10. Conclusion & Prospects

For centuries, economists, political scientists, politicians and other professionals have tried to understand what variables lead to economic growth and whether governments should intervene in the market to promote this growth or not.
10. Conclusion & Prospects
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Contributors (1)
Published
Dec 18, 2018

Conclusion & Prospects


For centuries, economists, political scientists, politicians and other professionals have tried to understand what variables lead to economic growth and whether governments should intervene in the market to promote this growth or not.


Although there is no universally accepted conclusion about these topics, the neoclassic theoretical model and explanations have become one of the most accepted and used theory to study them.

According with this theory, Economic Growth is a product of a set of variables such as Labor, Capital, Land, Economic Efficiency, Wage, among others. Thus, the variation in a country’s economic output can be theoretically predicted by applying mathematical models such as the Cobb-Douglas1 function. As the phenomena studied by this theory are neither static nor constant, theorists and scholars have to keep adapting the neoclassical model so it could predict the reality in a more accurate way. As consequence, the neoclassical model has evolved and other variables such as technological advances/new technologies started to be considered too in order to understand what influences Economic Growth and how it happens.

In this context, this research has focused mainly on understanding if and how new digital technologies applied to financial and banking activities can lead to an inclusive economic growth. In other words, this dissertation aimed to examine whether there was a causal relation between the usage of new financial technologies and inclusive economic growth even though knowing that that other variables – capital, land, labor, and economic efficiency – also affect a country’s economic growth and its inclusiveness.

In order to accomplish this goal, this dissertation was guided by the following research questions:

i. “Do new financial technologies boost Inclusive Economic Growth in developing countries?” and

ii. “What are the major factors affecting the adoption of these new financial technologies?”

During almost one year, data were collected, interviews were done2 and a deep analysis of the FinTech sectors in Brazil and in China was conducted. Two specific cases of companies innovating in the online payment sector – Alipay in China and PagSeguro in Brazil – were studied. The comparison between the emergence, application, impacts and regulations of the application and usage of new financial technologies in these countries contributed to the following conclusions:

i. There was an expansion in the number of merchants included in the formal economy or accessing financial services for the first time due to the emergence and usage of new financial technologies provided by the companies analyzed;

ii. A reduction of transaction costs and payment fees was observed after these companies integrated these new digital tools and other technologies to their financial services and products’ offers;

iii. The dominance and influence of big traditional banks and financial institutions have diminished due to the emergence of FinTech companies and their new customer and merchant-tailored solutions;

iv. There was a democratization of the access to means of payment such as Peer-to-Peer transactions, card-based transactions and online payment platforms all over these countries;

v. The government financial regulations played a decisive role on how the new financial technologies were developed, applied by companies and used by costumers. These regulations also affected indirectly the impacts of these new financial technologies and business models on Inclusive Economic Growth; and

vi. The decision-making process involving the creation of these regulations was not impartial. Indeed, different interest groups pressured government officials and policy-makers to legislate in favor of their interests and goals. In the Brazilian case, the most influential group was composed by representatives of the traditional banking system and financial institutions (pro-status quo/ pro-traditional finance). In the Chinese case, however, Internet and technology-related companies were able to influence the central and local governments to establish financial regulations supporting the development and application of innovations to the financial sector (pro-innovation).

Additionally, it is possible to affirm that new financial technologies can certainly work as a tool to boost Inclusive Economic Growth in developing countries. However, there are other independent variables that might affect a country’s economic growth and economic inclusiveness in a more determinant and impacting way. For instance, it was noticed that government regulations and the interest groups pressuring policy-makers are two variables that have shown especial ability to influence how new technologies and innovative business models are applied to the financial field and, therefore, can be considered indirect independent variables affecting a country’s inclusive economic growth.

Unfortunately, it was not possible to determine quantitatively how these two indirect independent variables affect this research’s dependent variable. Moreover, assessing mathematically how new technologies applied to the financial sector affected inclusive economic growth was not possible either. However, it is expected that more studies about this topic will be conducted in the future either by the author or by other scholars and researchers.

Besides investigating about the potential causal relation between Inclusive Economic Growth and the independent variables observed in this dissertation, there are still other new financial technologies-related topics that were not addressed here due to time and research constraints. For instance, some interesting topics that could not be discussed in this thesis are the following: “how new financial technologies affect the Brazilian and the Chinese economic productions and international trades”, “how new financial technologies such as cryptocurrencies affect a country’s monetary power and its monetary regulations and decisions”, “how Brazil and China’s governments and central banks are dealing with the emergence of cryptocurrencies and the usage of blockchain technologies applied to financial activities”, “how new financial technologies can be used in criminal activities and how the governments should prevent cybercrimes and frauds associated to the usage of new digital tools in financial activities”, “how personal information, data and privacy can be violated by companies using big data collected via new financial apps, platforms and tools”, “how privacy and information can be protected and, still, allow companies to use big data and other information from their costumers in an efficient and legal way”, “what risks the development and usage of new financial technologies can bring to a country’s economy and society”, among others. It is expected that these important topics will be discussed in the future either by the author or by other scholars and experts.

Finally, it is hoped that the present work contributes with the development of better public policies and regulations towards the financial field, in special, towards the FinTech sector. In addition, it is also desired that the case studies, the analysis and the conclusions drawn here can help policy-makers, entrepreneurs, scholars and other professionals to understand better the FinTech niche emerging in Brazil and in China. Certainly, more research and studies about the impacts of financial innovation and their impact on inclusive economic growth must be developed in order to better asses these innovations’ impacts in a country’s economic growth and economic inclusiveness.


Go to next: 11. Apendix A – D

Back to previous: 9. The FinTech sector in China and Brazil: an analysis of government’s regulations and their impact on the usage of new financial technologies


  1. 1.

    Cobb-Douglas function: 𝑓 𝐾, 𝐿, 𝑡 = 𝐴 𝑡 𝐾!(!)𝐿!!! ! , 𝐴 𝑡 > 0, 0 < 𝛼 < 1 , where K stands for capital stock, L means labor forces in terms of physical units, t is time period A(t) represents efficiency of labor. This function, for instance, uses the aggregate production function as one of its basis: 𝑌 = 𝑓(𝐾, 𝐿, 𝑡) , where Y is the maximum output produced by capital K and labor L in year t.

  2. 2.

    More than 30 professionals were interviewed by the author. The suggested questions used to conduct each interview can be found in Appendix D. All the interviews were done in a confidential way, therefore, no name was revealed and no direct quotation was written.

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