SOFTWARE AND INFORMATION SOLUTIONS ENGINEERING WITH A HIGH LEVEL OF REGULATION: A COMPARISON OF FINTECH AND CIVIL ENGINEERING

ИНЖЕНЕРИЯ ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ И ИНФОРМАЦИОННЫХ РЕШЕНИЙ В УСЛОВИЯХ ЖЕСТКОГО РЕГУЛИРОВАНИЯ: СРАВНЕНИЕ ФИНАНСОВЫХ ТЕХНОЛОГИЙ И ГРАЖДАНСКОГО СТРОИТЕЛЬСТВА

Никиташин Максим Евгеньевич

аспирант, ассистент, Приморский университет,

Словения, г. Копер

Лесьяк Душан

научный руководитель, доктор, профессор, Приморский университет,

Словения, г. Копер

ABSTRACT

This article examines how different levels of regulation shape information solutions engineering in different sectors, using a PESTLE-based comparison of the USA, China, Russia and Slovenia. Two modes of regulation are identified. The first is high or strict in vertical sectors such as civil engineering, agriculture, logistics, MedTech, and the military industry, which have similarities and where the research results can be mutually transferable. The second mode is low or weak, the most notable representative of which is the hospitality industry. The FinTech - civil engineering IT comparison shows that both sectors are highly regulated, yet for different reasons. However, in both sectors, regulation similarly encourages formal governance, documentation, and risk-aware development. The study shows that regulatory intensity strongly affects management and implementation across different national environments and reveals similarities and differences between industries.

АННОТАЦИЯ

В данной статье рассматривается, как различные уровни регулирования влияют на разработку информационных решений в разных секторах, с использованием PESTLE-анализа США, Китая, России и Словении. Выделены два режима регулирования. Первый - высокий или жесткий в таких вертикальных секторах, как гражданское строительство, сельское хозяйство, логистика, медицинские технологии и военная промышленность, которые имеют сходства, и результаты исследований в которых могут быть взаимно переносимы. Второй режим - низкий или слабый, наиболее ярким представителем которого является индустрия гостиничного дела. Сравнение финтех и IT индустрии гражданского строительства показывает, что оба сектора сильно регулируются, но по разным причинам. Однако в обоих секторах регулирование аналогичным образом способствует формальному управлению, документированию и разработке с учетом рисков. Исследование показывает, что интенсивность регулирования сильно влияет на управление и внедрение в различных национальных условиях и выявляет сходства и различия между отраслями.

Keywords: software engineering; information solutions engineering; software and information solutions engineering; regulatory intensity; FinTech; civil engineering; PESTLE analysis; compliance-oriented development.

Ключевые слова: разработка программного обеспечения; разработка информационных решений; разработка программного обеспечения и информационных решений; интенсивность регулирования; финтех; гражданское строительство; PESTLE-анализ; ориентированная на соответствие требованиям разработка.

1. Introduction

Recently, software engineering and information solutions engineering have often been mentioned together. This trend may stem from several important studies that highlight their similarities in historical development, research topics, design issues, and current practical challenges [1; 2]. These studies also suggest that software development and the broader development of information solutions should be examined more closely, as a combined field of software and information solutions engineering.

Recently, software engineering and information solutions engineering have often been mentioned together. This could be because several important studies show they share many similarities in their historical development, research topics, design issues, and practical challenges today [1; 2]. These studies suggest that software development and the wider development of information solutions should be studied together as software and information solutions engineering.

Numerous studies in software and information solutions engineering and financial technology (FinTech) highlight economic and management differences between these fields in general and in the finance sector [3; 4; 5]. This applies to service industries as well as various other sectors, including civil engineering IT [6; 7], agricultural IT [8], logistics IT [9], medical technology (MedTech) [10], military IT [11], and hospitality industry IT [12; 13].

Among the others, the first is the most advanced in terms of researching, explaining and controlling IT integration based on pre-research [14]. Therefore, it was selected for analysis and comparison with the FinTech field.

The mentioned differences include management approaches, methods and methodologies, economic principles, and legal frameworks related to developing, implementing, and using IT solutions in these industries [15; 16; 17; 18]. Highly regulated industries tend to stick to traditional management methods, like Waterfall, and established economic principles. In contrast, less regulated industries often adopt more modern, flexible, and efficient management techniques, such as agile [15; 19], and economic principles like open-source software [17] or platform economics [14]. In this context, regulatory intensity plays an important role in shaping software and information solutions engineering across industries. Highly regulated sectors, like FinTech and civil engineering IT, which have already been mentioned, require compliance-focused, well-documented, risk-aware, and often more formal development practices.

This regulation impacts governance, cybersecurity, interoperability, and project management right from the start [3; 5; 7]. On the other hand, less regulated sectors, like hospitality IT, are influenced more by customer expectations, operational efficiency, service quality, and market competition. This allows for greater flexibility, quicker experimentation, and more agile innovation. However, issues like privacy, payment security, and cybersecurity still pose relevant challenges [12; 13; 20; 21].

The comparison between FinTech and civil engineering IT is also highly relevant. Both sectors operate under strong regulatory pressure, but for different reasons. FinTech is shaped mainly by financial stability, consumer protection, data governance, payment security, and cybersecurity. Civil engineering IT is influenced by public procurement, Building Information Modeling (BIM) requirements, construction standards, infrastructure policy, and lifecycle accountability. This makes the topic actual for understanding in similar terms how high regulation affects software and information solutions engineering, project management, documentation, risk control, and innovation in different sectoral environments.

The object of this research is the influence of high regulation on software and information solutions engineering in FinTech and civil engineering IT, with attention to how legal, organizational, technological, and management requirements shape software and information solutions development, implementation, governance, and risk control in both sectors.

The subject of this research is the specific differences and similarities in software and information solutions engineering practices between FinTech and civil engineering IT, especially regarding regulation, compliance, project management, documentation, risk awareness, interoperability, and lifecycle governance.

2. Methodology

For this research, it was decided to analyze different vertical economic sectors using the PESTLE model. It was planned to analyze specific countries and then compare the results across these countries and sectors.

PESTLE is a strategic analysis model that looks at the macro-environmental forces influencing organizational decisions. It focuses on Political, Economic, Social, Technological, Legal, and Environmental factors. This model helps identify opportunities and threats in the external environment so that managers can adjust strategies to fit broader changes. However, it is worth noting that many scholars criticize the model for being too broad, largely qualitative, and sometimes not detailed enough unless used with other tools.

For this study, were selected countries that are currently among the most politically, economically and technologically developed powers: the United States (USA), China, Russia, and the European Union (EU). Slovenia was chosen as the representative country in the EU. The main reasons for choosing individual countries for analysis include the disunity of the EU and the significant independence of its members in politics and economics.

Here three main criteria were used to select these countries. The first is their global political and economic importance. The second is their level of technological development. The third is the diversity of their regulatory models. Here the USA and China were chosen as they represent two influential global economic and technological powers, but each has different traditions regarding markets and state regulation. Russia was included for its large, strategically important and sovereignty-focused regulatory environment. It also remains a significant world power, especially politically. The EU acts as a major regulatory and economic player, yet its member states maintain independence in their political and economic practices. Together, these selected countries allow for comparisons among market-driven, state-directed, sovereignty-focused, and EU-influenced approaches to software and information solutions engineering regulation.

Table 1.

Slovenia - EU Comparison

The main objectives of the research were to examine whether differences exist between individual sectors in terms of their level of regulation and, if so, to determine how these differences influence the engineering of software and information solutions within those sectors. The study also aimed to compare the selected vertical sectors with one another and then, based on the results of this comparative analysis, develop findings and recommendations for experts, managers and researchers working in the field.

The research questions were defined as follows:

1. Are there differences between the selected sectors in terms of the level of regulation?
2. If such differences exist, what are the main differences between the selected sectors regarding regulatory requirements?
3. How do these regulatory differences affect the engineering of software and information solutions in the selected research areas?
4. How do these differences compare across different vertical sectors?
5. How does their influence on software and information solutions engineering vary across different vertical sectors?

In general, the research was carried out by first defining the research questions and then selecting relevant databases, keywords, and countries based on the scope of the study. The search results were filtered through the screening of titles, abstracts, and full texts, after which relevant data were extracted and analysed. To support a structured comparison, individual groups or clusters were created by identifying recurring themes, methods, sectors, technologies, variables, and theoretical perspectives. Studies with similar characteristics were then grouped together to enable a clearer analysis and comparison.

More specifically, the literature review was conducted by selecting scientific and professional sources according to their relevance, visibility, and recognition in major academic databases, including Google Scholar, Scopus, and Web of Science (WoS), which are among the largest and most widely recognized international and interdisciplinary databases. The recognition of sources was assessed mainly through citation counts. The selected literature was then organized into sectoral clusters, namely FinTech and civil engineering IT, to compare how different levels of regulation affect the engineering of software and information solutions across industries and countries.

3. Research

3.1. Theoretical Basis

The topic of high regulated industries comparison develops from earlier research on FinTech software and information solutions engineering, agile and traditional methodologies, and regulated financial software and information solutions projects, as well as studies on BIM, digital twins, and IT implementation in civil engineering. Scientific sources show that both sectors require structured management, documentation, risk control, and compliance-oriented development. Simultaneously, FinTech is driven mainly by financial and data regulation, while civil engineering IT is shaped by BIM, infrastructure policy, procurement, and lifecycle governance.

The theoretical foundation of this topic is based on research related to regulated software and information solutions engineering, FinTech project management, BIM-driven digitalisation, and the use of digital twins in civil engineering. The key sources include the previously mentioned studies by Jinasena et al. [3], Munteanu and Dragos [5], and Letelay et al. [35], which address the development of software and information solutions in the FinTech sector. These are complemented by the works of Mahalingam et al. [36], Pan and Zhang [7], and Succar [37], which focus on BIM, digitalisation in civil engineering, and lifecycle-oriented IT governance. Together, these sources provide a strong basis for understanding the similarities between the two sectors. In particular, they show that both FinTech and civil engineering IT require structured management approaches, clear documentation, regulatory and professional compliance, interoperability between systems, and development practices that take risk into account.

3.2. FinTech

FinTech refers to the application of digital technologies in financial services, including areas such as payments, banking infrastructure, consumer finance, digital assets, open banking, cybersecurity, and regulatory technology. In this article, FinTech is understood as a highly regulated sector in which the engineering of software and information solutions is strongly influenced by requirements related to financial stability, consumer protection, secure payments, data governance, and cybersecurity. As a result, innovation in FinTech typically follows a compliance-first approach. This means that governance, documentation, operational resilience, and risk-aware development must be considered from the earliest stages of software and information solutions engineering [3; 5; 35].

The breakdown of the entire analysis for FinTech is presented in Table 2.

Table 2.

Breakdown of PESTLE Analysis for FinTech

3.3.  Civil Engineering IT

Civil engineering digitalisation in recent years has included developing foundational BIM concepts, performance frameworks, and maturity models for the built environment.

The most significant activity there was the BIMe Initiative (BIM Excellence Initiative), which is a non-profit, community-based program built around research of Dr. Bilal Succar. It aims to accelerate digital transformation in construction by creating open-access frameworks, benchmarks, tools, templates, and learning resources for individuals, organisations, projects, and even whole markets.

In practice, BIMe is known for resources such as the BIM Dictionary, the BIM Competency Table, the BIM Maturity Matrix, model-use resources and broader knowledge structures that help connect research with industry practice. The initiative emphasizes openness, peer review, modular knowledge structures, and international collaboration rather than top-down or purely prescriptive BIM adoption policies.

As was mentioned, the field is very advanced in terms of digitalization, its study and regulation [82]. The results of digitalization studies in the field show, among other things, that mandates, standards, a clear vision, strong leadership, precise requirements, motivators, long-term cooperation, digital support, and consideration of country specifics are important for an effective process from the state level [37]. Examples of effective policies include cooperation with both academia and industry, a combination of national and local measures and national digitalization plans [37].

The breakdown of the entire analysis for civil engineering IT is presented in Table 3.

Table 3.

Breakdown of PESTLE Analysis for Civil Engineering IT

As part of the analysis of the political dimension, Table 4 provides an additional approximate estimate of the number of regulations in the selected industries across the selected countries. For the United States, the estimate was based on data from the Federal Register [137]. For China, it relied on data from the Database of National Laws and Regulations [138]. In the case of Russia, the approximate number of industry-related regulations was estimated through searches in the official legal-act databases of the Ministry of Justice [139; 140]. However, the Russian results should be interpreted with caution. Russia’s regulatory system includes not only laws and decrees, but also registered executive acts, technical standards, and mandatory requirements. Therefore, the figures should be understood as approximate indicators of regulatory intensity rather than precise counts of individual regulations. For Slovenia, the estimate was based on data from the Legal Information System of the Republic of Slovenia (PisRS) [141].

It is important to note that the US FinTech sector is a special case, as almost every single state in the United States has its own regulations in the field. Therefore, the volume is high due to the dispersion of regulations, but not their strictness. Similar peculiarities apply to US civil engineering.

Table 4.

Number of Regulations in the Industries Analysed

4. Discussion

The comparison between FinTech and civil engineering IT shows that both sectors operate under relatively high levels of regulation, but the nature and effects of that regulation differ significantly. In FinTech, regulation is primarily driven by concerns related to financial stability, consumer protection, payment security, data rights, and cybersecurity. This creates an environment in which software and information solutions engineering must prioritize compliance, resilience, traceability, and trust. As a result, IT development in FinTech often requires strict governance, formal controls, and carefully documented processes, even when firms attempt to remain innovative and competitive.

By contrast, civil engineering IT is shaped less by financial or consumer-risk regulation and more by state mandates, procurement systems, construction standards, BIM requirements, infrastructure policy, and lifecycle accountability. This means that regulation in building IT is often embedded directly into project structures and public-sector requirements. Compared with FinTech, the regulation of building IT is more visibly connected to long-term planning, interoperability, model standardization, and the coordination of multiple stakeholders across design, construction and operations. In this sense, building IT appears even more institutionalized and structurally regulated than FinTech, especially in countries where BIM adoption is state-led or formally mandated.

Shortly concluding, from an IT-engineering perspective, both sectors demand compliance-oriented development, but they do so for different reasons. FinTech emphasizes secure transactions, consumer-data management, and legal oversight of digital financial activities, Simultaneously, civil engineering IT focuses on information modelling, digital permitting, infrastructure integration, and the governance of digital assets over the lifecycle of physical projects. This means that traditional or hybrid project-management approaches may remain more suitable in both areas than purely agile models, although for different reasons. FinTech because of systemic financial risk, and building IT because of procurement rigidity, technical interoperability, and regulatory formalization. Overall, the comparison suggests that high regulation does not produce a single model of IT engineering. Instead, each sector interprets regulation through its own economic and institutional logic. At the same time, there are many similarities between the industries that make research results in both fields interchangeable and mutually applicable.

A direct comparison of Slovenia and Russia, which share many similarities in history, environment and culture, in this context also highlights notable and important similarities. In FinTech, both countries show a strong role of the state and regulators in shaping the digital-finance environment, especially in areas such as payment infrastructure, cybersecurity, data governance and legal compliance. In both cases, IT engineering is therefore influenced by a compliance-oriented logic in which trust, resilience, and regulatory adaptation are essential. In civil engineering IT, Slovenia and Russia are also similar in that digitalisation is strongly linked to public policy, formal requirements and broader national or supranational development goals. In both contexts, software and information solutions engineering is driven not only by market demand, but also by institutional frameworks that emphasize structured implementation, interoperability, and accountability. As a result, both countries illustrate how highly regulated sectors tend to favor more formalized and coordinated approaches to IT development.

The broader cross-country comparison also adds value to the study. China and Russia generally demonstrate a stronger role of state direction, while the United States represents a more fragmented but still highly demanding regulatory environment. Slovenia, in turn, reflects a regulatory framework shaped by the European Union, along with the practical limitations of a smaller market.

At the same time, the study identifies a recurring weakness across the analyzed sectors. Sustainability is often recognized as important, but it is usually addressed in broad terms rather than translated into concrete operational practices. This points to an important direction for future research, which is examining how sustainability requirements can be turned into practical IT engineering methods that support regulatory compliance but at the same time improve sector-specific efficiency.

5. Conclusion

In conclusion, it can be stated that regulation operates in two main modes. The first is a high-regulation mode, which is typical of vertical sectors such as FinTech, civil engineering, agriculture, logistics, MedTech, and the military industry. These sectors share certain characteristics, meaning that some research findings may be transferable between them. The second is a low-regulation mode, with the hospitality industry serving as the clearest example.

The comparison between FinTech and civil engineering IT shows that both sectors belong to the more highly regulated side of software and information solutions engineering, but they are regulated for different strategic reasons. FinTech is primarily governed through rules related to financial stability, consumer protection, payment security, data governance, and cybersecurity, while civil engineering IT is shaped more strongly by public procurement, BIM mandates, infrastructure policy, interoperability requirements, and lifecycle accountability. In both cases, software and information solutions engineering must operate within a structured environment where compliance, traceability and reliability are central design conditions rather than secondary concerns. This means that software and information solutions development in both sectors tends to require stronger governance, more documentation and closer alignment with external institutional requirements than is typical in less regulated industries.

At the same time, the comparison demonstrates that high regulation does not produce absolutely identical engineering practices. In FinTech, regulation is centered on trust in digital financial transactions and system resilience. In civil engineering IT the regulation is tied to long-term project coordination, standardization and public-sector control over digital construction processes. Nevertheless, the two sectors share a common conclusion, that regulation pushes software and information solutions engineering toward more formalized and risk-aware development models, often favoring structured or hybrid methodologies over purely flexible approaches. Thus, the study confirms that both sectors illustrate how regulation can stabilize innovation, but also constrain speed and experimentation. And again, importantly, as already mentioned, there are many similarities between industries that can make research results in both fields interchangeable and mutually applicable.

It is also important to note that the vertical markets analyzed in different countries, including Russia and Slovenia, show several similarities, as discussed in the comparative analysis. These similarities suggest that the findings identified in the research are not coincidental.

As mentioned earlier, the countries selected for the analysis differ in their market, regulatory, and institutional conditions. However, the results are complementary in many respects across all of them. Therefore, it can be concluded that the research findings, as well as the recommendations developed on their basis and presented below, are valid for the analysed countries and sectors. They may also be broadly applicable to other countries and sectors with similar characteristics.

Based on the research findings, the following recommendations can be made:

1. Software and information solutions engineering practices should be aligned with the level of sectoral regulation.
2. Highly regulated sectors such as FinTech and civil engineering IT should prioritize compliance by design, strong governance, documentation, risk control, and structured or hybrid development methodologies.
3. Cross-sector learning between highly regulated industries should be encouraged, as many governance, documentation, and lifecycle management practices are transferable.
4. Across all sectors and countries, digital skills, organizational readiness, interoperability, and standardization are critical success factors, so it is essential to develop them.
5. Sustainability requirements should be translated into concrete and measurable software and information solutions engineering practices rather than remain general policy goals.

Overall, this research is significant because it shows that differences in regulatory intensity play a fundamental role in shaping sector-specific models of software and information solutions engineering. Future research should therefore broaden the comparison to include additional industries, improve the way regulation is measured across different contexts, and examine more precisely how sustainability, management methodologies, and management approaches can be translated into practice within both highly regulated and lightly regulated digital environments.

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