The artificial intelligence (AI) revolution is reshaping the way we work, solve problems, innovate and live.
Governments and regulators globally are racing not just to harness its potential but to regulate it.
Various jurisdictions (EU, UK, US, APAC) are taking different approaches to how AI should be governed, especially in high-risk sectors like finance.
Although AI’s possibilities are limitless, it comes with challenges such as bias, misinformation, cybersecurity, fraud, data privacy, intellectual property infringement, job losses, lack of explainability and, of course, ethics.
“AI is developing faster than market regulators can make rules. Regulation will have to adapt as well”, said FCA Chief Executive Nikhil Rathi.
Successful AI leaders will introduce robust measures which protect human rights and the economy without hindering innovation or growth.
We know one thing for sure: regulation is getting more complex in line with technological advancement.
For firms, that means staying compliant isn’t just about ticking boxes. It’s about understanding a mixture of rules, making real-time decisions, and proving you can trust the AI systems behind those decisions.
At FinregE, we’ve built that trust into every layer. Our platform helps firms confidently automate compliance with AI that’s auditable, traceable, and aligned with global regulatory expectations.
Global AI regulatory standards
European Union
The EU AI Act is setting the bar globally. It labels regtech as “high-risk,” meaning tools like ours must:
- Explain how decisions are made
- Keep humans in the loop
- Document risks clearly
- Follow strict data governance rules
On top of that, the General Data Protection Regulation (GDPR) restricts how automated decisions are made (see Article 22). At FinregE, we’ve built in explainable logic, traceable outputs, and review-ready workflows so you’re covered on both fronts: the AI Act’s rules and GDPR’s transparency and accountability.
United Kingdom
In UK, the FCA has made it clear: AI needs the same oversight as any other financial risk. That means you must govern and audit algorithmic decisions properly. FinregE support that through fully auditable workflows, clear ownership tracking, and tools that explain AI recommendations in plain language.
United States
While the US lacks a comprehensive federal AI law, regulators are increasing oversight:
- The FTC warns against opaque, discriminatory algorithms. If your algorithm makes decisions (like approving a loan or targeting an ad) and you can’t explain how it works, that’s a problem.
- The SEC expects model risk management for AI in financial advice, making sure the outputs of AI tools are trustworthy and aligned to client’s best interests.
- The White House AI Bill of Rights proposes fairness, transparency, and privacy in automated systems. Although not a law yet, it calls for a safe and effective system where personal data is protected and people know what AI is doing and why.
FinregE’s real-time, transparent regulatory intelligence helps firms operating in the US in complying with these emerging expectations.
APAC
- Singapore promotes explainability and human-centric design through its Model AI Governance Framework.
- Australia’s AI Ethics principles call for reliability, contestability, and transparency.
- Japan’s AI strategy prioritises safe AI in high impact sectors like financial services.
FinregE supports multilingual, multi-jurisdictional regulatory coverage, allowing institutions across APAC to align with local ethical AI frameworks and global best practices.
What is responsible AI?
Responsible AI refers to the usage of AI that is:
- Explainable – Users should be able to understand how AI operates and what it is doing.
- Fair – Decisions need to be unbiased.
- Transparent – It is essential to understand how data moves through the system and how insights are produced.
- Accountable – There should be well-defined responsibilities, and the users should be able to review decisions
- Privacy-Respecting – AI systems need to comply to privacy regulations and safeguard private information.
These guidelines are essential for corporate trust and legal defensibility when AI is used to assess regulatory effects, suggest controls, or rank compliance concerns.
How FinregE embeds responsible AI
FinregE has operationalised responsible AI principles:
Explainability
Our Regulatory Insights Generator (RIG) uses NLP to turn regulatory text into clear summaries. Every insight is mapped to specific legal text and can be validated by compliance professionals.
Fairness and neutrality
Our AI models were developed using domain-specific financial regulation data, not generic datasets. We partnered with Imperial College London under an Innovate UK grant to study how transformer models can improve regulatory understanding. As a result, the AI became less biased and more accurate.
Transparent and auditable
Every action on our platform is logged. Every regulation tagged, reviewed, or assigned has a visible trail. This makes it easy for compliance teams and auditors to check the full decision path.
Privacy and governance
We are GDPR compliant, FSQS approved, ISO 27001 certified, and designed for safe teamwork. Role-based access, SSO, and encrypted one-time connections allow you to maintain complete control over your data.
Global compliance support
With over 1,700 sources and regulatory intelligence from over 130 nations, our platform is built for intricate, cross-border compliance without sacrificing clarity or local relevance.
Why ethics, explainability, and transparency matter in regtech
Responsible AI is about staying credible in a world where trust is fragile, and expectations are rising.
Boards want to know how compliance risks are managed. Regulators want to see systems that are auditable, explainable, and fair. And your team needs tools they can trust.
If you’re using AI in compliance, the only real path forward is a responsible one.
At FinregE, we believe that embedding ethics, transparency, and accountability into AI isn’t just the right thing to do, it’s what makes the technology truly useful. Book a demo today.
