Research Articles Open Access

Computational Blue Finance Governance: RegTech and Automated Compliance for Sustainable Ocean Investment

Kolawole Afuwape *
* Corresponding author: Kolawole Afuwape ( afuwapekolawole@gmail.com )
Available online October 1, 2026
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Abstract

As blue economy activities continue to grow, the demand for sustainable investments in the ocean increases and expands to include blue bonds, marine renewable energy resources, sustainable fisheries, coastal infrastructure, and conservation. The study is proof of how Regulatory Technology (RegTech) and compliance computational governance can support blue finance by automating regulatory and sustainability requirements. The study is doctrinal and multidisciplinary, utilizing legal research, sustainable finance, and RegTech methodologies in the field of computational law. The paper introduces the existing regulatory frameworks and blue finance-related standards, requirements, and guidelines. This study covers RegTech solutions, including artificial intelligence (AI), regulatory application programming interfaces (API), distributed ledger technologies, smart contracts, automated reporting, and digital verification tools. The paper examines the positive effects of the use of RegTech in blue finance and how regulatory compliance can be converted into processes that are verifiable and auditable, which in
turn would encourage sustainable finance. The study illustrates that RegTech can contribute to making regulatory processes more efficient, formalized, clear, and reliable, promoting sustainable investments. The paper also proposes a model of computational governance for blue finance, which integrates regulatory provisions, sustainability requirements, digital platforms, automation of compliance procedures,
verification procedures, and supervision. The study highlights problems, such as the danger of algorithmic obfuscation, informational
fragmentation, interoperability concerns, cybersecurity risks, and legal responsibility. The study argues that through RegTech solutions,
computational governance can provide a feasible regulatory framework for blue finance, so long as automated compliance processes are transparent, verifiable, and accountable.

Keywords

RegTech blue finance computational law automated compliance sustainable ocean investment

Introduction

The development of the Blue Economy has increased the need for Blue Finance, including blue bonds, sustainable fisheries, marine renewables, coastal infrastructure, and ocean-conservation investment, to raise funds for sustainable oceans [1]. However, these activities operate within a complex regulatory framework that encompasses international ocean law, environmental norms, financial-market rules, sustainability standards, and corporate disclosure obligations. This plurality of regulations poses substantial challenges for compliance, information-gathering, and decision-making for investors, financial institutions, project developers, and regulators. Traditional compliance mechanisms, which rely heavily on manual legal interpretation, periodic reporting, and ex-post regulatory assessments, have proven insufficient in an investment environment characterized by escalating regulatory obligations for investment and an abundance of financial, environmental, and ocean-related data [2]. The convergence of law and computer science through RegTech has the potential to address these shortcomings by deploying AI, natural-language processing (NLP), machine-readable regulation, legal ontologies, regulatory APIs, blockchain technology, smart contracts, and automated monitoring [3]. However, literature has focused predominantly on banking, securities, insurance, anti-money laundering, and traditional financial regulation, while blue-finance literature has explored financing instruments, sustainability standards, and ocean-governance challenges [4]. Thus, there has been limited scholarly engagement with the extent to which computational legal techniques can transform fragmented ocean, environmental, financial, and sustainability obligations into interoperable, machine-readable, and auditable compliance systems for sustainable ocean investment [5]. This study addresses this lacuna by conceptualizing computational blue finance governance as a mechanism for integrating legal rules, sustainability requirements, and data through automated compliance technologies. The paper makes three principal contributions.

  • First, it develops a computational-law framework for translating natural-language blue finance obligations into legal ontologies, regulatory taxonomies, and rules-as-code.

  • Second, it proposes a comprehensive RegTech architecture linking regulatory requirements to financial, environmental, and ocean data, AI-driven compliance analysis, regulatory APIs, automated reporting, blockchain verification, and continuous monitoring.

  • Third, it identifies governance safeguards for automated compliance, including transparency, explainability, data integrity, interoperability, cybersecurity, human oversight, contestability, and accountability. The paper argues that computational RegTech technologies can reduce compliance costs, enhance sustainability assurance, and improve investor confidence, but that automation should be grounded in legally intelligible rules and meaningful human accountability to realise the transformative potential of technology on the rule of law.

1.1. Research Hypothesis

The use of regulatory technology and automated compliance procedures, or the computational blue finance governance, reduces the costs of compliance monitoring, enhances transparency, and expedites the flow of capital towards authentic sustainability development in marine investment funds. By using automated procedures, smart contracts, telemetry, and decentralized data and financial accounting, computational governance is a mechanism that prevents blue washing and ensures that private capital incentives are consistent with international law. Thus, the application of automated compliance processes helps to create a standard measure of ocean integrity and demonstrates that automated compliance procedures are an integral part of any successful fundraiser for the blue economy.

1.2. Research Objectives and Questions

Objective 1: Regulatory Tech Mapping Description: Research objective: To investigate the existing capabilities and design principles of Regulatory Technology or RegTech, used for automating compliance and risk management in sustainable ocean investments.

Research question: How could RegTech frameworks be designed to accurately trace compliance with blue finance practices, and what technical limitations might hinder their adoption?

Objective 2: The conceptual design represents a blockchain-based and smart-contract-controlled governance model that seeks to enforce real-time regulatory compliance while also preventing blue-washing by ensuring continuous automated assessment of relevant ocean-related activities against a set of ESG criteria.

Research question: How could systems of automated compliance be designed so that they constantly check that a given ocean investment reflects its stated goals?

Objective 3: Automation vs. Policy Description: Research objective: To analyze the legal and policy implications of automating compliance checks for international law, particularly in the complex domain of maritime border governance.

Research question: How could a shift from human to algorithmic governance be implemented, and what conflicts would arise if automated systems made decisions that appear to contradict established international treaties or agreements?

1.3. Contribution to the Study

The study contributes to the emergent field of computational law, specifically by advancing a computational blue finance governance framework that couples ocean governance, sustainable finance, and RegTech. The existing blue finance scholarship has predominantly focused on financial mobilization, sustainable investments, conservation finance, blue bonds, and the development of the oceanic sector. Simultaneously, research has tended to focus on conventional financial markets, banking, securities, anti-money-laundering and prudential compliance. By bridging the fields together, the study conceptualizes blue finance regulation as computationally operable legal governance, thus extending the scope of computational-law scholarship into the hitherto underdeveloped area of sustainable ocean investment.

A second contribution is reflected in the development of a legal-to-computational compliance pathway that transforms complex regulatory requirements into machine-readable compliance rules. The study proposes a sequence of legal rule identification, NLP-assisted extraction, legal ontology development, rules-as-code formalization, computational compliance testing, automated monitoring, verification, and human legal review. The study offers a methodological bridge between doctrinal legal analysis and computational implementation and demonstrates how legal obligations related to sustainability, disclosure, use of proceeds, fisheries management, protection, investment governance, and similar areas may potentially be translated into operational compliance parameters.

Third, the study contributes a computational blue finance governance Architecture (CBFGA), which incorporates seven interconnected layers, including legal and regulatory sources, legal processing, legal knowledge representation, regulatory and sustainability data, computational compliance, verification and supervision, and accountability. The architecture moves beyond viewing RegTech as being merely an efficiency-enhancing technology and conceptualizes it as a digital regulatory infrastructure that interconnects fragmented oceanic, environmental, financial and sustainability regimes. Consequently, the study offers a structured model through which regulators, financial institutions, investors, certification bodies, technology providers, and other marine sector entities may potentially interact within a more coherent compliance ecosystem.

The study further contributes by underlining the importance of digital evidence and regulatory data integrity to computational blue finance governance. The Seychelles Blue Bond case illustrates the challenges of maintaining effective monitoring and alignment of financial instruments with Blue Economy objectives, while the Philippine blockchain-enabled seafood traceability case provides an example of how digital provenance and supply-chain information may be leveraged for fisheries-related verification. Collectively, the cases demonstrate the complementary role of financial compliance infrastructure and reliable marine sector data infrastructure, while demonstrating that blockchain, AI, or automated systems cannot independently establish legal truth, and cannot substitute institutional verification.

Finally, the study contributes to policy and regulatory scholarship by suggesting a pathway towards interoperable, adaptive and accountable blue finance regulation. It underlines that effective computational governance requires more than technological deployment: it requires harmonized regulatory taxonomies, machine-readable legal standards, interoperable data structures, common sustainability indicators, regulatory APIs, reliable verification mechanisms and clearly allocated institutional responsibilities. The study makes a conceptual contribution to the field of computational legal theory, while also providing a practical governance framework for regulators and market participants seeking to make sustainable ocean investment more transparent, monitorable, verifiable and legally accountable.

Complete Article

The complete article, including all figures, tables, equations and algorithms, is available in the official publication PDF.

Data Availability

None

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