Can AI and FinTech Reverse Wealth And Income Inequality?

By Francesco Lapenta, professor and director of John Cabot University Institute of Future and Innovation Studies in Rome. With this project on FinTech, he is also a Mozilla fellow for DataEthics.eu

The world is facing an increasingly problematic gap in wealth accumulation by few, and increasing income inequality gap. FinTech and AI can be a solution, if done right. We see examples where FinTech creates access to basic financial services, credit and investments for those who never had access before. And also robot-advisers are promising. FinTech and AI can can play a big role in reversing the current financial markets from creating income inequality. But there are great risks of ‘winner-take-all’ effects.

ANALYSIS. To understand the increasingly problematic gap in wealth accumulation by few, and the increasing income inequality gap, we need to look at the evolution of global financial markets, and the economic and fiscal policies of national central banks and governments. Most critically, we have to analyze the implications of this wealthy minority often exclusive access to increasingly sophisticated financial services, and these financial services ever increasing technological dependencies and affordances.

It is rather complex to synthesize and describe the increasing wealth gap and income inequality problem that has characterized much of western societies and the world in the past two decades. Not least, because there are at least two apparently contradicting trends.
The past two decades have seen the increasing development and economic advancement of many emerging economic markets. In these markets, economic growth in the past two decades has often been in the double digits. In these markets many of the social and economic processes experienced last century by the strongest economies of the past have been taking place. Namely the dramatic development of an emerging middle class, and the average increase of this middle class income, wealth and spending. The social and economic growth of these emerging markets has been countered in the once dominant economies of the world by an unprecedented reversal in these very processes of wealth production, accumulation and redistribution.

Dominant economic markets of the past and their societies have for twenty years been characterized by an increasing slow down in wealth accumulation by the middle classes, and an increasing income inequality gap. One interpretation of these shifts is based on the critical analyses of the consequence and impact of globalization. According to this interpretation the very transfer of production processes and labour to emerging markets is consequence of both phenomena; economic growth in one developing area (led by a growing job market, exports and internal consumption growth), and stagnation, if not economic growth reversal in the other.
This basic, plausible, and at times politically convenient interpretation accuses (or credits) the globalization of markets and labour for this shift in trends. It also hides the complexities, and does not fully explain the other important underlying trend: the increasing gap in wealth distribution, and the growing income inequality within all said societies.

A recently published article by the Pew Research Center quotes:
“The wealth gap between upper-income and lower and middle-income families has grown wider this century. Upper-income families were the only income tier able to build on their wealth from 2001 to 2016, adding 33% at the median. On the other hand, middle-income families saw their median net worth shrink by 20% and lower-income families experienced a loss of 45%.”.

These data, referred to the U.S. market, hold true and similar for the European market (Stiftung and Stiftung 2017). One set of reasons often indicated for this market difference in wealth production and accumulation is often linked to the different sources of wealth of these socio economic groups. Lower and middle-income families are more, if not solely, dependent on labour generated income. If there is any form of wealth accumulation it is in the form of savings and home equity.

Upper-income families, derive a larger share of their wealth from financial market assets and investments (property, bonds, stocks and gold for eg.) and business equity. They also normally have a different knowledge of, and exclusive access to, financial institutions, professional fiscal advisors, and financial instruments and technologies used to manage their wealth.
An analysis by the IFM (International Monetary Fund) on “Globalization and Inequality” offers insight in the role that financial technologies have played in the creation of characteristic uneven processes of wealth accumulation, and income inequality of the past few decades. IFM states that although trade globalization is often accused to be the cause of this growing wealth and income inequality, the real causes of this transformation should be found in the parallel evolution of globalized financial markets and financial technologies.
The globalization of financial flows has been as rapid in the same period of time. “Total cross-border financial assets more than doubled as a share of output between 1990 and 2004. In the IMF analyses of available data however, whereas trade globalization has helped reduce global inequality, financial globalization—and foreign direct investment (FDI) in particular—have tended to increase economic inequalities in advanced and developing economies. The data indicate that the per capita incomes have risen across virtually all regions of the world for all segments of the population, including the poorest, but so has the economic divide between lower and middle-income families and the higher-income ones. In their analyses, contrary to common belief, trade globalization has helped reduce inequality rather than increase it—particularly for agricultural exports, especially in developing countries where agriculture still employs a large share of the workforce and the higher skills manufacturing jobs that followed.
The globalization of financial flows and the associated foreign direct investment, however, had mainly a negative effect on the distribution of income in advanced economies, in which the greater part of the population have been excluded from the advantages of this globalization of financial flows and participation in foreign direct investments.
And in the emerging economies in which large parts of the population did not have even the most basic access to banking or the most basic financial tools. Technology and Financial Technologies specifically, the report supports, have been one of the driving force and one of the main factors driving the recent increase in economic inequality.

New Financial Technologies Can Close The Gap

The conversation about the innovation processes that could be made to create a more inclusive financial system are ongoing as are the efforts by new fin-tech start-ups and projects. Many positive steps have been made by fin-tech to bank the world’s poor and drive the cost of remittance payments from overseas down.

One example always cited is that of M-Pesa and the similar IndiaStack mobile payments technologies that have helped to give millions of people in Africa and in India access to basic financial services, such as that of electronic payments and small loans. M-Pesa notoriously helped create a basic banking system in Africa where an enormous network of small agents have created the infrastructure for an efficient, economic and simple system of mobile payment that replaced traditional and more expensive banking services. Such systems have been hailed as the drivers of economic growth in Africa and in India and China and have moved forward the discussion about the steps that the financial system could take with fin-tech applications to improve and close the gap in access in the areas of payments, credit markets, savings, investment and insurance. The innovation in mobile payments has been vibrant worldwide and has created access to electronic payments to many small businesses activities that were normally excluded by more expensive and complicated electronic systems such as debit and credit cards.

A second crucial area is credit. Traditional credit systems have shown and still show worldwide crucial biases and distinctly favour the wealthy. Not only substantial groups of the world population are still excluded from credit systems and loans, but the traditional financial systems have displayed distinct biases that seem to remain in the current fin-tech evolutions. In several countries, there is evidence that innovations in fin-tech and big tech credit have served borrowers who are underserved by banks. But the costs of borrowing and the access to borrowing are still distinctly tilted. For instance, Pereira da Silva, Frost and Gambacortata (2019) using data on US mortgages, have found that African American and Hispanic borrowers are disproportionately less likely to gain from the introduction of machine learning in credit scoring models, and like many other studies have found that most algorithms still display distinct socio-economic biases.

A third crucial area is that of savings and investments.This is the most crucial area where, to date, wealthier households have earned distinctly higher returns on their wealth than less wealthy households. The entire financial investment system is tilted towards providing unique support and access to the wealthy. A number of fin-tech firms claim that their innovations are “democratising” investment, and giving small consumer access to new savings and investment products that they would not otherwise be able to use. This is also the crucial area in which A.I. based fin-tech innovations could change the balance of financial systems and offer access and opportunities in investments normally xxx to the wealthy.

thenounproject.com

The Robo-Advisors Show Great Promise
The most promising area of innovation is that of the so called robo-advisors. Robo-advisors are digital platforms comprising interactive and intelligent user assistance components (Maedche et al. 2016) that use information technology, machine learning and A.I. applications to guide customers through an automated (investment) advisory process (Sironi 2016; Ludden et al. 2015).

The first robo-advisor, Betterment, was launched in 2008. As Frankenfiel (2020) describes their initial purpose was to rebalance assets within target-date funds as a way for investors to manage passive, buy-and-hold investments through a simple online interface. The technology itself was nothing new. Human wealth managers, he continues, have been using automated portfolio allocation software since the early 2000s. But until 2008, they were the only ones who could buy the technology, so clients had to employ a financial advisor to benefit from the innovation.

The development of robo-advisors based on advanced machine learning and A.I. application seems to promise the most meaningful transformation in the financial system in decades. After a decade of development, robo-advisors are now capable of handling much more sophisticated tasks, such as tax-loss harvesting, investment selection, and retirement planning. The industry has experienced explosive growth as a result; client assets managed by robo-advisors hit $60 billion at year-end 2015 and have increased enormously since and are projected to reach $7 trillion worldwide by 2025.

Understanding financial markets and finance coupled with the exclusive access to financial institution and advisors has constituted the backbone of the increasing wealth gap in society in the past few decades. While not changing the need for financial literacy, or addressing the income inequality gap, the advancement and wide distribution of advisory financial services and investment tools to a broader range of individuals in society promises to have the same socially disruptive potential of other historic information technology.

Risks of Data Centralizaton
This evolution in the application of A.I. and machine learning in finance is coupled however by the same very high risks characteristic of other highly data centric economies and technologies. As Pereira da Silva (2020) analyzed, in many cases, digital markets may be characterised by network externalities and winner-takes-all effects. Especially those firms that can leverage their access to data, their large network of users and their breadth of activities may rapidly establish a dominant position. Mobile payments in China, for instance, are very concentrated, with two firms controlling 94% of the market. Data collection juggernauts companies could use their dominant data collection positions to enter and dominate this emerging financial space. Re-enacting the the strategy of using vast resources to purchase small or in time big or much bigger competitors, after-all it was Bill Gates, Microsoft founder whom notoriously said “We require banking, not the banks”. The risk of a data driven winner-takes-all economy requires foresight, and the same level of innovation and forward thinking in regulatory policies.

Extra Background: The Role of National Central Banks
These exclusive opportunities for wealth generation have been compounded and combined with the economic policies of central banks that in the past twenty years have exacerbated this gap and the uneven distribution of wealth and income. The role of governments and central banks in this process of wealth redistribution and accumulation cannot be understated. It is argued that the response to the financial crises of the past 20 years with different historically unprecedented rounds of “Quantitative Easing” have heavily contributed to strengthening this gap. QE, as it is known, saw the U.S. Federal Reserve, the ECB and other national central banks print trillions in different fiat currencies and buy trillions worth of government bonds, mortgage-backed securities and other financial assets and debts. In theory QE is supposed to put more cash into the financial system to encourage businesses and individuals’ landing, and spending. However, a known effect of QE has been that of boosting financial markets, stocks, and other asset prices, from equities to houses prices have boomed as an outcome of these interventions.

The problem is that most of the assets that got artificially boosted in value such as property, stocks, bonds and gold are owned by a minority of upper-income families. And the financial institutions and tools that manage such assets are rarely accessible to the greater majority of the lower or medium income families. “A 2012 Bank of England report said that its QE boosted asset prices and household wealth, but the impact was “heavily skewed,” because the top 5% of households held 40% of the assets”. These processes have been repeated several times in the past twenty years, trough different crises, and all signs indicate that Covid-19, yet another financial crises of unprecedented proportions in this century, will increase inequality even further. Governments are using unprecedented amounts of resources and accumulating debt to subsidise public and private labour social costs, and businesses are sold out or taking out loans to survive. This debt is once again for example being used to pay rent to those who own assets. And other financial assets, such as gold and stocks have once again increased in value repeating and sustaining again a now well know cycle of wealth transfer. 

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