The Impact of RegTech on Compliance Costs and Risk Management
from the Perspective of Saudi Banks' Employees
LOTFI ZABAT, NAIMA SADAOUI, HOUCINE BENLARIA*,
SUMAYA AWAD KHADER AHMED, BALSAM SAEED ABDELRHMAN HUSSIEN,
BADRELDIN MOHAMED AHMED ABDULRAHMAN
College of Business,
Jouf University,
SAUDI ARABIA
*Corresponding Author
Abstract: - Through this research, we will be analyzing the Effect of RegTech on Compliance Costs and Risk
Management in the Banking Sector, mainly with the eye of people in administrative roles in Saudi Banks, a
total of 232. A new technological trend is reshaping the financial industry, RegTech, marked by various
advanced technological processes and automation. The main findings show that RegTech significantly reduces
compliance costs, confirming its cost-saving potential. Therefore, Employee perceptions are critical to
integrating and adopting RegTech within business operations. In addition, RegTech improves risk management
systems with more accessible procedures and better internal controls. This proves RegTech's ability to improve
the banking processes and strengthen the risk management system. Proportional to the organizational support,
tool investments, and tool diversity interactions are moderated, and operational efficiency is enhanced. This
research contributes significantly to the more profound knowledge of the implication of RegTech in the Saudi
banking sector, which facilitates transformation through renewed practices in the industry alongside its
efficiency.
Key-Words: - RegTech, banking sector, compliance costs, risk management, operational efficiency, technology
adoption, employee perspectives, financial institutions, internal controls, Saudi Arabia.
Received: July 29, 2023. Revised: February 29, 2024. Accepted: April 24, 2024. Published: May 17, 2024.
1 Introduction
Regulatory compliance and risk management are
references that foster the stability and stuck-
togetherness of banking organizations in the ever-
changing financial markets. The emergence of
leaner and more complex legal frameworks in place,
coupled with the increasing complexity of financial
transactions, has spawned a host of innovative
technical solutions geared toward simplifying
compliance operations, [1]. Technology Regulators,
or RegTech, have emerged as one of the significant
forces for change in the banking sector. RegTech is
a set of technologies specially developed for
enhancing regulatory processes, automated
compliance, and better risk management
frameworks. The integration of financial sectors
with high interconnectivity, as well as enhanced
regulatory requirements, poses a severe dilemma for
banks in Saudi Arabia, where they have to take into
consideration the deployment of modern technology
while implementing a rigorous regulatory regime,
[2].
Notably, the Kingdom of Saudi Arabia's
financial regime is developing very fast. The Central
Bank of the State of Saudi Arabia (SAMA), its
monetary regulatory authority, has led the way in
implementing forward-looking and internationally
applicable regulations that infuse the financial
system with integrity and soundness, [3]. The
regulatory boundary covers all the areas from a wide
range of topics that include AML, AML, KYC to
Basel III Compliance and data protection. That
means that the banks of Saudi have to expertly
execute their functional roles of being compliant
with the rules and procedures in an environment that
is complex and technological, [4]. In this regulated
setting where the rules become more and more
complex, the old measures used to be commonly
used can be changed due to that they are long and
difficult. In addition, having RegTech solutions,
there are added advantages like higher efficiency,
more precision, and the ability to monitor in real-
time, [5]. To mention a few, they are data analytics,
artificial intelligence [AI], machine learning [ML],
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Lotfi Zabat, Naima Sadaoui,
Houcine Benlaria, Sumaya Awad Khader Ahmed,
Balsam Saeed Abdelrhman Hussien,
Badreldin Mohamed Ahmed Abdulrahman
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and blockchain which are used to automate
compliance, quality control and error reduction, and
risk management.
1.1 Objectives
The trend of the Research aims to find out the
ability of RegTech to reduce the Costs of
Compliance on a bank’s risk system and the Job of
the employees, which we will call the Risk
Management System in Saudi banks. It covered by
the module the RegTech features including the
results of their adoption to banking operations,
organizational support being the RegTech
component, and finally the role of RegTech
becoming an efficiency and cost driver. In line with
this, the study will look at the mediating effect and
also adaptation of the bank to use in new regulatory
changes in the Kingdom. By doing the research this
paper aims to present the deep-rooted relationship
describing how of organization cooperation with
RegTech implementation is operating effectively,
with high efficiency, and with the participation of
employees in Saudi Arabia banks. The results are
designed so that they give extremely useful
materials that assist in developing strategies,
crafting policies, and adding to the ongoing
conversations in the formation of IT in finance and
regulation compliance.
1.2 Research Significance
The role of Regtech in the success of the core
objectives of common Saudi banks is contingent
upon the support from the management and
implementation of the technology. Financial
institutions will be able to incorporate tech for
operational efficiency, risk management and
compliance after the research provides them with
evidence, [6]. Saudi banks can drop out along the
way, increasing compliance costs, hence enduring
this complicated regulatory environment. It likewise
seems like RegTech does not only lower compliance
costs but also enables resource allocation and
becomes a key success factor. Organizational
support, as a mediating factor in the RegTech
adoption process, might be what banks wish to be
collaborative. Grasping how organization support
impacts RegTech's effectiveness further promotes
the creation of an inviting environment for the
adoption and usage of the technology. Therefore,
this research provides insight into the intricate link
between regtech, organizational dynamics, and the
case of the Saudi banking industry. Amplifies risk
management effectiveness, standardizations
compliance, and adopts financial technology. Such
investigation may help to identify a lot of actual
approaches, guided government policy, and
broadened expertise of SA finance institution's
financial technology, regulatory compliance, and
risk management.
2 Literature Review
RegTech and Bank Outcomes
RegTech, which stands for "Regulatory
Technology," is changing the banking industry's
shape by providing sophisticated tools that increase
compliance efficiency and decrease the associated
risks. Much research can be found on Saudi banks
and how RegTech improves risk management and
cuts operational expenses in compliance, [7]. The
banks can avoid monetary losses after letting their
regulatory functions be automated and organized by
RegTech technologies, as per [8]. Banks in Saudi
Arabia will be able to save on compliance-related
operational costs by automating ID checking,
reporting, and monitoring with the help of advanced
processing systems. Moreover, regTech solutions
make risk management processes better in Saudi
banks. What, research shows is that banks can
identify risks in real-time by monitoring RegTech's
transactional data. These measures bolster the bank
structure and assign the character of prompt,
rational, and data-driven solutions regarding risk
detection and adherence to regulatory needs.
RegTech can help optimize regulatory compliance
processes in the banking industry using automation
and utilization of the most recent technologies like
big data analytics, artificial intelligence, machine
learning, robotic process automation, and cloud
computing, [9]. Using these technologies, RegTech
platforms can automate and optimize regulation
processes, deliver more sensible and when-needed
data in time, and make it easy for financial
institutions and regulators to work together, [10].
Moreover, RegTech also aids banks in dealing with
complex and evolving regulatory obligations,
improving internal controls and risk management
systems, and changing corporate control functions'
roles, [11]. Implementing RegTech in banking can
be crucial in more efficient regulatory compliance,
paying everyone the just remuneration and
supporting the business model's sustainability, [12].
RegTech can address the efficiency problem
area in risk management of the banking sector by
utilizing technology platforms. Integrating RegTech
frameworks that support regulatory interpretation
and reporting automation will also help strengthen
compliance practices and fight against money
laundering. On top of that, incorporating the
RegTech functionalities, including data analytics,
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artificial intelligence, and machine learning, can be
a big contribution to implementing risk management
procedures since they can contribute to the bank's
operational efficiency and make risk-taking
behavior less prevalent. Moreover, implementing
Technologies in Risk (RegTechs) can optimize
internal business processes and increase risk
management capability, ultimately leading to stable
social and economic developments, [13], [14].
Although the essential thing is to consider the
digitalization effect on banking services, the
countries with high levels of internet use for
payments can face a negative impact of these
indicators as banking indicators such as return on
assets and loan portfolio quality, [15]. Overall,
adapting RegTech solutions will offer banks
possibilities to enhance and even automate risk
management processes and positively impact the
banking industry. RegTech is a type of technology
stemming from financial regulations. There are two
existing forums in RegTech: as a part of FinTech
companies and as a RegTech startup.
Organizational support is a crucial success
factor by which the impact of technology
implementation on the banking sector can be
measured. It has been found that such factors as
management support, firm size, and competitive
pressure positively affect the use of core banking
technology, [16]. Also, the study showed that core
banking functionality must have trial runs just when
there is an implementation, which suggests that
organizational support is essential for the success of
implementation, [17]. The Nigerian banking sector
study also suggested that technology management is
essential because it boosts people's performance at
work and makes the organization perform at the
highest level. One of the studies has discovered that
banks with higher capitalization presented in the
form of ICT were granting more decision-making
power to their branch managers, showing ICT's
positive effect on organizational independence, [18],
[19].
Organizational is associated with the technology
adoption/efficiency link, [20], [21]. Among the
change support measures, training and participation
in decision-making can act as a shield against the
negative effects of organizational change on the
outcome of technology implementation, [22].
Cultivating change support that is challenging to the
needed changes remains the most efficient approach
to this task, [23]. Additionally, perceived
organizational support mediates between technology
adoption and extra-role performance, affective
organizational commitment, and job satisfaction,
[24]. Gratitude, felt obligation, and pride are the
mechanisms through which the perception of
organizational support is related to these outcomes;
of all these mechanisms, gratitude is the most
efficient as a mediator. Institutional support is the
key facilitating factor for self-efficacy and
innovative behavior, which is the medium element
in the relationship between institutional support and
employee technology adoption behavior. In
conclusion, organizational support is vital in
moderating the link between technology adoption
and productivity outcomes. It reduces the tangible
consequences of change demands and increases a
positive perception of employees and their
behaviors.
H1: There are relationships between key Regulatory
Technology (RegTech) implementation dimensions
and fundamental outcomes in Saudi Arabian banks.
Specifically:
H1a: Duration of RegTech Usage (DR) influences
Compliance Costs (CCS).
H1b: Duration of RegTech Usage (DR) influences
Risk Management Effectiveness (RME).
H1c: Diversity of Tools (DT) influences Compliance
Costs (CCS).
H1d: Diversity of Tools (DT) influences Risk
Management Effectiveness (RME).
H1e: Investment Levels (IL) Influence Compliance
Costs (CCS).
H1f: Investment Levels (IL) influence Risk
Management Effectiveness (RME).
H2: The organizational support (OSP) and
RegTech implementation affect operational
efficiency (OEF). Particularly:
H2a: Organizational Support (OSP) and Diversity
of Tools (DT) influence Operational Efficiency
(OEF).
H2b: The Organizational Support (OSP) and
Investment Levels (IL) influences Operational
Efficiency (OEF).
Operational Efficiency as a Mediator in RegTech
Implementation
RegTech is undoubtedly helpful in operational
efficiency because it can automate and bring the
idea of digital innovations into the picture. It can
also allow the financial industry to meet regulatory
standards and reporting. RegTech allows for
successful strategic management activities and
regulates organizational and regulatory procedures,
resulting in the achievement of commercial and
prudential objectives, [25]. Digitalization, which is
technology-driven by RegTech, results in
operational efficiency improvements, increasing the
output of the business and, hence, the company's
overall performance, [26]. More patient safety,
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increased satisfaction of care team members, and
faster/more efficient processes are the primary
benefits of RegTech in many specific industries,
such as health care, from our standpoint, [27], [28].
Similarly, RegTech can provide a nearly real-
time and proportionate regulatory system, which
will help in risk identification and mitigation and
ensure general compliance with regulations and
regulatory agencies. The supplementing capability
of RegTech that allows Saudi banks to do scenario
modeling and predictive analytics, [29], reinforces
risk management systems. Consequently, this allows
them to predict and lessen the risks of a new kind,
which helps to keep the ecosystem stable.
In light of this, the research indicates how
RegTech can augment banks within Saudi to build a
compliance culture. In the view of the research,
RegTech implementation promotes a culture of
transparency, opens the company structure, and
provides compliance with all regulations. This
cultural change is indispensable when people
consider banks necessary.
Operational efficiency is characterized as a
moderating factor in the cause-effect relationship
between the implementation of RegTech and
compliance costs and risk management
effectiveness, [30]. Increases in operational work
efficiency can lead to the enhancement of
environmental and financial performances, [31].
The RegTech platform system provides conditions
for early identification and proactive response to
risks in providing financial services and running
businesses, thus ensuring the stability of services or
running of businesses, [32].
This paper looks at operational efficiency as a
link function connecting the regulators of
technology in Saudi Arabian banks. This hypothesis
works as a mediator, with the RegTech
implementation extent determining the relationship
between the compliance costs and risk management
effectiveness. The paper illustrates that RegTech is
an intervening process impacting Saudi bank
operational processes, compliance, and risk
management.
H3: The relationship between different dimensions
of RegTech implementation and banking outcomes
in Saudi banks is mediated by Operational
Efficiency (OEF).
H3a: The relationship between Duration of RegTech
Usage (DR) and Compliance Costs (CCS) is
mediated by Operational Efficiency (OEF).
H3b: The relationship between Duration of RegTech
Usage (DR) and Risk Management Effectiveness
(RME) is mediated by Operational Efficiency
(OEF).
H3c: The relationship between Diversity of Tools
(DT) and Compliance Costs (CCS) is mediated by
Operational Efficiency (OEF).
H3d: The relationship between Diversity of Tools
(DT) and Risk Management Effectiveness (RME) is
mediated by Operational Efficiency (OEF).
H3e: The relationship between Investment Levels
(IL) and Compliance Costs (CCS) is mediated by
Operational Efficiency (OEF).
H3f: The relationship between Investment Levels
(IL) and Risk Management Effectiveness (RME) is
mediated by Operational Efficiency (OEF).
Organizational support and technology-
Operational efficiency
Organizational support influences the relationship
between technology and operational efficiency,
[33], [34], [35]. It has been widely recognized that
technology, such as information technology (IT),
can enhance operational performance by improving
information capability and facilitating the handling
of large amounts of information within and between
organizations, [36]. However, the effectiveness of
technology in improving operational efficiency is
influenced by organizational factors, such as
organizational structure and top management
support, [37]. Organizational structure affects the
relationship between technology investment and
operational performance, as it determines the level
of coordination, autonomy, and creativity within the
organization. Top management support is crucial in
achieving synergy between technology and
organizational structure, as it provides the
appropriate environment and incentives for
innovation and problem-solving.
Organizational support is crucial in managing
compliance costs and risks in the banking sector,
[38]. Implementing a comprehensive risk
management system requires the organization's
support and commitment, as it involves neutralizing
negative consequences and forming qualitative
characteristics of banking products, [39].
Developing a risk management system is necessary
to effectively manage risks and ensure the bank's
compliance with regulations and internal standards,
[40]. Compliance management systems (CMS) can
be used to reduce the risk of fraud and corruption,
but the effectiveness of these measures depends on
careful selection and evaluation, [41]. The growth of
risk management and compliance as governance
functions in banking markets is driven by
government regulation and practices developed in
the private sector, [42].
H4: Operational Efficiency (OEF) serves as a
mediator in the relationship between the indirect
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interaction of Organizational Support (OSP) and
the application of RegTech on banking outcomes.”
H4a: The interaction between Organizational
Support (OSP) and Diversity of Tools (DT)
indirectly influences Compliance Costs (CCS)
through Operational Efficiency (OEF).
H4b: The interaction between Organizational
Support (OSP) and Diversity of Tools (DT)
indirectly influences Risk Management Effectiveness
(RME) through Operational Efficiency (OEF).
H4c: The interaction between Organizational
Support (OSP) and Investment Levels (IL) indirectly
influences Compliance Costs (CCS) through
Operational Efficiency (OEF).
H4d: The interaction between Organizational
Support (OSP) and Investment Levels (IL) indirectly
influences Risk Management Effectiveness (RME)
through Operational Efficiency (OEF).
H4e: Organisational Support (OSP) directly
influences Compliance Costs (CCS) through
Operational Efficiency (OEF).
H4f: Organisational Support (OSP) directly
influences Risk Management Effectiveness (RME)
through Operational Efficiency (OEF).
H4g: The interaction between Organizational
Support (OSP) and Duration of RegTech Usage
(DR) indirectly influences Compliance Costs (CCS)
through Operational Efficiency (OEF).
H4h: The interaction between Organizational
Support (OSP) and Duration of RegTech Usage
(DR) indirectly influences Risk Management
Effectiveness (RME) through Operational Efficiency
(OEF).
Employee Role and Technology Implementation
in Banking
Technology can impact employee roles in banks in
several ways. Firstly, automation through ATMs,
internet banking, and mobile banking can save time
and elevate employee workload, increasing
productivity, [43]. However, this automation may
also limit the utilization of employee skills, resulting
in some wastage of resources, [44]. Secondly, using
information technology (IT) in banks can positively
affect employee performance by reducing workload
and improving accuracy, [45]. Banks' IT-based
services are convenient and user-friendly, boosting
customer satisfaction, [46], [47]. Technology makes
information easy to access and use, helping bank
employees provide quality service. Employees need
training to use new technologies effectively.
Employee engagement and role dynamics
significantly impact technology implementation.
Engaged workers are more productive, customer-
focused, and process-aware, increasing profits, [48].
Employee engagement and performance improve
with psychological capital like self-efficacy, hope,
optimism, and resilience, [49]. Job resources like
social support, challenging work, and leadership
potential boost employee engagement, [50].
Additionally, software project success depends on
employee empowerment and engagem,ent [51].
Communication technology use (CTU) can improve
employee well-being through accessibility and
efficiency and decrease it through interruptions and
unpredictability, [52]. To understand CTU's impact
on employee well-being, consider its resources and
demands.
H5: The role of employees (ER) has an impact on
Compliance Costs (CCS), Operational Efficiency
(OEF), and Risk Management Effectiveness (RME).
This hypothesis includes the following sub-
hypotheses:
H5a: Employee Role (ER) influences Compliance
Costs (CCS).
H5b: Employee Role (ER) influences Operational
Efficiency (OEF).
H5c: Employee Role (ER) influences Risk
Management Effectiveness (RME).
The Conditional Effects of RegTech
Implementation on Operational Efficiency
The effects of technology solutions in banking are
regulated by the regulatory environment, size of
banks, and technology regimes. Low levels of
efficiencies emerge due to the regulatory barriers to
bank operations and high capital requirements, [53],
[54]. Competition for the smaller-sized banks is
based on two factors, relationship-lending and
significant network density returns, while the larger
may need help with diseconomies of scale, [55]. The
study of German banks also found three technology
regimes: Customer and retail, Small and specific,
and Gen/General and association, emphasizing the
critical role of banking technology, [56]. The factors
demonstrated that the technology products in the
banking industry should be assessed from different
contexts.
[57], showed that RegTech solutions, directly
and indirectly, impact the banking environment and
services. The direct impact includes a reduction in
cost and risk management, such as adequate
identification and mitigation of risks—however,
indirect effects were found to mold employee
perceptions towards work environment, job roles,
and RegTech effectiveness. However, the role of
organizational culture, employee training, and skill
development was found to cause changes in banking
services and adaptability to RegTech solutions. It is
hypothesized that both direct and indirect effects
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influence positive changes within Saudi banks and
employee perceptions towards their job role and
technology use. Predicting the hypothesis's
acceptance or rejection helps estimate the research
outcome. In general, the role of RegTech in the
digitalized era has changed the working processing
and environment in banking services, [57].
[58], explained how RegTech helps build a
more robust compliance infrastructure by
automating procedures and reducing the chance of
human mistakes. The research on how RegTech has
affected Saudi banks' compliance expenses and risk
management highlights the revolutionary
possibilities of this technology. Financial
institutions in the Kingdom can significantly benefit
from RegTech, which offers a range of cost-saving
initiatives, increased risk detection capabilities, and
a culture of compliance.
H6: There are conditional effects of RegTech
implementation on operational efficiency.
Subhypotheses of this hypothesis include:
H6a: RegTech Usage Duration (DR) affects OEF
conditionally.
H6b: Diversity of Tools (DT) affects Operational
Efficiency conditionally.
H6C: Investment levels (IL) condition operational
efficiency (OEF).
Numerous studies have investigated the impact
of RegTech on both risk management and
compliance costs in the financial sector. However,
the attitudes of Saudi bank employees towards
RegTech application need to be sufficiently studied.
Additionally, the development of RegTech solutions
and their consequences on banking activities is
another crucial aspect that needs to be described.
This research aims to examine how Saudi bank
officials view RegTech and how it affects their
productivity and performance. In addition, it
identifies cultural aspects, employee preparedness,
and organizational dynamics that determine the
outcome of a technological change. This study seeks
to add innovativeness to the existing body of
knowledge by uncovering the factors that can
enhance and hinder the adoption of RegTech by
Bank employees in Saudi.
3 Methodology
This study investigates the Impact of RegTech on
Compliance Costs and Risk Management within the
banking sector. It draws data from 232 employees in
administrative roles within Saudi banks. For this
purpose, a primary quantitative research method
was used, and information was gathered from
employees working in Saudi Bank. They are using a
closed-ended questionnaire based on a 5-point
Likert scale.
Smart PLS software was used for analysis and
statistical findings after data collection. Descriptive
statistics were used to assess the variables' key
features and normality in this study. The variables'
relationships were assessed using correlation
analysis. After that, reliability analysis assessed the
current research's latent constructs' consistency.
Cronbach's alpha should exceed 0.7 to ensure latent
variable construct reliability. VIF was also used to
assess multicollinearity in the current research,
which should be below 5 or 10, [59], [60].
After ensuring the reliability and
multicollinearity of the variables, the path
coefficient was used to evaluate the direct effect of
investment level, diversity of tools, and duration of
RegTech usage on compliance Cost and risk
management effectiveness. Additionally, it also
considered the interaction with organizational
support. Moreover, the indirect effect has also been
used to analyze the mediating influence of
operational efficiency on RegTech and compliance
costs and risk management effectiveness.
Furthermore, the moderating role of the employee
was also considered to analyze the impact on
compliance costs, operational efficiency, and risk
management effectiveness. Table 1 represents the
variables and questions used to analyze the impact
of RegTech on compliance cost, risk management,
and operational efficiency in Saudi banks.
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Table 1. Questionnaire Development
Variables
Statements
Source
Compliance Costs (CCS)
Influence of tech investment on compliance costs.
Adequacy of current RegTech investment.
RegTech integration for cost-saving.
Impact on compliance-related expenses.
RegTech's role in reducing compliance challenges.
[1], [7], [8]
Duration of RegTech usage. (DR)
Impact on organizational efficiency.
Relationship with risk management.
Role in reducing compliance costs.
[8]
Diversity of tools (DT)
Use of diverse RegTech tools for compliance.
Benefits in risk management.
Adoption of emerging technologies.
[10]
Investment levels (IL)
Priority of RegTech investment.
We are addressing unique compliance challenges.
Improving risk management efficiency.
[12], [13]
Operational Efficiency (OEF)
Improvement in operational efficiency.
Reduction in manual processes.
Efficiency gains in various departments.
Value for operational decision-making.
[25], [26]
Organisational Support (OSP)
Enhancing resource allocation.
Contribution to risk management and compliance.
Investment in employee training.
Encouraging resource optimization.
[16], [17]
Risk Management Effectiveness (RME)
RegTech's impact on risk identification.
Efficiency in risk assessment.
Automating processes and error reduction.
Addressing change-related risks.
Success in risk management.
[14], [15]
Employee Role (ER)
Role of collaboration in efficiency.
Employee contribution to cost efficiency.
Employee roles in risk mitigation.
[43], [45]
4 Results of the Study
Table 2 presents descriptive statistics and normality
tests for various constructs in a study with 232
observations each. The constructs, including
Compliance Costs (CCS), Decision Rights (DR),
Digital Technology (DT), Innovation Leadership
(IL), Operational Efficiency Factor (OEF),
Organizational Support (OSP), Risk Management
Effectiveness (RME), and Employee Role (ER),
exhibit mean values ranging from 3.693 to 4.328,
indicating a generally positive presence among
respondents. Standard deviations are below 1,
showing varying variability. All constructs have
negative skewness and varying degrees of excess
kurtosis, with IL peaking at 2.340. An anomaly is
observed in QE (OEF), showing zero for mean and
standard deviation. These statistics suggest a
consistent response pattern across the sample, albeit
with some deviations from normality, particularly in
IL. Table 2 indicates a reasonable degree of
consistency and normality in the data, laying a solid
foundation for further inferential statistical analysis.
Table 2. Descriptive Statistics and Normality Test (Mean and SD)
Mean
Standard deviation
Excess kurtosis
Skewness
Number of observations used
3.932
0.746
1.113
-0.789
232
3.693
0.943
0.181
-0.698
232
4.018
0.741
0.746
-0.704
232
4.328
0.617
2.340
-1.043
232
3.997
0.743
1.395
-0.809
232
3.944
0.686
0.910
-0.363
232
0.000
0.000
n/a
n/a
232
3.711
0.854
0.078
-0.467
232
3.885
0.877
1.006
-0.921
232
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Balsam Saeed Abdelrhman Hussien,
Badreldin Mohamed Ahmed Abdulrahman
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Table 3 provides a correlation analysis among
various constructs in a study, revealing significant
interrelationships. Compliance Costs (CCS) exhibit
strong positive correlations with all other constructs,
most notably with Operational Efficiency Factor
(OEF) and Risk Management Effectiveness (RME),
both over 0.8, suggesting that higher compliance
costs are closely associated with enhanced
operational efficiency and risk management. DR
and DT parallel with CCS and RE setting strong
functional links. IL (Innovation Leadership)
highlights the binding relationship between Digital
Technology and innovation. OEF is highly
associated with CCS and RME, which indicates its
weighty roles in compliance and risk management.
Organisational Support (OSP) demonstrates strong
connections, particularly with OEF, underlining its
importance in operational efficiency. Similarly,
Employee Role (ER) presents moderate to strong
correlations across the board, highlighting its
influence on various organizational aspects,
especially compliance and operational efficiency.
These correlations underscore the
interconnectedness of these constructs, suggesting
that enhancements in decision rights, technology,
and leadership are vital to improving operational
and risk management outcomes.
Table 4 in the study presents a comprehensive
analysis of various constructs, focusing on their
reliability, explained variance, and collinearity
statistics. The reliability of the constructs, measured
by Cronbach's Alpha, indicates strong internal
consistency across most constructs. Compliance
Costs (CCS) show a high-reliability score of 0.909,
and Decision Rights (DR), Digital Technology
(DT), and Risk Management Effectiveness (RME)
also demonstrate good reliability with values above
the 0.7 threshold. Notably, Innovation Leadership
(IL), Operational Efficiency Factor (OEF),
Organizational Support (OSP), and Quality
Enhancement (QE) related to OEF exhibit
exceptionally high Cronbach's Alpha values, some
exceeding 1.0, which is unusual and may necessitate
further examination.
Table 3. Quality Assessment and Criteria Constructs
Constructs
CCS
DR
DT
IL
OEF
OSP
RME
ER
CCS
1.000
DR
0.745
1.000
DT
0.733
0.714
1.000
IL
0.686
0.535
0.705
1.000
OEF
0.818
0.590
0.648
0.638
1.000
OSP
0.720
0.548
0.614
0.571
0.809
1.000
RME
0.819
0.648
0.680
0.593
0.824
0.732
1.000
ER
0.706
0.566
0.592
0.552
0.706
0.662
0.698
1.000
Fig. 1: Output loading of factors
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Table 4. Quality criteria
Cronbach Alpha
R-square
R-square Adjusted
Collinearity statistics (VIF)
CCS
OEF
RME
0.909
0.702
0.702
N/a
N/a
N/a
0.758
0.741
0.987
N/a
2.128
N/a
0.757
0.706
0.705
N/a
4.876
N/a
1.076
N/a
N/a
N/a
3.830
N/a
0.993
N/a
N/a
2.956
N/a
2.956
0.984
N/a
N/a
N/a
4.513
N/a
1
N/a
N/a
2.206
N/a
N/a
0.891
N/a
N/a
N/a
N/a
N/a
N/a
N/a
N/a
N/a
3.757
N/a
N/a
N/a
N/a
N/a
4.567
N/a
N/a
N/a
N/a
N/a
3.494
N/a
Regarding explained variance, the R-square and
adjusted R-square values are noteworthy for CCS,
DR, and DT. CCS has an R-square of 0.702,
suggesting the model explains approximately 70.2%
of its variance. DR and DT also show substantial
explanatory power, with R-squares of 0.741 and
0.706, respectively.
The constructs demonstrate acceptable levels of
collinearity, assessed through Variance Inflation
Factor (VIF) values, indicating no severe
multicollinearity. VIF values for DR, DT, IL, OEF,
and OSP, as well as their interactions (OSP x DT,
OSP x IL, OSP x DR), are all below the commonly
used thresholds of 5 or 10, suggesting that
multicollinearity does not significantly impact the
study's findings, [61], [62], [63]. Table 4 portrays
the constructs as reliable and effective explanatory
without significant multicollinearity concerns.
In Table 5 and Figure 1, the study analyses the
direct effects and interactions concerning the extent
of Regulatory Technology (RegTech)
implementation in the banking sector. The findings
are as follows:
For H1, regarding direct relationships, the
duration of RegTech usage (DR) shows a non-
significant effect on Compliance Costs (CCS), with
a standard beta of 0.341 and a p-value of 0.121,
leading to the rejection of this hypothesis. However,
DR's influence on Risk Management Effectiveness
(RME) is statistically significant, evidenced by a
standard beta of 0.287 and a p-value of 0.000,
warranting acceptance of this relationship. The
diversity of tools (DT) demonstrates a significant
positive impact on CCS, with a standard beta of
0.209 and a p-value of 0.000, supporting its positive
relationship. However, DT's effect on RME, despite
a relatively high standard beta of 0.356, is not
statistically significant (p-value = 0.425), resulting
in hypothesis rejection. Investment levels in
RegTech (IL) significantly impact CCS, indicated
by a standard beta of 0.373 and a p-value of 0.000.
However, its effect on RME (standard beta = 0.285)
is not significant (p-value = 0.312), leading to the
rejection of this relationship.
In H2, which examines interactions with
Organizational Support (OSP), the interaction
between OSP and DT about Operational Efficiency
(OEF) is statistically significant, with a standard
beta of 0.115 and a p-value of 0.002, confirming this
positive relationship. Furthermore, the interaction of
OSP with IL on OEF is significant. However, it
presents a negative impact, as shown by a standard
beta of -0.083 and a p-value of 0.011, still resulting
in the acceptance of the hypothesis.
In conclusion, Table 5's analysis elucidates
the dynamics of RegTech implementation in banks,
highlighting how certain aspects, like the duration of
usage and diversity of tools, variably influence
compliance costs and risk management
effectiveness. The fact that organizational support is
the modifier in the relationship between the two
operation-efficient factors(i.e., the investment level
and the tool diversity) is posited by the case study.
These observations hint that RegTech in the banking
industry must adapt a carefully considered method
to its application and adoption.
Shown below in Table 6 will be an explanation
of the direct effect as well as the other interaction
terms that occur within the context of RegTech
implementation in the Saudi Arabian banking sector
that will show the relationship that is mediated and
the importance of organizational support.
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Table 5. Summary of Direct Effects and Interactions
Hypotheses
Relationships
Std beta
t value
P values
Decision
H1 (Direct Relationships)
DR -> CCS
0.341
18.209
0.121*
reject
DR -> RME
0.287
10.409
0.000**
accept
DT -> CCS
0.209
7.069
0.000**
accept
DT -> RME
0.356
9.381
0.425*
reject
IL -> CCS
0.373
13.438
0.000**
accept
IL -> RME
0.285
7.482
0.312*
reject
H2 (Interaction with
Organizational Support)
OSP x DT -> OEF
0.115
3.081
0.002**
accept
OSP x IL -> OEF
-0.083
2.536
0.011*
accept
Significant at P** =< 0.01, p*<0.05
Note: Investment levels (IL), Diversity of tools (DT), Duration of RegTech usage (DR), Compliance Costs (CCS), Risk Management
Effectiveness (RME), Operational Efficiency (OEF), Organizational Support (OSP)
The table showing the relationships inevitably
accompanies formal beta coefficients, t-values, and
p-values every time it is feasible to decide whether
to accept or reject the hypothesis towards which the
data is directed.
In H3 which regresses mediated interactions of
RegTech usage, the duration for which users use
RegTech, DR, is shown to have a significant
indirect effect on Compliance Costs, CCS, through
Operational Efficiency, OEF, with the standard beta
of 0.275, and a p-value of 0.005, which supported
the hypothesis acceptance. Likewise, DR's indirect
effect on Risk Management Effectiveness (RME)
through OEF is significant (standard beta = 0.227,
p-value = 0.004), warranting acceptance. The
diversity of tools (DT) also demonstrates significant
indirect effects on both CCS (standard beta = 0.287,
p-value = 0.012) and RME (standard beta = 0.237,
p-value = 0.018), leading to the acceptance of these
hypotheses. Investment levels in RegTech (IL)
exhibit a strong positive mediated impact on CCS
(standard beta = 0.356, p-value = 0.000) and RME
(standard beta = 0.294, p-value = 0.001), resulting in
the acceptance of both hypotheses.
Under H4, which examines the indirect
interaction with Organizational Support (OSP), the
interaction of OSP with DT reveals a significant
effect on CCS through OEF (standard beta = 0.084,
p-value = 0.003) and on RME (standard beta =
0.069, p-value = 0.005), leading to the acceptance of
these interactions. However, the interaction of OSP
with IL shows non-significant effects on both CCS
(standard beta = -0.061, p-value = 0.112) and RME
(standard beta = -0.050, p-value = 0.217), resulting
in the rejection of these hypotheses. Furthermore,
OSP significantly directly affects the mediated
relationships between OEF and CCS (standard beta
= 0.548, p-value = 0.000) and RME (standard beta =
0.453, p-value = 0.000), confirming these
hypotheses. Additionally, the interaction of OSP
with DR shows significant effects on CCS (standard
beta = -0.060, p-value = 0.009) and RME (standard
beta = -0.049, p-value = 0.007), leading to their
acceptance.
Overall, Table 6 illustrates that the effects of
RegTech implementation on compliance costs and
risk management effectiveness are significantly
mediated by operational efficiency. It also
highlights the complex role of organizational
support, which significantly influences these
mediated relationships in varying directions.
Table 7 in the study provides an analysis of the
influence of Employee Role (ER) on key banking
metrics, explicitly examining its impact on
Compliance Costs (CCS), Operational Efficiency
(OEF), and Risk Management Effectiveness (RME).
The analysis is detailed in standard beta coefficients,
t-values, and p-values, which inform the decision to
accept or reject each hypothesis.
The hypothesis regarding the influence of
Employee Role (H5) reveals significant
relationships across all examined areas. The impact
of ER on CCS is notably significant, as indicated by
a standard beta of 0.218 and a robust t-value of
9.861, along with a p-value of 0.000, leading to the
acceptance of this hypothesis. This suggests that the
role of employees within banks significantly affects
compliance costs. In terms of Operational
Efficiency (OEF), ER also shows a substantial
impact, evidenced by a standard beta of 0.180, a t-
value of 7.655, and a p-value of 0.000, warranting
the acceptance of this relationship. This finding
highlights the pivotal role that employees play in
enhancing operational efficiency. Finally, the
influence of ER on RME is similarly significant,
with a standard beta of 0.226, a t-value of 8.950, and
a p-value of 0.000, supporting the hypothesis that
employee roles significantly contribute to the
effectiveness of risk management in banks.
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Table 6. Summary of Indirect Effects and Interactions
Hypotheses
Relationships
Std beta
t value
P values
Decision
H3 (Mediated Relationships):
DR -> OEF -> CCS
0.275
2.810
0.005**
accept
DR -> OEF -> RME
0.227
2.892
0.004**
accept
DT -> OEF -> CCS
0.287
2.518
0.012*
accept
DT -> OEF -> RME
0.237
2.376
0.018*
accept
IL -> OEF -> CCS
0.356
3.770
0.000**
accept
IL -> OEF -> RME
0.294
3.345
0.001**
accept
H4 (Indirect Interaction with Organizational Support)
OSP x DT -> OEF -> CCS
0.084
2.967
0.003**
accept
OSP x DT -> OEF -> RME
0.069
2.804
0.005**
accept
OSP x IL -> OEF -> CCS
-0.061
2.632
0.112*
reject
OSP x IL -> OEF -> RME
-0.050
2.382
0.217*
reject
OSP -> OEF -> CCS
0.548
6.043
0.000**
accept
OSP -> OEF -> RME
0.453
5.648
0.000**
accept
OSP x DR -> OEF -> CCS
-0.060
2.632
0.009**
accept
OSP x DR -> OEF -> RME
-0.049
2.691
0.007**
accept
Significant at P** =< 0.01, p*<0.05
Note: Investment levels (IL), Diversity of tools (DT), Duration of RegTech usage (DR), Compliance Costs (CCS), Risk
Management Effectiveness (RME), Operational Efficiency (OEF), Organizational Support (OSP)
Table 7. Influence of Employee Role on Compliance Costs, Operational Efficiency, and Risk
Management Effectiveness
Hypotheses
Relationships
Std beta
t value
P values
Decision
H5 (Employee Role Influence)
ER <- CCS
0.218
9.861
0.000**
accept
ER <- OEF
0.180
7.655
0.000**
accept
ER <- RME
0.226
8.950
0.000**
accept
Significant at P** =< 0.01, p*<0.05
Note: Employee Role (ER), Compliance Costs (CCS), Operational Efficiency (OEF), and Risk Management
Effectiveness (RME)
Table 8. Summary of Conditional Direct and Indirect Effects in Organisational Support Context
Hypotheses
Path
Condition
Std. Beta
t-Value
p-Value
Decision
H6
DR -> OEF
OSP at Mean
0.054
2.807
0.005**
accept
DT -> OEF
OSP at Mean
0.061
2.213
0.027*
accept
IL -> OEF
OSP at Mean
0.159
6.335
0.000**
accept
Significant at P** =< 0.01, p*<0.05
Table 8 in the study presents an in-depth
analysis of the conditional direct and indirect effects
of different aspects of Regulatory Technology
(RegTech) implementation in the context of
Organizational Support (OSP). This analysis is
conducted under the condition of OSP being at its
mean level, focusing on how this affects the
relationships with Operational Efficiency (OEF),
Compliance Costs (CCS), and Risk Management
Effectiveness (RME).
For the conditional direct effects under H6, the
Duration of RegTech Usage (DR) shows a
significant positive effect on OEF, with a standard
beta of 0.054, t-value of 2.807, and p-value of
0.005. This indicates that the longer the duration of
RegTech usage, the greater its impact on operational
efficiency, especially in the context of average
organizational support. The Diversity of Tools (DT)
used in RegTech implementation also positively
influences OEF, as evidenced by a standard beta of
0.061, t-value of 2.213, and p-value of 0.027.
Investment Levels (IL) in RegTech exhibit a notably
strong positive effect on OEF with a standard beta
of 0.159, a t-value of 6.335, and a p-value of 0.000,
suggesting that higher investment levels
significantly enhance operational efficiency in the
presence of average organizational support.
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Regarding the conditional indirect effects, the
path from DR through OEF to CCS is significant
(standard beta = 0.040, t-value = 2.452, p-value =
0.014), suggesting that the duration of RegTech
usage indirectly influences compliance costs
through its impact on operational efficiency.
Likewise, the indirect effect of DR on RME
through OEF is significant (standard beta = 0.033, t-
value = 2.544, p-value = 0.011). The impact of DT
on CCS and RME through OEF is also statistically
significant, with standard betas of 0.044 (t-value =
2.007, p-value = 0.045) and 0.037 (t-value = 2.105,
p-value = 0.035), respectively. Moreover, IL's
indirect influence on RME and CCS through OEF is
robust, with significant effects (standard betas of
0.096 and 0.116, t-values of 4.775 and 4.434, and p-
values of 0.000 for both paths), highlighting the role
of investment in enhancing risk management and
compliance cost outcomes via operational
efficiency.
5 Discussion
RegTech leverages emerging technologies like AI
and Blockchain to modernize regulatory compliance
and improve compliance, [8]. Moreover, they
discovered that AI, big data, and machine learning
could standardize compliance, generate precise data,
and collaborate among borders. The RegTech
increases the effectiveness of the risk managers and
internal control departments. Therefore, the current
research article compares the cost of compliance
and risk management of Saudi banks after
implementing RegTech in their employees. A
current study revealed that compliance costs were
not affected by the RegTech. Discovery also shows
that the diversity of tools and impact levels of
compliance on the cost of Saudi banks is positive
with significance. Previous research has highlighted
how RegTech uses technology innovations to
enhance banks' risk management processes, [8] [13].
RegTech is from the point of view of risk
management and even improves the results of the
corresponding activities. Impairing or poor levels of
banking risk management are little affected by
various tools and investment levels. Earlier studies
have revealed that RegTech assists banks in
fulfilling complex and regulatory requirements, thus
improving money risk management, [11]. [8],
Moreover, found that technology can also improve
handling risk management by banks. The deduction
from the findings is that H1 is partially accepted.
The role of organizations remains a question of
interest to determine how they can affect working
efficiency. Indirect and, at the same time,
Significant organizational support is a base for
efficiency improvement. In the past, organizational
support was shown to be a factor in the link between
technology and operational efficiency through other
studies, [33], [34]. The findings have been accepted.
Thus, the null hypothesis (H2) has been accepted,
which shows that organizational support
significantly impacts operational efficiency.
The recent research, however, analyzed the
mediating role of operational efficiency between the
implementation dimensions of RegTech and the
outcomes of the Saudi Arabian banks.
Organizational performance undisputedly mediates
(or, in other words, reduces) compliance cost and
risk management. Earlier studies have shown that
technology advances trim operational costs, refine
risk management, and reduce compliance costs,
[37]. Results corroborate the working hypothesis,
implying that the higher the operational efficiency
of a specific business, the higher the associated
internal compliance costs and risks. Furthermore,
RegTech investigated the organization support as a
moderating effect between operational efficiency
and compliance cost.
On the other hand, risk management.
Organizational help will support RegTech
communication directly, but the operational
efficiency is positively correlated and significant.
The current findings confirm the validity of H4.
The employee role has also been examined as a
moderator of compliance cost, operational
efficiency, and risk management. Employee role
positively and significantly affects cost compliance.
The current research also found that employee role
positively affects operational efficiency. According
to the literature, employee role positively and
significantly affects Saudi bank operational
efficiency. Time savings and increased workload
boost productivity and operational efficiency, [43].
Risk management effectiveness is also
positively impacted by employee role. Previous
studies found that employee roles improve risk
management, [47]. According to the current
research, H5 is also accepted, indicating that
employees affect Saudi banks' compliance costs,
operational efficiency, and risk management.
RegTech reduces human error and automates
processes to improve compliance infrastructures,
[5]. According to a study, RegTech can transform
risk management and compliance costs at Saudi
banks. [8], claim that RegTech solutions can
automate and streamline regulatory compliance and
save banks money. Automating data collection,
reporting, and monitoring can reduce compliance
costs for Saudi banks. Correlation analysis reveals
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significant relationships between study constructs.
All other constructs have strong positive
correlations with Compliance Costs (CCS),
especially OEF and RME, which are above 0.8. This
suggests that risk management, operational
efficiency, and compliance costs are linked.
Digital technology and innovation leadership
(IL) are linked, suggesting innovation and
technology application blend well. OEF's strong
correlation with CCS and RME shows its impact on
compliance and risk management. Organizational
Support (OSP) is crucial to operational effectiveness
due to its close relationship with OEF. Employee
Role (ER) also has moderate to strong correlations
across the board, affecting operational efficiency
and compliance. These connections show how these
categories are related and suggest that improving
decision-making authority, technology, and
leadership benefits operations and risk management.
The other research also investigated the direct
impact of RegTech usage duration on OEF.
RegTech usage supports OEF and indicates that its
impact on operational efficiency increases with its
usage period. The variety of RegTech and
investment levels increase OEF (Opportunity for the
Economy to Fly). Therefore, although it is
challenging for RegTech to lower direct compliance
costs, it makes compliance operations more
efficient. Investment level and diversity have an
indirect and important effect on RME and CCS via
OEF. H6 is thus affirmed based on these results.
H6 highlights how RegTech embedding plays a
part in OEF within the framework of organizational
readiness. This exploration is consistent with earlier
studies that propose that regulator environment,
bank size, and technology regulations influence
banking technology solutions, [54], [55], [56]. The
use of RegTech in the banking sector has direct and
indirect consequences, such studies as [57] suggest.
Immediate impacts include cost reduction and risk
management, while the impacts, in the long run, are
in employees' perceptions, job roles, and RegTech
solution effectiveness. Organizational culture,
training, and skills development influence a bank's
Regtech adaptability. The results lend credence to
the assumption that the implementation of RegTech
improves Saudi bank employees' attitudes toward
the technology and its use.
Although all the above factors may be
determinants, H6 states that there are operational
efficiency effects of RegTech regulation. And, the
data in Table 8 support it. There is a conditional
effect of organizational support on both tool
diversity (H6b), tool usage duration (H6a), and
investment levels (H6c) about operation efficiency
when the support is average. Thus, the implications
of this observation are having such elements and
organizational backing in mind when introducing
RegTech solutions in banks as a way of improving
the operational efficiency of these institutions, [5],
[54], [57].
6 Conclusion
To conclude, this research studies the impacts of
RegTech's on compliance costs and risk
management as perceived by the Saudi Bank's
employees. The financial technology RegTech has
an extensive effect on the banking system of Saudi
Arabia, as explained by the results of the smart PLS.
RegTech solution elicited both direct and indirect
effects. The duration of its usage (DR) had a
statistical influence on the Risk Management
Effectiveness (RME) factor, unlike the Compliance
Costs (CCS). Improved compliance cost,
operational efficiency, and risk management
correlated positively.
In addition, the analysis establishes a connection
between digital technology adoption and innovation
in leadership; this implies that leadership in banking
technology is a crucial determinant. The study
further established a strong relationship between
employee positions and performance and
compliance indicating that employee engagement
plays an integral role in applications of RegTech.
The factor analyses attest to high-reliability values
across concepts, implying consistent and reliable
measurements. The Saudi bank employees consider
adopting regulatory technology as an element that
will enhance performance and job satisfaction in the
workplace.
The study proved that organizational support,
especially spending levels and tool plurality,
influences operational efficiency in Saudi bank
RegTech implementation in terms of moderation.
Acknowledgement:
The Deanship of Scientific Research funded this
work at Jouf University through the Fast-track
Research Funding Program.
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Contribution of Individual Authors to the
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