trillion USD annually.
However, the success of its Alipay platform is only the tip of the proverbial iceberg for the Ant Group. Ant Group leverages very rich data from Alipay to power a remarkable number of businesses- ranging from health insurance, mutual funds, money market funds, credit rating, consumer lending, online gaming, wealth management, and more.
The already impressive range of businesses and active users is made vastly more impressive by the fact that the entire operation is powered by just 16,660 employees. To put this in context, the Bank of America employs over 200,000 people to serve roughly 70 million customers, with a product offering that is far more limited than that of Ant Group. In large part, this can be put down to the difference in operating model among incumbent institutions and the companies of the future.
A tech enabled shift in operating models
In a traditional business operating model size is a double-edged sword. It allows a business to deliver more value at a lower price as it grows. However, the advantages of scale are limited by the increasing capital and logistics costs required to deliver products and services. Thus, ultimately complexity and size become a hindrance in traditional financial organizations like banks.
Nowadays, AI's influence is becoming more pervasive, defining a new age for business and society alike. Particularly as it relates to the digitization of operating models. Perfect AI is not strictly necessary to bring about large-scale change in an organization/institution. Imperfect so-called weak AI is often enough to prioritize content on a social network, make a perfect cappuccino, set optimal pricing, or even to create new art in the forms of celebrated geniuses.
Taken in this light, the Ant Group provides perhaps the quintessential example of a well-executed digital operating model's value capture capabilities. Ant Group’s success lies in its ability to leverage data to learn about its users’ needs, which is then consolidated in an integrated platform that uses AI to automate functions like application processing, credit scoring, fraud detection, and loan qualification.
Unlike traditional institutions, the Ant Group has been built on a digital core. Meaning, it effectively has no employees that work on/are responsible for the core operating activities of its businesses. There is no actual human manager that has to approve a loan, no actual human financial advisor advising you on a time horizon for a foray into a money market fund, and no human investment team making the final analysis of a bond purchase. Thus, in the digitized operating model that leverages AI to automate a substantial part of tasks and manage complexity, operating costs do not increase at the same level as the scale of service. Without such traditional operating constraints, the Ant Group has been able to achieve unprecedented growth and compete in novel ways.
AI is driving the explosive growth of leading companies across sectors; notable examples include but are not limited to Facebook, Tencent, Amazon, Alibaba, Google, Ocado, Zebra Medical Vision, and (of course, the main topic of this post) Ant Group. Even in industries that are considered to be capital intensive, AI is allowing for increased automation, which decreases operating costs. A particularly poignant example would be Uber, which can broadly be considered one of the world's largest ‘taxi’ companies. Incidentally, Uber owns almost no vehicles and employs virtually no drivers.
(Although, in the case of Uber, this is likely to change in the not too distant future with the rise of autonomous vehicles, whereby Uber will own/operate its own fleet but will deliver the key part of its service without human involvement.)
Therefore, it is apparent that the right technology paired with a digital/tech-first operating model allows firms to digitize and drive rapid scale with significantly fewer resources. The ascension of such models is also exciting in terms of generating increased economic growth and potential prosperity. A figure that illustrates this point brilliantly is that in 1990 the three largest companies in Detroit employed 1.2 million workers and had a combined market capitalization of $36 billion (coincidently also smaller than that of Ant Groups’ IPO alone), whereas, in 2014, the three largest companies in Silicon Valley employed a mere 137,000 workers but enjoyed a collective $1.09 trillion market capitalization. Even inflation-adjusted the wealth creation is simply astonishing to behold.
What the future holds
The pending Ant Group IPO means that digital disruption and large-scale automation are no longer a theoretical matter to be discussed or mentally masturbated over. It is here. The Ant Group has only existed since 2014, meaning it has taken 6 years to eclipse most of the world's largest financial institutions. Such is the power of a well funded and executed digital model to scale and grow.
When AI/digital-first firms clash against more traditional organizations, competitive advantages are increasingly distinguished by the capacity to form and control digital networks. As the Ant Group aptly demonstrates, success is largely predicated on connecting different businesses/services by aggregating the data that flows through them and applying algorithms to maximize value across service lines. In this way, Ant has traditional network effects and AI-driven learning curves reinforcing each other. This multiplies its impact, thereby turning Ant into what can be considered a ‘hub’ firm; by compiling data through various network connections (and businesses) and applying AI to heighten competitive advantages across industries.
Traditionally, large corporations have relied on greater focus and specialization to optimize their operations. This resulted in the siloing of various business units that, in a way, disconnected them from each other, only loosely being held together by the nucleus. When each silo of a firm develops its own processes and processes its own data individually, internal development is fragmented. It becomes highly challenging to build connections across silos or broader ecosystems. In no way does this allow them to compete with the Ant Group or other digital-first companies such as Facebook or Amazon.
Therefore, what is needed for legacy companies is first to rethink and rearrange the structure of their organizations. Absent such a revamp of their organizational structure, introducing the most sophisticated AI available won’t be conducive to competing with AI-first companies without a structure that will allow the company to make the most of their AI capabilities. Data feeds data, which feeds data, which drives impact and delivers results.
Broader implications
The pace of disruption set by digital operating models brings discussions around growing inequality and unemployment into the mainstream. The related trend, unfortunately, appears to be further exacerbating these issues. A consensus doesn’t exist among economists on what the longer-term effects are going to be on the employment market. Some believe that in the long run, employment will be gained as new jobs/roles/professions are created, while others argue that far fewer people will be employed as the jobs that are automated away will not be replaced. Although the longer-term future of the employment market is hazy, there seems to be a pretty wide consensus among economists and other experts that there will be much wider spread under- and unemployment as a result of automation in the short to medium terms. Particularly, with the success of the Ant Group (and other digital tech companies) is proving that indeed lots can be done with relatively little.
Unfortunately, legislators do not have a strong recent history of being prudent when responding to innovation, nor have they been particularly prudent in forethought to prepare for future innovations. However, EU MP Mady Delvaux can be seen as a rare trailblazer for her role in tabling a motion to the European Commission in 2017, calling on the Commission to regulate the ‘rise of robots.’ Her motion included an ethical framework for the development, deployment, and the establishment of liability for the actions of robots/AI, including autonomous vehicles. However, the European Parliament rejected the element of the proposal calling for the imposition of a so-called ‘automation tax’ aimed at financing the retraining of workers displaced by automation.
On the bright side, since Delvaux’s famous proposal, there has been some traction globally for the idea of legislatures to prepare for the impending wave of automation. The 2020 U.S. Presidential campaign of Andrew Yang perhaps provided the most visibility on the issue of automation, whereby a centre-piece of Yang’s campaign was to introduce a form of VAT to finance a form of Universal Basic Income that is meant to offset the economic costs that would be felt as a result of a rise in unemployment due to mass automation.
Unfortunately, since Yang didn’t receive his party’s nomination, it doesn’t seem as if either the Biden or Trump campaign currently squaring off for the White House has adopted Yang’s concerns about mitigating the effects of possible mass automation. Moreover, it doesn’t seem as if any global jurisdiction has put serious thought into approaching the issue of taxing algorithms and other technologies that automate work away from humans.
A large part of the political fear that paralyzes jurisdictions' abilities to tax technologies that automate jobs away from humans (to support those that actually do lose their jobs) stems from the fear that doing so would curtail innovation. Jurisdictions tend to compete on taxes to increase the attractiveness of their jurisdictions to entrepreneurs and corporations. Understandably, no jurisdiction wants to miss out on the possibility of benefiting from having the next Ant Group emerge or establish themselves in their country. However, legislators need to think deeply and coordinate amongst each other to find ways to create optimal policy solutions that do not discourage innovation and create a financial safety net for those displaced by automation, and that does not favour capital > labour or vice versa.
Although in a global society where the international order is shifting more inwards thanks to a rise in populism, a trend that has been particularly emboldened by the global Covid-19 pandemic (including the lack of a coordinated global response despite international bodies meant to facilitate such), it is difficult to be optimistic about such a widespread global response.
A uniquely Chinese model of innovation
Many jurisdictions would like to believe that a tax policy or some other incentives would have meant that a unicorn akin to the Ant Group could have sprouted in their market. Such thought is naive and ignores the perfect storm that China creates to foster such a climate of innovation. In fact, the Ant Group's success and growth must largely be credited to the climate that exists in China and other similar emerging markets.
“If data is the new oil, then China is the new Saudi Arabia.” — Kai-Fu Lee
In particular, China’s history of having a lax attitude towards personal data protection and privacy has made it a hotbed of AI research and start-ups. The level and type of data that Ant Group was able to acquire in China about its customers is simply not possible in many western jurisdictions, both in terms of quality and quantity. Recently, this has resulted in a trend of top AI researchers/talent leaving companies and countries to work in China. According to industry giant Kai-Fu Lee, training algorithms is a lot more about brute force than elegance or sheer brilliance. This plays well into China's hands, who has vastly superior numbers of engineers (despite what some may argue is a lower quality engineer compared to other global geographies). China also has far fewer intellectual property restrictions compared to most developed western nations, which means that there are fewer barriers to vertical integration in supply chains. This culminates in Chinese start-up culture being typically much more aggressive than its western counterparts. Finally, it’s important to also iterate on the importance that the Chinese government places on being a leader in AI. The result of this has been nearly unparalleled funding opportunities for research and start-ups in AI. Particularly since China’s leadership believes that being at the forefront of AI is critical to the future of China’s economic and military power.
Therefore, if at first the eye-popping figure that the IPO raised piqued someone’s interest in what the Ant Group is/does, hopefully, they came to realize that the importance of the IPO is so, so much more. It signifies the confirmation of the advent of a new era of business and society that is to be dominated by digitization and automation. This should also reaffirm that debates surrounding trade-offs in privacy, taxation, and social safety networks should be more and more at the forefront of the public consciousness. Finally, It also imparts lessons about differing commercial climates in various parts of the world (notably in this case, China), which creates the perfect ecosystem for a company such as the Ant Group to thrive and conquer.
