=Paper=
{{Paper
|id=Vol-2917/paper47
|storemode=property
|title=Neurogenetic Tools for Fintech
|pdfUrl=https://ceur-ws.org/Vol-2917/paper47.pdf
|volume=Vol-2917
|authors=Sergey Rippa,Anatoliy Sachenko,Maria Rippa,Oksana Chereshnyuk,Oleg Sachenko,Taras Lendyuk
|dblpUrl=https://dblp.org/rec/conf/momlet/RippaSRCSL21
}}
==Neurogenetic Tools for Fintech==
https://ceur-ws.org/Vol-2917/paper47.pdf
Neurogenetic Tools for Fintech
Sergey Rippa 1, Anatoliy Sachenko 2, Maria Rippa 3, Oksana Chereshnyuk 2, Oleg Sachenko 2
and Taras Lendyuk 2
1
Kyiv National University of Economics named after Vadym Hetman, 54/1, Perenohy ave, Kyyiv, 03057, Ukraine
2
West Ukrainian National University, 11, Lvivsta str., Ternopil, 46000, Ukraine
3
University of the State Fiscal Service of Ukraine, 31, Universytetska str., Irpin, Kyyiv region, 08205, Ukraine
Abstract
The main subject of the article is the analysis of the problems of development and
implementation of Fintech technologies in the context of ideology and innovation DeFi
(Decentralized Finance), which are caused by accelerating digital economy growth under the
influence of blockchain technologies. (AI), incl. neurogenetic instruments. The specifics of the
retrospective of the epochs of industrial evolution are described together with the stages of
development of financial technologies based on the development of the so-called Fintech for
Sustainable Development (FT4SD) drivers. The instrumental basis of FT4SD in the form of a
triad of blockchain, AI and IoT, which create a synergetic effect of "decentralized finance",
generating, in fact, unlimited investment resources for technological innovation of the digital
economy within the processes of sustainable development. The representation of FT4SD
drivers in the form of a double helix symbolizes the introduction of neurogenetic tools for the
implementation of blockchain and IoT. In the presence of a crisis economic situation in the
world in general and in Ukraine in particular, a positive result of supporting "decentralized
finance" is shown, which with the use of neurogenetic tools for Fintech are able to ensure
optimal decision-making and stable growth of the digital economy.
Keywords 1
neurogenetics, neuro-models, fintech, sustainable development, investment resources,
decentralized finance, blockchain, AI, IoT.
1. Introduction
The impact of scientific-technical progress on the development of the modern economy today
confirms that in the process of growing climate, environmental and social challenges, the requirements
of reliability and stability of global, regional and national financial systems in the long run can be met
only by harmonizing them with sustainable development [2]. The financial system consists of
institutional units and markets that work together to mobilize financial resources for investment and
provide them not so much to finance business as to reorient to new Fintech sectors. The role of financial
institutions within such a system is mainly an intermediate link between those who provide funds and
those who need them, which usually entails the need to transform and manage the risks of the entire
socio-economic system and, above all, its human capital. and innovative resources.
The formation of the category of “green finance”, the growth of the renewable energy share and the
relevant financial infrastructure requires the search for new approaches and new tools for financial
decision-making. And such tools have appeared only recently, but have already attracted the attention
and commitment of many experts and analysts. These tools are neuromodels and genetic algorithms
MoMLeT+DS 2021: 3rd International Workshop on Modern Machine Learning Technologies and Data Science, June 5, 2021, Lviv-Shatsk,
Ukraine
EMAIL: rippa_serg@ukr.net (S. Rippa); as@wunu.edu.ua (A. Sachenko); rippa_mary@ukr.net (M. Rippa); oksana.duda@gmail.com
(O. Chereshnyuk); olsachenko231@gmail.com (O. Sachenko); tl@wunu.edu.ua (T. Lendyuk)
ORCID: 0000-0003-0429-6112 (S. Rippa); 0000-0002-0907-3682 (A. Sachenko); 0000-0003-2781-2642 (M. Rippa); 0000-0001-5067-3463
(O. Chereshnyuk); 0000-0001-9337-8341 (O. Sachenko); 0000-0001-9484-8333 (T. Lendyuk)
©️ 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
that are an important part of the theory of artificial intelligence and are increasingly being implemented
in the practice of financial analysis, forecasting and decision making.
The role of international financial institutions and banking institutions in modern conditions has
changed. Although they are active players in risk assessment, obtaining loans and confirming the
issuance of shares and debts, it is necessary to note the formation and spread of a new financial sector,
which forms the modern digital economy, legalized as virtual assets and is a crypto-economy (Fig. 1-
2). Fig. 1 shows the number of cryptocurrencies (10283), cryptocurrency exchange (383) and the
dominance of BTC together with ETH (over 60%) in the upper row of the coinmarketcap.com window
show overactive positive dynamics. For comparison, Fig. 2 shows in 2013, the beginning of June – only
14 cryptocurrencies, 2015, the beginning of June – already 651 cryptocurrencies.
Figure 1: Growth of crypto-economy [14]
Figure 2: Comparative data on the growth of the crypto market for 2013 and 2015 [2015]
In this context, short- and medium-term banking instruments no longer ensure the preservation and
mobilization of long-term assets for investors. Therefore, capital markets increasingly being
transformed from slow banking platforms on the Internet of instant Fintech transformations for digital
finance. The Bitcoin project, which has been predicted to collapse for more than 10 years in a row, is
confidently gaining momentum. And it is no coincidence that the same publication of Satoshi
Nakamoto, from which the crypto-economy began, literally meant – “bitcoin as an electronic peer-to-
peer cash system” [12]. The affinity of network concepts for neuroscience and crypto-economy, the
common basis of cryptology and the blockchain as a distributed database of Internet registers create a
single platform for neural networks and genetic algorithms as decision-making tools in digital finance.
2. Related work
Statistics and dynamics of the modern financial space show steady growth, where Fintech
instruments work to mobilize sources of long-term investment and as a means of transferring monetary
policy to the real economy, which also depends on the efficient operation of the traditional financial
system, i.e. banks, capital markets and institutional capital distribution systems. Today, Fintech
represents the sector of technology startups, which replace traditional financial market participants with
their products, in most cases – banking and insurance institutions, by offering a wide range of consumers
alternative solutions without the participation of such intermediaries and in parallel with reducing
transaction costs. In this context, we can distinguish 4 epochs of development of Fintech industry from
1.0 to 3.5, which cover a long period of financial development of more than 150 years and according to
the authors [1] represent Fintech from the primary telegraph to modern digital and virtual financial
technologies (Fig. 3). The use of neuromodel tools and genetic algorithms [19-22] for Fintech decision-
making is also widespread.
Figure 3: General chronology of Fintech development
In the last period of Fintech 3.0-3.5, which corresponds to the activation and spread of crypto-
economy, the aggressive promotion of neurogenetic tools in the practice of supporting Fintech solutions
has just begun. At the last stage Fintech 3.0-3.5 begins the stages of intensive research and practical
implementation of neurogenetic tools in crypto-economics. Figure 3 highlights the epochs of Fintech
3.0 and 3.5 for countries with financial markets at different stages of development. Moreover,
sometimes emerging financial markets are significantly ahead of traditional markets of developed
countries in the implementation of Fintech innovations [16]. In these conditions, the Central Banks of
developed countries have to catch up and adapt to changing conditions and the latest financial products.
This situation is typical today, for example, of the crypto market and blockchain technologies, when
central regulators (central banks) plan to introduce national cryptocurrencies, where neurogenetic
methods are a significant instrumental support.
Analysis of the publications of leading financial scientists and experts in the field of digitalization
[4-6, 11, 13, 17] The world community today is at the stage of the fourth or even the beginning of the
fifth industrial revolution, which began in the XXI century due to the widespread use of achievements
in the field digital and information technologies, which originated during the previous revolution,
namely – the Internet, 3D printing, bio- and nanotechnology. And the achievements of artificial
intelligence, neurogenetics and genetic engineering have played a leading role in the introduction for
the development of the economy and the production of such previously unknown technologies as
blockchain (Table 1) in the field of IT and electronic payment systems.
Table 1
Generalized characteristics of world industrial revolutions
Industrial Key technological The main Description
Revolution, achievements sources of
period (years, energy
approx.)
The first (1760- Steam engine Coal Steam and hydropower are
1900) used for mechanization of
production
The second Internal combustion engine Oil, electricity Mass production is made
(1900-1970) possible by the use of
"Technological electricity
revolution"
The Third (1970- Internet, IoT, computers and Atomic energy, Production automation is
2000) "Digital robots, 3D printing, genetic natural gas carried out with the help of
Revolution" engineering, artificial electronics and information
intelligence, data analysis, technology
virtual and mixed reality
Fourth (2000-…) Fintech (green finance), IoT Green energy Almost all production is
"Industry 4.0" globalization, blockchain, automated, it begins to use
industrial nano-, artificial intelligence and
biotechnology, data analysis, human
neurogenetics, genetic intervention is completely or
engineering and 3D printing almost absent; information
is stored on the blockchain
Fifth (... ? ...) Industrial IoT, collaborative Personalized products are
work ("cobots"), industrial manufactured in accordance
neurogenetics with the requirements and
needs of consumers;
collaborative work and
globalization of crypto-
economy are widely used
In the last two periods of the industrial revolution, which continue today, the connection between
financial technology and sustainable development in a new area, which is commonly called "Fintech
for Sustainable Development" (FT4SD). Highlighted in italics in table 1, the tools of neurogenetics is
becoming the dominant component of innovative technologies IoT, robotics and Fintech [18].
3. Methods and Materials
It should be stressed that even in the publications and developments of the 3rd period of the industrial
revolution [3] laid the scientific foundations of Fintech concepts through the definition of three types
of costs in the economy: search costs, coordination and contracting, which assumes that business
whether the firm expands until the cost of the transaction within the firm exceeds the cost of the
transaction outside it. This statement mainly concerns information-related costs and the assumption that
Fintech can destroy redundant or simplify many functions of the financial system and the real economy,
significantly reducing the cost of search, coordination and through reducing transaction costs. In
subsequent publications in Nature, in January 2013, scientists demonstrated the ability of DNA to
encode information to store digital data [10]. The use of the DNA double helix analogy to describe the
main attributes of the FT4SD process is becoming a trend in many scientific publications, as the idea
of coding, processing and storing information on the basis of genetic engineering in Fintech is spread
and fixed theoretically, mathematically and instrumentally [3]. The neurogenetic concept acquires for
Fintech a dominant status as an integration of neural network ideologies, genetic algorithms and the
blockchain platform as a technological basis for the entire crypto-economy.
Active research on neurogenetic instruments began in the middle of the last century. Hidalgo's
research [7] examines the relationship between information and knowledge, their development,
dissemination, use and implementation, and how this determines the complexity of the economy around
the world and, consequently, their ability to develop over time. The author notes that most DNA
molecules consist of two helix strands that form a double helix, and consist of simpler units, the so-
called bases, which are combined, in turn, in predetermined ways of gene generation and encode all life
forms on land. In this context, the terms "DNA molecules", "bases" and "genes" are used conventionally
to denote the components of the DNA helix and the possibility of their integration and interaction.
Under the possibilities of integration and interaction of DNA elements, we understand the use of tools
of neurogenetic models and methods. Awareness of the fundamental attributes (or basics of DNA) of
Fintech and sustainable development as factors of destruction and influence, the use of the language
"double helix FT4SD" is proposed (Fig. 4). These two concepts can also be "connected" in predefined
ways to create new sustainable business models. It helps to explore and influence change and provide
a common language to discuss both the positive and negative effects of FT4SD – effectively ensuring
the use of metalanguage for communication between the financial, industrial and technological spheres,
taking into account the priority and importance of social and humanitarian components. The language
platform of both theoretical and practical developments of neurogenetic instruments is the universal
language basis – XML and a number of its derived dialects, including languages of knowledge bases,
ontologies, etc.
Figure 4: FT4SD double DNA helix in combination with neurogenetic instruments
In Fig. 5 an example of using a neuromodel to forecast the market of communication services (based
on the analytical platform Loginom) is given. In the process of adjusting the input parameters,
normalization is performed by the method of linear transformation by constructing a scale of values in
the interval [0,1]. The normalization algorithms are based on the use of Gray codes.
Figure 5: Example of using a traditional neuromodel
Fig. 6 presents the result of calculating forecast data for one of the forecast periods. Before starting
the neuromodel, a number of preparatory procedures are performed, which provide preliminary
preparation of data for further processing by the neuromodel – a partial processing to eliminate
anomalies and other unwanted data deviations, sorting and a sliding window. The last two procedures
in the scenario provide the calculation of forecast data – the neural network for one period, and then the
ARIMAX procedure – for 2 more periods.
Figure 6: Loginom configuration platform of Loginom analytical platform
Characteristics and learning parameters are set in the following window of setting the neuromodel
(Fig. 7): these are the parameters of splitting the input data into training and test sets, determining the
methods of splitting, validation and sampling. The main types of partitioning – random (Random) and
sequential (Sequence), as validation methods are used – K-fold cross validation and the Monte Carlo
method.
Figure 7: Neural network learning process settings
The next stages of instrumental configuration of the neural network are the definition of the
architecture (Fig. 8) and the establishment of parameters for automatic selection of the configuration
architecture of the neural network (Fig. 9).
Figure 8: Neural network configuration parameters
Parameters for determining the architecture of the neural network can be considered standard for
most software and platforms, they include three main groups: the first – the number of hidden layers
and the number of neurons in them, the second – learning parameters (restart, degree of relaxation and
continuation) and the third – stop criteria (minimum weight change threshold and maximum number of
epochs).
Figure 9: Neural network configuration selection options
Parameterization of automatic neural network configuration selection (Fig. 9) also includes three
groups of parameters: the first is a set of standard neural network parameters for automatic structure
setting, attenuation and starting parameter of a specific structure, the second is sampling parameters
and the third is hitchhiking parameters.
Figure 10: Neural network configuration selection options
Based on the analytical platform Loginom, it is possible to choose three classes of problems with
neural networks – classification, regression neural networks and self-organizing maps (SOM, Kohonen
maps), within which the process of data preparation and processing, parameterization and direct neural
network and neurogenetic calculations obtaining the resulting data. These can be forecast calculations,
clustering operations, classification or presentation of multidimensional data in the process of
preparation and decision-making.
The concept of Fintech today as a phenomenon, along with the positive attitude of the world
community, is also of concern, in particular from representatives of regulatory bodies. The reason for
this is not the financial technologies themselves, but the speed of their development and the integrity of
the intentions of those who use them. Thus, the era of modern society is marked by a new digital
economy, which, according to Professor of Fintech and blockchain D. Kuo Chuen Lee (Singapore),
provides for the presence of four "D" [1]:
• Digitalization;
• Disintermediation (reduction of the use of intermediaries);
• Democratization and
• Decentralization.
The combination of these four factors has given society, in addition to innovative forms of doing
business (digital nomadism, Digital Nomadism) and everyday digital life (social networks, Social
Networks) also a synergistic effect – the fifth industrial revolution is expected to bring back the human
factor (Human Touch). in production in a broad sense [13]. According to some forecasts, in the future
the industry will again feel the urgent need for human intervention due to the influence of behavioral
factors (e.g., the precedent of irrational financial decisions of individuals, groups and communities),
because the driver of any change is not new technology, but the person behind them, her personality.
While some professions will disappear due to primitive robotization, new ones will appear – those that
require a suitably highly skilled workforce [9] with an emphasis on intelligence and decision-making.
4. Conclusion
In the presented study, the basics of DNA of financial technologies and sustainable development (F
are connected using so-called "DNA connectors", which are integrated into the "FT4SD reducer" and,
if necessary, can be combined using different methods. This combination of "FT4SD reducer" contains
three main components - Internet of Things, blockchain and Artificial Intelligence), which are able to
provide a large-scale sustainable development program for the modern world community within the
crypto-economy.
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