FinTech, RegTech & SupTech: Transforming the Global Battle Against Financial Crime

The rise of digital financial services has lowered barriers to entry for consumers and firms alike. With mobile-first solutions, real-time payments, decentralised finance (DeFi), and AI-enhanced services, the modern financial ecosystem is more agile and globalised than ever before. But these same innovations are being exploited by criminals seeking to launder proceeds of crime, evade sanctions, or defraud individuals and institutions.

The traditional compliance framework of manual reviews, siloed data, and periodic audits is no longer adequate. A technology-led approach is now essential. The convergence of FinTech, RegTech, and SupTech provides a comprehensive model for defence. FinTech operates on the innovation frontline, creating new vectors of exposure and opportunity. RegTech offers automation and intelligence to scale compliance functions. SupTech equips regulators with the tools to supervise, investigate, and intervene effectively.

FinTech: Redefining Finance & Recalibrating Risk

Financial Technology, or FinTech, is far more than the digitisation of traditional financial services. It marks a fundamental transformation in how financial products are delivered, accessed, and monetised. Whether through embedded finance integrated into e-commerce platforms or decentralised lending powered by blockchain protocols, FinTech represents a dynamic and disruptive ecosystem that continues to evolve faster than many regulatory frameworks can accommodate.

Building Beyond the Banking Infrastructure

Rather than operating within the established architecture of legacy banks, many FinTech companies have built alternative infrastructures. These new systems often involve application programming interfaces, tokenised assets, and peer-to-peer models. Stripe facilitates seamless international payments without the need for a banking licence. Wise offers cross-border transfers at speeds and costs that outpace many traditional financial institutions. In the decentralised finance space, platforms such as Aave offer lending and borrowing services through smart contracts without relying on intermediaries.

These developments are not simply about delivering financial services differently. They raise fundamental questions about who controls access to the financial system and how that access is regulated.

Challenger Banks & the Regulatory Spectrum

Challenger banks such as Monzo, Starling, and Atom Bank provide full banking services via digital-first platforms. Although often included in broader discussions about FinTech, they differ in one key respect. These institutions typically operate under full banking licences and are therefore subject to more rigorous regulatory oversight. In contrast, the wider FinTech sector encompasses a broad range of entities. These can include unregulated start-ups as well as specialised service providers operating under limited permissions, such as electronic money licences or regulatory sandboxes.

This diversity reflects both the strength and the complexity of the sector. It enables innovation while introducing inconsistencies in regulatory expectations and enforcement.

Innovation & Exposure to Financial Crime

The characteristics that define FinTech, including speed, scalability, and digital-first design, also create significant vulnerabilities. Features such as real-time onboarding, minimal manual review, and frictionless user experiences can be exploited by bad actors. One of the most significant risks is synthetic identity fraud. Criminals use a blend of real and fabricated personal information to construct entirely new identities that can bypass standard know your customer checks. In digital lending environments, synthetic identities are believed to account for more than 80 percent of credit fraud, highlighting the scale of the problem.

Complexity in Monitoring Transactions

The growing use of stablecoins, private wallets, and bespoke payment systems introduces further challenges in tracing transactions. As financial activity moves away from traditional rails, established anti-money laundering systems become less effective. Some FinTechs have responded by investing in scalable compliance infrastructure. Revolut, for instance, has built systems capable of supporting compliance across multiple jurisdictions. Monzo has earned recognition for publishing detailed reports on suspicious activity and customer complaints. This level of transparency remains rare in the sector.

In contrast, Starling Bank’s £29 million fine from the Financial Conduct Authority for anti-money laundering failings demonstrates what can happen when compliance does not keep pace with growth. This enforcement action illustrates the risks associated with underinvesting in control frameworks during periods of rapid expansion.

The Regulatory Horizon

As FinTechs continue to expand, pursue banking licences, and integrate cross-border services, they can expect heightened scrutiny from regulators. Supervisory attention is likely to focus on the strength of transaction monitoring systems, the handling of cryptoassets, the management of third-party relationships, and the safeguarding of data across jurisdictions.

The long-term success of the FinTech sector will depend not only on technological innovation but also on the integration of comprehensive compliance strategies from the outset. Achieving sustainable growth will require firms to align agility with accountability and ensure that innovation is supported by strong governance and effective risk management.

RegTech: From Cost-Saving Tool to Compliance Cornerstone

Regulatory Technology, or RegTech, refers to the use of advanced data analytics, artificial intelligence (AI), and automation to enhance regulatory compliance processes. Once viewed primarily as a means of reducing operational costs, RegTech has matured into a core element of the financial crime defence architecture. It now plays a pivotal role in increasing accuracy, improving responsiveness, and strengthening auditability across compliance functions.

Addressing the Shortcomings of Legacy Systems

At its foundation, RegTech aims to resolve the persistent limitations of traditional compliance models. Legacy systems, often dependent on static thresholds and rigid rule sets, are widely criticised for producing high volumes of false positives. This inefficiency burdens compliance teams and diverts resources from genuine risk indicators.

AI-driven RegTech platforms offer a more adaptive approach. These systems continuously learn from transaction behaviour and customer patterns, enabling more precise detection. In the context of transaction monitoring, this leads to more effective alert prioritisation and identification of anomalies without overwhelming analysts. Similarly, in know your customer (KYC) processes, RegTech enhances onboarding by integrating biometric authentication, document verification, and behavioural analytics. However, this evolution also introduces new risks, such as algorithmic bias in facial recognition and the emergence of deepfake technologies.

Enhancing Sanctions Screening & Reporting

Sanctions screening remains a core compliance function but has traditionally been prone to inefficiencies, particularly around false matches and the challenge of name variations. Emerging RegTech solutions now use natural language processing to interpret unstructured data, such as adverse media, court filings, or customer communications. This provides a more contextual understanding of potential risks and enhances screening precision.

Regulatory reporting is also shifting from static, periodic submissions to real-time reporting architectures. Many institutions are now building API-driven pipelines that feed data directly to regulators, allowing for a more dynamic and responsive approach to supervisory oversight.

The UK’s RegTech Ecosystem & Barriers to Adoption

The UK has established itself as a leading centre for RegTech innovation, with companies like Napier AI and ComplyAdvantage developing tools that incorporate explainable AI. These solutions are designed to bridge the gap between complex machine-learning models and the transparency demanded by regulators.

Despite this progress, adoption remains uneven. Many mid-tier and regional financial institutions face challenges integrating RegTech due to high costs, legacy infrastructure constraints, and a shortage of in-house expertise. These barriers can delay or dilute the effectiveness of deployment, undermining the potential benefits.

Accountability, Governance & Regulatory Expectations

A major concern for regulators is the opacity of automated decision-making systems. Many firms struggle to articulate how their algorithms operate, making it difficult to assure regulators of accountability and control. In response, the Financial Conduct Authority (FCA) and other bodies increasingly expect institutions to demonstrate robust algorithmic governance. This includes the ability to monitor, audit, and intervene in automated processes where necessary.

Over-reliance on third-party vendors presents another challenge. While outsourcing can deliver operational efficiencies, it also shifts risk outside the institution’s direct control. Without strong internal oversight, firms may not notice when vendor tools deteriorate in accuracy, become misaligned with risk appetites, or introduce systemic bias. In addition, poor interoperability between platforms often results in fragmented workflows and duplicated alerts, reducing overall effectiveness.

Embedding RegTech within Risk Frameworks

To realise the full potential of RegTech, implementation must be driven by risk and compliance teams rather than delegated to IT procurement alone. Solutions must integrate directly into the institution’s broader data architecture and control framework. Effective deployment requires more than technical functionality; it depends on clear governance structures, staff training, and continuous feedback mechanisms to ensure tools remain aligned with evolving regulatory expectations.

The Road Ahead: RegTech & the Rise of SupTech

The future of RegTech lies in its convergence with supervisory technology, or SupTech. In this model, compliance platforms will provide real-time, structured data directly to regulators, enabling proactive supervisory engagement. Institutions that invest today in explainable systems, integrated workflows, and transparent partnerships with regulators will be best positioned to thrive in this emerging regulatory paradigm.

SupTech: Enhancing Regulatory Oversight in a Digital Age

Supervisory Technology, known as SupTech, refers to the integration of advanced analytics, artificial intelligence and automation into the processes of regulatory oversight. Unlike traditional models that depend on periodic reporting and backward-looking analysis, SupTech enables regulators to respond to real-time data, assess systemic risks as they emerge, and identify potential breaches before they develop into major issues. This is not simply a technological upgrade but a fundamental shift towards continuous supervision and proactive, data-driven regulation.

Leadership in the UK

Regulatory authorities in the United Kingdom are among the global pioneers of SupTech adoption. The Financial Conduct Authority and the Bank of England have introduced several initiatives aimed at modernising supervision through innovation. The Financial Conduct Authority’s BLENDER system automates the processing of regulatory returns, highlighting anomalies and compliance gaps with minimal need for human review. In parallel, the Digital Sandbox allows financial firms to work alongside supervisors in a safe environment to test new technologies and approaches. This encourages innovation within a controlled and observable framework.

Global Innovation in SupTech

Elsewhere, regulators are deploying natural language processing to examine financial statements and evaluate conduct risks embedded in written communication. The Monetary Authority of Singapore has created centralised repositories known as data lakes, which store regulatory submissions for analysis using machine learning techniques. These tools help identify stress indicators, shifts in financial behaviour and emerging threats within the system. This enables regulators to take a more predictive approach to oversight rather than waiting for problems to arise.

Transforming the Regulator-Firm Relationship

SupTech is changing how regulators and financial institutions interact. Supervisors now have access to near-instantaneous information on transactions and customer behaviour, which eliminates the need to rely solely on incident reports or whistleblowing. Algorithms can detect unusual activity in transaction volumes, changes in client behaviour, or unexpected patterns in financial products. This allows for earlier identification of risks and faster regulatory responses.

Increased Responsibility for Data Quality

The shift to real-time supervision places new demands on firms. The quality, accuracy and explainability of data become central to effective oversight. Submitting inconsistent or incomplete data can disrupt regulatory processes and expose firms to further scrutiny. Regulators are also enhancing their internal capacity by hiring experts in data science and systems engineering, which enables them to interpret large and complex datasets more effectively. As a result, the traditional delay between risk identification and supervisory action is rapidly shrinking.

Implementation Challenges

While the potential of SupTech is considerable, practical challenges remain. One major obstacle is the diversity of data sources. Regulators must reconcile information drawn from outdated internal systems, new digital platforms and external vendors. Ensuring that all of this data is compatible and complete requires significant investment and coordination. Another challenge is governance. Supervisors must ensure that automated tools used to inform decisions are transparent, explainable and free from embedded bias. This includes establishing processes to test and validate algorithms regularly.

Addressing New Risks in the Digital Space

The growing influence of financial influencers who promote high-risk products through social media has created new concerns for consumer protection. These individuals, often operating outside regulatory frameworks, are encouraging speculative behaviour among retail investors. SupTech solutions that monitor online content are under consideration to address this issue. However, the use of such tools must be carefully balanced against the need to protect individual privacy and avoid excessive surveillance.

Towards a New Model of Supervision

SupTech represents a necessary evolution in regulatory oversight. It reflects a cultural transformation within supervisory bodies, requiring new skills, greater transparency and the willingness to act quickly on data insights. As financial markets become more digital and complex, regulators must adopt real-time tools to maintain effective control. The institutions that embrace this change will be better prepared to manage emerging risks and maintain public trust in the integrity of the financial system.

Strategic Recommendations

The convergence of FinTech, RegTech, and SupTech requires a recalibration of strategy across both industry and regulatory spheres. The following recommendations are based on an evolving understanding of best practices, emerging risks, and lessons from enforcement actions and innovation programmes.

• For FinTech Firms: FinTechs must move beyond minimum regulatory compliance and adopt a risk-led design philosophy. This involves embedding AML/CFT considerations into product architecture, prioritising data lineage and auditability, and conducting regular threat assessments. FinTechs should also consider investing in in-house compliance technology talent rather than relying solely on third-party vendors.

• For Financial Institutions: Banks and established institutions should adopt a layered RegTech strategy, focusing on full-stack integration rather than piecemeal procurement. Priority should be given to tools that support explainable decision-making, adaptive learning, and interoperability across legacy and cloud-based environments. Institutions must also align their RegTech roadmaps with internal audit and governance cycles to ensure control consistency.

• For Regulators: Supervisory bodies must continue evolving SupTech initiatives from pilot to policy. This includes formalising real-time data submission frameworks, standardising machine-readable regulations, and developing supervisory models that reward transparency. Regulators should also invest in ethical AI training and cross-border data-sharing protocols to maintain oversight as financial services globalise further.

• Cross-Sector Collaboration: Public-private partnerships should be leveraged to build industry-wide utility layers for KYC, sanctions screening, and fraud detection. These shared infrastructures could reduce cost burdens, enhance data quality, and improve outcomes across the ecosystem. Multi-stakeholder engagement on emerging risks such as digital identity manipulation and algorithmic bias must be embedded into regulatory planning cycles.

Conclusion

The convergence of FinTech, RegTech and SupTech represents more than technological integration. It reflects a fundamental transformation in how we understand risk, design digital infrastructure and enforce accountability in a rapidly evolving financial ecosystem. Each domain brings distinct strengths. FinTech expands access to financial services but must embed operational resilience. RegTech enhances scalability and accuracy but depends on transparency. SupTech empowers regulators with data-led oversight but requires innovation within the public sector.

Achieving true systemic resilience will rely on how effectively these three domains are aligned. Firms and regulators must embrace a model based on continuous compliance and real-time intervention, grounded in ethical governance, supported by data integrity and strengthened through industry collaboration.

As financial crime becomes more adaptive and complex, our defences must keep pace. This means investing in cutting-edge RegTech, shaping policies that anticipate risk and building strategic alliances that reinforce the entire compliance ecosystem.