Deployment of AI technologies in banking sector: comparison of russian and singaporean approaches
| Autor | Ella Gorian |
| Ocupação do Autor | Ph.D. in Jurisprudence, Associate Professor, School of Law |
| Páginas | 879-894 |
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DEPLOYMENT OF AI TECHNOLOGIES IN
BANKING SECTOR: COMPARISON OF RUSSIAN
AND SINGAPOREAN APPROACHES1
Ella Gorian
Ph.D. in Jurisprudence, Associate Professor, School of Law
Vladivostok State University of Economics and Service.
Summary: 1. Introduction. 2. Conclusions. 3. References.
1. INTRODUCTION
Artificial intelligence technologies (AI technologies) are gaining popularity in the
banking and financial sectors. Business Insider Intelligence analysts note that about 80%
of banking institutions with assets of more than $100 billion and just under half of banks
with assets of less than $100 billion are currently implementing projects using AI. The
results are expected to be impressive: the industry will generate significant savings of
$447 billion by the year 2022 with $416 billion in savings in the front office (conversa-
tional banking) and middle office (anti-fraud) only in the USA2.
In Russia the AI technologies are being used by the largest national bank - Sber-
bank of Russia: on the decisions of AI 100% of credit cards are issued, more than 90%
of consumer loans and over 50% of mortgage loans are approved, and since 2019 AI is
integrated into mobile application. The most discussed issues in Russian banking are the
technologies for launching a new financial product on the market; technologies for remote
verification of clients and protection against fraud; monetization of the new paradigm
of customer relations; digitalization of financial services; deployment of digital services
in banking, scepticism of bank shareholders on FinTech technologies (despite the fact
that more than 50% of Russian banks are actively investing in FinTech startups); the lack
of solutions in the b2b segment, cybersecurity and new opportunities in the regulatory
field. The use of AI technologies in retail banking services is a standard technological
process, now it is a turn for investment banking. Such impressive results should not
diminish the degree of attention to AI technologies: since they are a type of information
1. The reported study was funded by RFBR, project number 20-011-00454 «Ensuring the rights of investors in the
banking and financial sectors in the context of the digitalization of the economy in the Russian Federation and
the leading financial centres of East Asia: a comparative legal aspect.
2. Digalaki E. The $450B opportunity for the applications of artificial intelligence in the banking sector & examples
of how banks are using AI (2019).
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ELLA GORIAN
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technology, the security is the question that naturally emerge. In addition, the banking
and financial sectors are a part of national critical information infrastructure, that makes
them the priority target for cyber-attacks. Therefore, the issue of AI deployment and
information security is relevant and essential for the development of a sustainable and
effective cybersecurity mechanism.
There are two different approaches in regulation of AI technologies implementation:
regulatory (when a state prescribes the imperative regulations and controls the process
of AI deployment) and self-regulatory (when a state envisages a certain framework of
principles and expects both public and private sector to participate in rule-making
process). Russia is following the regulatory approach: both the National Strategy for
the Development of Artificial Intelligence3 and the national program Digital Economy
of the Russian Federation both entail the leading role of public authorities and national
corporations in ensuring information security. Singapore on the contrary has envisa-
ged the policies and projects aimed at the broadest involvement of private sector actors
(pro-business approach).
2. CONCLUSIONS
The most popular definition of artificial intelligence was made by John Mc-
Carthy, the head of the Stanford University Artificial Intelligence Laboratory, who
considers AI as “the science and engineering of making intelligent machines,
especially intelligent computer programs. It is related to the similar task of using
computers to understand human intelligence, but AI does not have to confine itself
to methods that are biologically observable”4. AI can also be defined as “cognitive
technologies” used in machine learning, including deep learning and predictive
analytics, natural language processing (NLP) including translation, classification,
clustering, and information extraction5. AI is being used in various spheres of life.
Despite the potential consequences of such a widespread deployment of AI, which
are being widely discussed by scholars and researchers, there is a need for a legal
definition of AI and determination of its place in legal relations. All this refers to the
“weak” AI, the opposite of which is the so-called “strong” AI – an artificial general
intelligence (AGI), which matches or exceeds human intelligence and is defined as
the ability “to reason, represent knowledge, plan, learn, communicate in natural
language and integrate all these skills toward a common goal”6. The latest modern
scientific developments present the “weak” AI, capable of simplifying and accelerating
the execution of certain information technology processes - artificial intelligence
technologies. Despite the limitations imposed by the modern level of technology,
computing power is growing exponentially (according to Moore’s law the number
of transistors in a dense integrated circuit doubles about every two years) and in
ten years the mankind will have the computing power, that is two hundred times
3. National Strategy for the Development of Artificial Intelligence (2019).
4. McCarthy J. What is artificial intelligence? Basic Questions (2007).
5. AI in Law: Definition, Current Limitations and Future Potential (2017).
6. AI in Law: Definition, Current Limitations and Future Potential (2017).
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