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Autonomous Systems in Finance

Aggressive and conservative market estimates for autonomous systems and artificial intelligence in the Fintech market. Revenue pool for AI start ups is to reach 500 billion $ by 2030, exceeding 100 billion $ by 2025 in the aggressive growth estimate – US market. Source: Autonomous Next

Finance is, today, a business in the cyberspace. Autonomous Agents –AA- and Artificial Intelligence have already changed the landscape and will further change it in the next decade.

Kensho’s Artificial Intelligence Investment Analyses platform has been acquired by S&P for 550 million $, the largest price tag on an artificial intelligence engine. Both AA and AI are created an Augmented Finance where software based reasoning is taking the upper hand. Although unnoticed by the general public, the digital transformation in the financial arena is changing the landscape.

In the US there are, as of 2018, some 2.5 million people working in financial institutions (Banking, Investments, Insurance) and AA/AI is expected to have an impact in the range of a trillion $, 490 billion $ of which in the front office, 350 billion $ in the middle office and 200 billion $ in the back office. Personal consulting agents, that can take the shape of Alexa, are now starting revolutionizing the front office.

As shown in the figure, the foreseen revenue out of AA/AI (in the US) may be reaching (aggressive estimate) 500 billion $ signalling a shift from the money saved using AA/AI to companies providing fintech services through AA/AI (most of these companies are “new” companies). Notice that in the Finance area, the digital transformation is not acting on product, rather on services and the processes used in the “manufacturing” of these services. The shift in value also corresponds to a loss of jobs.

Although both Autonomous Agents and Artificial Intelligence are the technology building block of Augmented Finance, the artificial intelligence part takes the lion share since it is the one that is analysing data, evaluating risk and perspectives and eventually taking decisions. Autonomous Agents are more executors, both locally and across a network. This characteristics of Autonomous Agents to live and roam networks makes them applicable to a variety of context, becoming more a sort of commodity, hence limiting their market value. Besides, since they can be applied to a variety of context and they are network entities it is foreseen that the major market value is found in telecom application, particularly in the management of distributed resources. The global market value is estimated in 345 million $ in 2019 to grow to almost 3 billion in 2024.

European Neobanks landscape. Source: CB Insights

A further segment of interest is the one of Neobanks, banks that exist only in the cyberspace. They are quite widespread in Europe and are on the rise in other geo-markets. This is a rapidly growing market, with funding growth from 750 million $ in 2017 to 2.2. billion $ in 2019– see figure.

All banking system is adopting autonomous agents, data analytics and artificial intelligence. Chatbots are widely used. The old style brick and mortar banks are upgrading their services and streamlining their processes by embracing the digital transformation. Digital banks (not owning any brick and mortar location but backed by large financial institutions) have been around for a while and are leveraging on autonomous systems. The Neobanks are based on a new model, completely relying on mobile access. They have not been born through a digital transformation of an existing company, but are brand new digital companies. As of 2018 the number of clients was in the order of a few million in Europe, with Revolut topping the list with 1.5 million customers and 3.5 million in the US with a 1.58 billion $ in deposit (that’s nothing, representing the 0.014% of all deposit in US banks).

The Fintech transformation, as in several other areas hit by the Digital Transformation is not, per sé, creating new value, rather it is decreasing the overall market value. Fintech apps by disintermediating the front office have saved 5 billion $ to US consumers (that is a 5 billion $ decrease in the Fintech market).

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the Industry Advisory Board within the Future Directions Committee and co-chairs the Digital Reality Initiative. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.

One comment

  1. Based on the company’s own statement, the algorithm of the fintech robo-advisor EquoBot (using IBM’s super-computer Watson) is capable of processing over one million pieces of information a day. This includes earnings releases, economic data, consumer trends, industry developments, and headline news – all information that the average regulator takes in each day. EquoBot coverts this Big Data into Smart Data: predictive financial models on over 15,000 globally traded companies.

    There is a second philosophy for investors. Human- or robo-advisors analyze the charts of the stocks to see if their short- or long-term trends follow any potential lines or even break through such. This theory is based on mathematics, even if the causal-relation is questionable. On the other hand, as a group of individuals follow this theory and act accordingly, it works as a “self-fulfilling prophecy”.

    This approach also uses financial information to connect them via mathematical formulas, so there is no need to say that the robo-advisors are superior. Comparable to the mathematical-based astrology, the “black-box”-effect of the algorithm is no obstacle for human investors. On the contrary, it may foster the “myth of secret knowledge” as this philosophy also includes regular events as the “triple witching hour.”